research environment chapter 3

Integrity in Scientific Research: Creating an Environment That Promotes Responsible Conduct (2002)

Chapter: 3 the research environment and its impact on integrity in research.

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3 The Research Environment and Its Impact on Integrity in Research To provide a scientific basis for describing and defining the research environment and its impact on integrity in research, it is necessary to articulate a conceptual framework that delineates the various compo- nents of this environment and the relationships between these factors. In this chapter, the committee proposes such a framework based on an open- systems model, which is often used to describe social organizations and the interrelationships between and among the component parts. This model offers a general framework that can be used to guide the specifica- tion of factors both internal and external to the research organization that is relevant to understanding integrity in research. After its review of the literature, the committee found that there is little empirical research to guide the development of hypotheses regard- ing the relationships between environmental factors and the responsible conduct of research. Thus, the committee drew on more general theoreti- cal and research literature to inform its discussion. Relevant literature was found in the areas of organizational behavior and processes, ethical cultures and climates, moral development, adult learning and educational practices, and professional socialization.1 1For general references on organizational behavior and processes, see Donabedian (1980), Hamner and Organ (1978), Harrison (1994), Katz (1980), Katz and Kahn (1978), Peters (1978), Peters and Waterman (1982), and Pfeffer (1981). For general references on ethical cultures and climate see Ashforth (1985), Schneider and Reichers (1983), and Victor and Cullen 49 

50 INTEGRITY IN SCIENTIFIC RESEARCH THE OPEN-SYSTEMS MODEL The open-systems model depicts the various elements of a social or- ganization; these elements include the external environment, the organi- zational divisions or departments, the individuals comprising those divi- sions, and the reciprocal influences between the various organizational elements and the external environment (Ashforth, 1985; Beer, 1980; Daft, 1992; Harrison, 1994; Katz and Kahn, 1978; Schneider and Reichers, 1983). The underlying assumptions of the open-systems model and its various elements are as follows (Harrison, 1994): 1. External conditions influence the inputs into an organization, af- fect the reception of outputs from an organization’s activities, and di- rectly affect an organization’s internal operations. 2. All system elements and their subcomponent parts are interrelated and influence one another in a multidirectional fashion (rather than through simple linear relationships). 3. Any element or part of an organization can be viewed as a system in and of itself. 4. There is a feedback loop whereby the system outputs and out- comes are used as system inputs over time, with continual change occur- ring in the organization. 5. Organizational structure and processes are in part determined by the external environment and are influenced by the dynamics between and among organizational members. 6. An organization’s success depends on its ability to adapt to its environment, to tie individual members to their roles and responsibilities within the organization, to conduct its processes, and to manage its op- erations over time. THE OPEN-SYSTEMS MODEL OF RESEARCH ORGANIZATIONS Figure 3-1 shows the application of the open-systems model to the research environment, which can include public and private institutions, such as research universities, medical schools, and independent research organizations. As noted above, any element or part of an organization can (1988). For general references on moral development, see Kohlberg (1984), Rest (1983), and Rest et al. (1999). For general references on adult learning and educational practices, see Brookfield (1986), Cross (1981), and Knowles (1970). For general references on professional socialization, see Schein (1968), Siehl and Martin (1984), Van Maanen and Schein (1979), and Wanous (1980). 

External Environment Resear ch Or ganizat ion Or ganizat ional St r uct ur e -Policies, procedures, codes -Roles and responsibilities Out put s/ Out com es I nput s/ Resour ces -Decision-making practices -Missions and goals, objectives, strategies Funding -Technology Resear ch-Relat ed Act ivit ies -Level and source -Quality/quantity of activity Hum an Resour ces Or ganizat ional Pr ocesses -Leadership Resear ch I nt egr it y -Training and experience -Competition -Knowledge of and attitudes toward -Sociocultural and -Supervision ethical standards psychological background -Communication -Behavioral adherence to standards -Socialization -Organizational learning Et hical Cult ur e and Clim at e Feedback FIGURE 3-1 Open-systems model of the research organization. This model depicts the internal environmental elements of a research organization (white oval), showing the relationships among the inputs that provide resources for organizational func- tions, the structures and processes that define an organization’s operation, and the outputs and outcomes of an organization’s activities that are carried out by individual scientists, research groups or teams, and other research-related programs. All of these elements function within the context of an organization’s culture and climate. The internal environment is affected by the external environment (shaded area; see Figure 3-2 for further detail). The system is dynamic, and, as indicated by the feedback arrow, outputs and outcomes affect future inputs and resources. 51 

52 INTEGRITY IN SCIENTIFIC RESEARCH be viewed as a system in and of itself. For research organizations, then, this includes not only the institution itself, but also any of its departments, divisions, research groups, and so on. Figure 3-1 illustrates the research environment as a system that functions within an external environment, whereas Figure 3-2 depicts the specific factors within the external envi- ronment and their influence on the research organization. These factors within the external environment are discussed later in this section. An organization’s internal environment consists of a number of key elements—specifically, the inputs that provide resources for organizational functions, the organizational structure and processes that define an organi- zation’s setup and operations, and the outputs and outcomes that are the results of an organization’s activities. The system is dynamic, and, as indicated by the feedback arrow in Figure 3-1, outputs and outcomes affect future inputs and resources. However, all of these components exist within the context of an organization’s culture and specific climate dimen- sions—that is, the prevailing norms and values that inform individuals within the organization about acceptable and unacceptable behaviors. With respect to the committee’s focus on integrity in research, the ethical dimension of the organizational culture and climate is very important. Structurally, organizations are compartmentalized into various sub- units, including work groups or divisions (the research group or team), along with other defined sets of organizational activities and responsibili- ties (e.g., programs that educate members about the responsible conduct of research, institutional review boards [IRBs], and mechanisms for dis- closing and managing conflicts of interest). The operation of these pro- grams and their overall effectiveness influence researchers’ perceptions of the organization’s ethical climate. Individuals within an organization exist both within and across these defined groups and sets of activities. Given this, it is important to differentiate between an organizational level of analysis (e.g., the research university, medical school, and independent research organization) vis-à-vis the group level of analysis (e.g., the re- search group or team) and the individual level of analysis (e.g., the indi- vidual scientist or researcher). Inputs and Resources In its examination of research environments, the committee focused on two input and resource factors of importance: the levels and sources of funding for scientific research, and the characteristics of human resources. These inputs and resources are obtained from an organization’s external environment and are used in the production of an organization’s outputs. 

THE RESEARCH ENVIRONMENT AND ITS IMPACT 53 Funding The research funding that an organization receives is distributed to research groups or teams and to individual scientists. Funding levels may increase and decrease over the years, both for the organization as a whole and for individual research groups. Just as the overall level of funding available for research within society affects the scientific enterprise as a whole, the level of funding coming into a particular research organization or research team also affects behavior. The impacts that the level of funding and the competition over fund- ing have on the responsible conduct of research are not clearly under- stood. There is some limited evidence that in highly competitive environ- ments, individuals with a high “competitive achievement striving” are at risk for engaging in misconduct, particularly when they are faced with situations in which their expectations for success cannot be reached by exerting additional effort (Heitman, 2000; Perry et al., 1990). Encouraging a high level of individual integrity in research, despite vigorous competi- tion for funding, presents a significant challenge for research organiza- tions. Human Resources The human resources available to a research organization are also important to the analysis of integrity in research. The background charac- teristics of scientists coming into a research organization influence its structure and processes as well as its overall culture and climate, and these factors, in turn, influence the responsible conduct of research by individual scientists. Scientists (whether they are trainees, junior research- ers, or senior researchers) entering into a research organization will have competing professional demands (e.g., research, teaching, practice, and professional service), and thus there are likely to be conflicting commit- ments. The dynamics of these competing demands and conflicting com- mitments change as individual scientists become integrated into the re- search organization, taking on specific roles and responsibilities. Also, scientists enter into an organization with various educational and cultural backgrounds. They have different conceptions of the collabo- rative and competitive roles of the scientist, different abilities to interpret the moral dimensions of problems, and different capacities to reason about and effectively resolve ethical problems. These individual differences will influence organizational behavior, in general, and research conduct, in particular, in complex and dynamic ways. Given this variation in human resource input into the research orga- nization, it is particularly important for institutions to socialize newcom- 

54 INTEGRITY IN SCIENTIFIC RESEARCH ers and provide them with an understanding of the organization and how to act within it. As in any organization, newcomers must learn the logis- tics of their organization, the general expectations of their roles by peers, the formal and informal norms governing behavior, the status and power structures, the reward and communication systems, various organiza- tional policies, and so on (Katz, 1980). Within research organizations, individual differences are complicated by the international nature of the scientific workforce and the corresponding sociocultural differences. Therefore, it is particularly important for research institutions to create an environment in which scientists are able to gain an awareness of the responsible conduct of research as it is defined within the culture, to understand the importance of professional norms, to acquire the capacity to resolve ethical dilemmas, and to recognize and be able to address con- flicting standards of research conduct. Organizational Structure and Processes Structure To better understand the impact of the research environment on in- tegrity in research, it is important to focus on the organizational elements that characterize its structure—those elements that are more enduring and less prone to change on a day-to-day basis. These elements include an organization’s policies and procedures; the roles and responsibilities of members of the organization; decision-making practices; mission, goals and objectives, including the strategies and plans of the organization; and technology. Policies, Procedures, and Codes The formalization of policies and prac- tices to support the responsible conduct of research is important in the analysis of research environments and their influence on integrity in re- search. Chapter 2 identified a number of the practices that are essential to the research environment. Specifically, a research organization should have explicit (versus implicit or nonexistent) procedures and systems in place to fairly (1) monitor and evaluate research performance, (2) distrib- ute the resources needed for research, and (3) reward achievement. These policies and procedures should include criteria related to the responsible conduct of research that are applied consistently. Furthermore, research organizations support integrity in research when they have efficient and effective systems in place to review research involving humans and ani- mals, manage conflicts of interest, respond to misconduct, and socialize trainees and other scientists into responsible research practices. The speci- 

THE RESEARCH ENVIRONMENT AND ITS IMPACT 55 fication of these policies and procedures helps to regulate and maintain group control and reduce uncertainty about acceptable and unacceptable behaviors (Hamner and Organ, 1978). Research has shown that strongly implemented and embedded ethi- cal codes of conduct within organizations are associated with ethical be- havior in the workplace. McCabe and Pavela (1998) describe the Univer- sity of Maryland at College Park as one example where implementation of a strong “modified”2 honor code has proven to be a successful strategy for creating a culture where cheating is viewed as socially unacceptable. Major elements of the Maryland model include (1) involving students in educating their peers and resolving academic dishonesty allegations, (2) treating academic integrity as a moral issue, and (3) promoting enhanced student-faculty contact and better teaching. The mere presence of an honor code, however, is generally not sufficient. Rather, the honor code is used as a vehicle to create a shared understanding and acceptance of the poli- cies on academic integrity among both faculty and students (McCabe and Trevino, 1993). Corporate codes have a similar effect in the workplace. An original study by McCabe demonstrated that self-reported unethical behavior was lower for survey respondents who worked in a company with a corporate code of conduct (McCabe et al., 1996). Self-reported unethical behavior was inversely correlated with the degree to which the codes were embed- ded in corporate philosophy and the strength with which the code was implemented (determined by survey questionnaire of employee percep- tions). Roles and Responsibilities The specification of roles and responsibili- ties within various research groups and teams and relevant research pro- grams (e.g., education in the responsible conduct of research, IRBs, and conflict-of-interest review committees) provides a blueprint for researcher behavior. It is particularly important to clearly define researchers’ respon- sibilities related to the responsible conduct of research. Furthermore, the 2Traditional honor codes generally include a pledge that students sign attesting to the integrity of their work, a strong, often exclusive role for students in the judicial process that addresses dishonesty allegations, and provisions such as unproctored exams. Some also require students to report any cheating observed. Modified honor codes generally include a strong or exclusive role for students in the academic judicial system, but do not usually require unproctored exams or that students sign a pledge. Modified codes do place a strong campus focus on the issue of academic integrity and students are reminded frequently that their institution places a high value on integrity (McCabe, 2000). 

56 INTEGRITY IN SCIENTIFIC RESEARCH relative positions of these responsibilities within the organizational hier- archy and the status of persons who operate them will send a clear mes- sage to the research community about the importance of such endeavors. For example, if a highly respected scientist with high status spearheads the program of education in the responsible conduct of research, and sufficient resources (in terms of both staff and financial resources) are available to carry out the program’s work, then there is a greater likeli- hood that its efforts will be taken seriously. Again, these factors have great symbolic value within the organization and provide compelling images of the organization’s ethical culture, which affects the degree to which members of the organization will internalize the norms associated with the responsible conduct of research (Pfeffer, 1981; Siehl and Martin, 1984). Decision-Making Practices How an organization reaches decisions and formulates policies will affect individuals’ perceptions of these policies and their behavioral compliance with them. Individuals are more likely to accept and adhere to policies and practices when they have played a role in their development and implementation. Hence, scientists are more likely to buy into various research policy decisions that are reached through a collaborative process among key stakeholder groups, rather than being imposed by a top-level centralized authority (Anderson et al., 1995, Saraph et al., 1989). Organizational research that focuses on the pursuit of quality and that explicitly values cooperation and collaboration to achieve maximum effectiveness leads to better decisions, higher qual- ity, and higher morale within an organization (NIST, 1999). Classically, faculty and administrators both have governing roles in academic institu- tions, and this shared responsibility facilitates the bottom-up establish- ment of rules of research behavior. Missions, Goals and Objectives, and Strategies and Plans The mission and goals of an organization specify its desired end states (e.g., becoming a “best-practice” site in terms of the protection of human research sub- jects). Objectives are the specific targets and indicators of goal attainment (e.g., becoming an accredited program and receiving recognitions and awards through scientific associations). Strategies and plans are the over- all routes and specific courses of action (e.g., allocating the resources to comply with the standards for accreditation and ensuring that the pro- gram has leadership support) to the achievement of goals. If the respon- sible conduct of research is a prominent part of the mission and goals of a research organization, along with associated objectives, strategies, and plans, then the prominence of this issue sets the tone for the organization’s 

THE RESEARCH ENVIRONMENT AND ITS IMPACT 57 ethical climate and sends a message to scientists that the responsible con- duct of research is important. Research has shown that the most success- ful organizations are those that have a vision and goals that are clearly defined, consistent, and shared among their members (Anderson et al., 1995; Deming, 1986; Freuberg, 1986; Hackman and Wageman, 1995). Technology An organization’s technology offers the methods for trans- forming system resources into system outputs. It consists of such aspects of an organization’s infrastructure as facilities, tools and equipment, and techniques. These aspects can be mental and social, mechanical, chemical, physical, or electronic. Research environments not only need the neces- sary tools and equipment for their respective types of scientific research, but they must also establish technologies (e.g., accounting systems and library and information retrieval systems) within the organization for the effective and efficient operation of the research. There may be competi- tion within an organization to acquire the various forms of technology that are of sufficient quantity and quality to facilitate research production. The availability of this technology may, in turn, attract highly skilled scientists who hope to carry out research at the cutting edge of technol- ogy. As already mentioned, the effective management of competition—in this case, for technologies—is an important element of promoting the responsible conduct of research. Processes Organizational processes, as opposed to an organization’s more stable and enduring structural elements, are the patterned forms of interaction between and among groups or individuals within an organization. Pro- cesses represent the dynamic aspects of an organization. The processes that characterize organizational dynamics are too numerous to mention here. However, in the committee’s examination of research organizations, the processes of most interest consist of (1) leadership, (2) competition, (3) supervision, (4) communication, (5) socialization, and (6) organizational learning. Leadership The level of support for high ethical standards by the lead- ership of an organization or research group can vary; leaders can be ex- tremely supportive, can show ambivalence, or can be nonsupportive. Leaders at every level serve as role models for organizational members and set the tone for an organization’s ethical climate (Ashforth, 1985; OGE, 2000; Treviño et al., 1996). Therefore, when leaders support high ethical standards, pay attention to responsible conduct of research, and 

58 INTEGRITY IN SCIENTIFIC RESEARCH are openly and strongly committed to integrity in research, they send a clear message about the importance of adhering to responsible research practices (Wimbush and Shepard, 1994). Considerable evidence from the organizational research literature supports the relationship between su- pervisor behavior and the ethical conduct of the members of an organiza- tion (Posner and Schmidt, 1982, 1984; Walker et al., 1979). Supervisors provide a model for how subordinates should act in an organization. Furthermore, supervisors have a primary influence over their subordi- nates, an influence that is greater than that of an ethics policy. Even if a company or profession has an ethics policy or code of conduct, subordi- nates follow the leads of their supervisors (Andrews, 1989). Competition The extent to which the organization is highly competi- tive, along with the extent to which its rewards (e.g., funding, recognition, access to quality trainees, and power and influence over others) are based on extramural funding and short-term research production, may have negative impacts on integrity in research. Evidence from organizational research indicates that reward systems based on self-interest and commit- ment only to self rather than to coworkers and the organization are nega- tively associated with ethical conduct (Kurland, 1996; Treviño et al., 1996). In addition, the level of unethical behavior increases in organizations where there is a high degree of competitiveness among workers (Hegarty and Sims, 1978, 1979). Given these facts, one might expect that a research environment in which competition for resources is fierce and rewards accrue to those who produce the most over the short term sends a wrong message, a message that says “produce at all costs.” Creating a reward system and policies that promote being the “best” within the scientific enterprise, and within a context that encourages the responsible conduct of research, represents a challenge in research envi- ronments. Supervision The extent to which research behavior is monitored and quality control systems are operational will affect the level of adherence to ethical standards. Scientists need to see that policies about responsible research behavior are not just window dressing and that the organization has implemented practices that follow up stated policies. Consistency between words and deeds encourages the members of an organization to take policies seriously. Organizations vary widely in terms of their efforts to communicate codes of conduct to members, as well as to implement mechanisms to ensure compliance. When implementation is forceful and the policies and practices become deeply embedded in an organization’s culture, there is a greater likelihood that they will be effective in prevent- 

THE RESEARCH ENVIRONMENT AND ITS IMPACT 59 ing unethical behavior (McCabe and Treviño, 1993; Treviño, 1990; OGE, 2000). Communication Communication among members of a research organi- zation or research group that is frequent and open, versus infrequent and closed, should have a positive influence on integrity in research. A posi- tive ethical climate is supported by open discussions about ethical issues (Jendrek, 1992; OGE, 2000). Frequent and open communication enhances awareness of issues, encourages individuals to seek advice when faced with ethical dilemmas, and establishes the importance of resolving issues before they become something to be hidden. Socialization Mentoring relationships between research trainees and their advisers are important in the socialization of young scientists (Anderson et al., 2001; Swazey and Anderson, 1998). These relationships can be characterized by a variety of factors, including the level of trust, communication patterns, and the fulfillment of responsibilities as a men- tor or trainee. In addition to mentoring relationships, education in re- search and professional ethics is an aspect of socialization (Anderson, 1996; Anderson and Louis, 1994; Anderson et al., 1994; Louis et al., 1995; Swazey et al., 1993). Socialization practices can be formal or informal, but they are essential to helping individuals internalize the norms and values associated with the responsible conduct of research. Research that exam- ines the effect of more formalized methods of socialization—for example, education—reveals that interactive techniques (e.g., case discussion, role- playing, and hands-on practice sessions) are generally more effective in producing behavioral change than are activities with minimal participant interaction or discussion (e.g., lectures or presentations [Davis et al., 1999]). Furthermore, sequenced education has a greater impact than single educational sessions (Davis et al., 1999; OGE, 2000). These findings sub- stantiate the principles of adult education; these principles describe suc- cessful practices as being learner-centered, active rather than passive, rel- evant to the learner’s needs, engaging, and reinforcing (Brookfield, 1986; Cross, 1981; Knowles, 1970) (Chapter 5). Organizational Learning Organizations that learn from their operations and that continuously seek to improve their performance are better able to adapt to a changing environment (Anderson et al., 1994; Deming, 1986; Hackman and Wageman, 1995; Schön, 1983). All organizations change over time, but for some this can be an excruciating and painful process if it comes about through reaction to a crisis situation. For example, when a research subject dies or a researcher is accused of data fabrication, the 

60 INTEGRITY IN SCIENTIFIC RESEARCH organization should respond immediately. However, this response is fo- cused on crisis intervention rather than prevention. On the other hand, organizations that have mechanisms in place to continuously evaluate the efficiency and effectiveness of their programs and activities are more likely to build a preventive maintenance system (Fiol and Lyles, 1985; Schön, 1983). Furthermore, if the members of an organization have a voice in the design and implementation of such systems, then they are more likely to accept and be cooperative with the continual evaluative processes. Culture and Climate All of the enduring elements and features of an organization’s struc- ture and its more dynamic processes exist within the context of an organization’s culture and climate. In fact, an organization’s structure and processes help to create the culture and climate inasmuch as they are shaped by them (Ashforth, 1985). An organization’s culture consists of the set of shared norms, values, beliefs, and assumptions, along with the behavior and other artifacts (e.g., symbols, rituals, stories, and language) that express these orientations.. Culture and climate factors are character- istics of an organization that guide members’ thoughts and actions (Schneider, 1975). The ethical (or moral) climate is one component of an organization’s culture and is particularly relevant in the analysis of integrity in research (Victor and Cullen, 1988). This climate is defined as the prevailing moral beliefs (i.e., the prescribed behaviors, beliefs, and attitudes within the community and the sanctions expressed) that provide the context for con- duct. The stable, psychologically meaningful, and shared perceptions of the members of an organization are used as indicators of ethical climate, which may exist both at the organizational level and at the research group or team level (Schneider, 1975; Schneider and Reichers, 1983). An ethical climate that supports the responsible conduct of research is created when scientists perceive that adherence to ethical standards takes precedence and that sanctions for ethical violation are consistently applied. Research in this area has established that the factors within an organization that are most strongly related to ethical behavior are atten- tion to ethics by supervisors and organizational leadership, consistency between policies and practices, open discussions about ethics, and follow- up of reports of ethics concerns (OGE, 2000). These features of an organi- zation can help establish an ethical climate in which organizational mem- bers perceive that the responsible conduct of research is central to the organization’s practice and that it is not something to be worked around. It creates an environment in which a code of conduct is strongly imple- mented and deeply embedded in the community’s culture (Treviño, 1990). 

THE RESEARCH ENVIRONMENT AND ITS IMPACT 61 Outputs and Outcomes Outputs The outputs of research organizations are produced at all levels—the organizational level, the research group or team level, and the individual scientist level. The outputs are the products produced, the services deliv- ered, and the ideas developed and tested. The most obvious outputs are the number and quality of research projects completed, reports written, publications produced, patents filed, and students graduated. For the committee’s purposes, however, it is important to focus on the outputs of activities or programs related to integrity in research—for ex- ample, institutional review boards, conflict-of-interest review commit- tees, and programs that provide education in the responsible conduct of research. Outputs from these programs are generally measured in terms of the quantity and the quality of activities—for example, the number of workshops and seminars offered, the number of scientists who partici- pate, and the number of research proposals reviewed by IRBs and the dispositions of those proposals. Research organizations that design and implement high-quality activities related to integrity in research—and in a quantity that is sufficient to meet their needs—are more likely to achieve the outcomes that they seek (e.g., adherence to responsible research prac- tices). Although these activities will not be the sole factors that determine the responsible conduct of research, their implementation becomes a sym- bol for the members of an organization, serving as an indicator of the leadership’s commitment to the establishment of a culture and a climate that supports the responsible conduct of research. Outcomes The outcomes of organizational activities refer to the specific results that reflect the achievement of goals and objectives. As with organiza- tional outputs, outcomes can be associated with the organization as a whole, the research group, or the individual scientist. However, the committee’s primary interest is in the individual scientist’s level of integ- rity in research. As discussed in Chapter 2, the committee defines integ- rity in research as the individual scientist’s adherence to a number of normative practices for the responsible conduct of research. Adherence to these practices provides a set of behavioral indicators of an individual’s integrity in research. However, behavioral compliance is assumed to be associated with an understanding of the norms, rules, and practices of science. In addition, judgments about an individual’s integ- rity are based on the extent to which intellectual honesty, accuracy, fair- 

62 INTEGRITY IN SCIENTIFIC RESEARCH ness, and collegiality consistently characterize the dispositions and atti- tudes reflected in a researcher’s practice. Judgments about a person’s integrity are less about strict adherence to the rules of practice and are more about the disposition to be intellectually honest, accurate, and fair in the practice of science (i.e., in the willingness to admit and correct one’s errors and shortcomings). The committee resisted defining integrity in terms of (1) adherence to the normative practices listed in Chapter 2, (2) the knowledge and aware- ness of the practices of responsible research, and (3) the attitudes and orientation toward the practices of responsible research (i.e., the degree to which individuals agree with the practices, the level of importance that they attach to them, and the extent to which they are subject to conflicting sets of practices), as has been common in the social sciences.3 These three conceptually distinct categories of outcomes fail to capture the complex- ity of the process through which individuals interact with their environ- ment and make ethical decisions. One simply cannot assume that as scien- tists gain awareness of standards of practice, they will be positively oriented to them or will be more likely to adhere to the behavioral re- quirements. The committee recognizes that although researchers might be well intentioned, there is truth in what psychologists (Rest, 1983) have observed: that everyone is capable of missing a moral issue (moral blind- ness); developing elaborate and internally persuasive arguments to jus- tify questionable actions (defective reasoning); failing to prioritize a moral value over a personal one (lack of motivation or commitment); being ineffectual, devious, or careless (character or personality defects, often implied when someone is referred to as “a jerk”); or having ineffectual skills at problem solving or interpersonal communication (incompetence). For this reason, focusing on the processes that give rise to the respon- sible conduct of research are important individual-level outcomes of or- ganizational activities within the research environment. Components of the process of ethical decision making include ethical sensitivity, reason- 3A recent review of approaches to the study of morality (Bebeau et al., 1999) has chal- lenged the usefulness of the usual tripartite view that assumes that the elements to be studied and assessed are attitudes, knowledge, and behavior. When researchers have stud- ied the connections among these elements, they usually do not find significant connections and are left with the conclusion that attitudes do not have much to do with knowing and behavior is often devoid of feeling and thinking. A more profitable approach is to assume that many types of cognitions, many types of affects, and many kinds of observable behav- iors are involved in morality or integrity. All behavior is the result of cognitive-affective processes. Instead of studying cognitions, affects, and behaviors as separate elements, psy- chologists suggest that researchers study functional processes that must arise to produce moral behavior (Rest, 1983). 

THE RESEARCH ENVIRONMENT AND ITS IMPACT 63 ing, moral motivation and commitment, and character and competence (Bebeau, 2001). Educational programs that train scientists in the respon- sible conduct of research are often premised on the assumption that these essential capacities for ethical decision making are well developed by the time individuals begin their research education, and that one simply needs to teach the rules of the responsible conduct of research. Research on ethical development in the professions demonstrates that even mature professionals show considerable variability on performance assessments that measure ethical sensitivity, moral reasoning and judgment, profes- sional role orientation, and appropriate character and competence to implement action plans effectively. Therefore, if a research environment implements educational pro- grams to foster integrity in research, then these programs should promote sensitivity to issues that are likely to arise in the research setting by build- ing a capacity for reasoning carefully about conflicts inherent in propos- ing, conducting, and reporting research; by developing a sense of per- sonal identity that incorporates the norms and values of the research culture; and by building competence in problem solving and interper- sonal communication (see Chapter 5 for further discussion). External Environment The external environment of a research organization consists of both an external-task environment and a general environment (Figure 3-2). The external-task environment includes all the organizations and condi- tions that are directly related to an organization’s main operations and its technologies. The systems and subsystems of the external-task environ- ment are embedded within the larger sociocultural, political, and eco- nomic environment and have a more indirect impact on an organization. It is important to recognize that relationships also exist between and among all elements within the external environment. For example, gov- ernment policies and regulations can affect the areas and levels of fund- ing. Journal policies can be affected by decisions made within scientific associations, and these decisions can be driven by government regulation (or pending regulation). External-Task Environment A number of factors within the external-task environment have a significant impact on scientists’ responsible conduct of research. These factors include government regulation, funding for scientific work, job opportunities for trainees and researchers, journal policies and practices, and the policies and practices of scientific societies. 

64 General Sociocultural, Political, and Economic Environment Funding Government for regulation scientific work Research Organizations Journal policies and Human practices resources/ job market Policies and practices of scientific societies FIGURE 3-2 Environmental influences on integrity in research that are external to research organizations. The external-task environment includes all of the organizations and conditions that are directly related to an organization’s main operations and technologies. The double arrows depict the interrelatedness between the research organization and the various external influenc- es (unshaded circles) that are hypothesized to have an impact on integrity in research. The general environment has a more indirect impact on an organization. The systems and subsystems of the external-task environment are embedded within the larger, general sociocultural, political, and economic environment (shaded area). Although not specifically shown in this figure, it is important to recognize that relationships exist between and among the elements within the external environment. 

THE RESEARCH ENVIRONMENT AND ITS IMPACT 65 Government Regulation Governmental bodies, particularly at the fed- eral level, have been promulgating regulations concerning the conduct of research for many years. Most widely known and recognized are the regulations regarding the protection of human research subjects (45 C.F.R. § 46, 1999; 21 C.F.R. § 50 and 56, 1998) and the protection of animals in research (7 U.S.C. §§ 2131, 1966, et seq.). Furthermore, regulations have been promulgated regarding the evaluation of allegations and the report- ing of scientific misconduct (42 C.F.R. § 50, §§A, 1989; Federal Register, 2000) and the handling and disposal of hazardous chemicals in the labo- ratory (29 C.F.R. § 1910.1450, 1996), to name just two. As these govern- ment regulations come into force, they have direct impacts on a research organization and individual scientists. Specifically, organizations and in- dividuals must be in compliance with the regulations or face sanctions. Funding for Scientific Work Research organizations are directly af- fected by both the level and the source of funding that is available for scientific work (e.g., they are affected by the balances between govern- ment and corporate support and between industry and foundation sup- port). Most funding sources provide support for specific research propos- als rather than particular investigators. Although proposals are usually ranked on a relative scale, more typically they are funded in an all-or- none fashion. At the same time, funding needs always outpace funding opportunities. For instance, only one in three investigator-initiated grant proposals (see http://silk.nih.gov/public/[email protected]. dsncc) to the National Institutes of Health is successful. In this situation, even investigators who succeed in their research sometimes lose funding, a fate that threatens the very existence of their projects and often threatens their personal incomes. The task for research organizations is to develop structures that help their scientists deal with this competitive research situation while main- taining the responsible conduct of research. Similarly, when corporate or industry funds are involved, research organizations should require strat- egies for the management and disclosure of conflicts of interest to reduce problems related to publication rights, ownership of intellectual prop- erty, and research involving human subjects. Job Opportunities When the job market is tight and there is more com- petition for every research position, researchers will be pressured to achieve higher levels of productivity and recognition. This situation chal- lenges scientists to be the best while maintaining the highest levels of integrity in research. Similarly, research programs must compete for stu- dents and postdoctoral fellows, who, in turn, enhance a program’s ac- complishments and overall status. The ability of researchers to gain rec- 

66 INTEGRITY IN SCIENTIFIC RESEARCH ognition often is believed to be the best path to attracting high-quality trainees to a program. The organizational challenge is to help researchers develop competitive programs while maintaining a high level of commit- ment to integrity in research. Journal Policies and Practices Journal editors can be more or less rigor- ous in their implementation of the review process and the extent to which they insist on high levels of adherence to scientific standards. Further- more, journals may have specific policies in such areas as authorship practices, disclosure of conflicts of interest, duplicate publication, and reporting of research methodologies. The scientific community receives an important message about integrity in research when journal policies and practices regarding these practices are clear and are required as a condition of publication—and when the most prestigious journals adopt such practices. For example, members of the International Committee of Medical Journal Editors recently revised their submission policies related to industry-sponsored research. Authors are now required to sign a state- ment accepting full responsibility for the conduct of a clinical trial, and they must confirm that they had access to the original data and had full control over the decision to publish (Davidoff et al., 2001). Policies and Practices of Scientific Societies Scientific societies are in a position to influence the behaviors of their members in ways that could promote integrity in research4 (AAAS, 2000). The societies vary exten- sively, however, in their development of codes of conduct, their enforce- ment of such codes, and their socialization of members with regard to these standards of behavior. To aid in this process, the Association of American Medical Colleges has published a guide to help societies in the development of ethical codes (AAMC, 1997). Other associations develop standards for accreditation—for example, standards for science education programs, research laboratories, and programs for the protection of hu- man and animal research subjects. These accreditation standards gener- ally have specific statements regarding the responsible conduct of re- search and stipulate the structures within the organization that must be in place to ensure compliance with the standards. Scientists who are part of such accredited programs will be subject to the influences of these exter- nal controls. 4See Chapter 6 for further discussion of the role professional and scientific societies can play in fostering an environment that promotes integrity in research. 

THE RESEARCH ENVIRONMENT AND ITS IMPACT 67 General Environment The general environment has an indirect impact on an organization. This environment includes all of the conditions and institutions that have sustained or infrequent impacts on the organization and its functions (Harrison, 1994). Included are the state or conditions of major social insti- tutions (e.g., the economy, political system, educational system, science and technology system, and legal system) as well as the local, national, and international cultures within which an organization operates. The general public, and more specifically the effects of public trust in the research enterprise, are also important components of the general envi- ronment. As reflected in Figure 3-2, the organizations and conditions of the external-task environment (unshaded circles) are embedded within this larger environment (shaded area). An example of how the broader environment can affect the conduct of research is the recent national debate over embryonic stem cell re- search; this debate reflects a clash of values that affect the characterization of ethical or unethical research (NAS, 2001; National Bioethics Advisory Commission, 1999). In another instance, the new rules governing the pri- vacy of health records that are part of the Health Insurance Portability and Accountability Act are being challenged by scientists as too restric- tive in providing access to identifiable data for research (AAMC, 2001; Annas, 2002). Also, society places a high premium on human rights and the protection of vulnerable persons, values that have been translated into federal regulations for the protection of human research subjects (45 C.F.R. § 46, 1993, and 21 C.F.R. § 50 and 56, 1981). Other social institutions also have an indirect impact on research en- vironments. Educational systems produce scientists, and these systems affect not only their quantity but also their quality and how well they have been socialized into professional standards of conduct. The technol- ogy systems determine the availability of equipment and the methods used to carry out various types of research, factors that may raise ques- tions about the propriety of certain research endeavors. Ethical conflicts are often created when the development of new technologies requires an answer to the question of whether what can be done should be done. Finally, the legal system and the propensity in the United States to resort to litigation may bring about situations in which scientists are caught between the responsible conduct of research and subpoenas for confiden- tial data. These examples are by no means exhaustive, but they reflect the ways in which major social institutions and cultural values can affect research organizations and a scientist’s practice of research. 

68 INTEGRITY IN SCIENTIFIC RESEARCH SUMMARY The committee found no comprehensive body of research or writing that can guide the development of hypotheses regarding the relationships between the research environment and the responsible conduct of re- search. However, viewing the research environment as an open-systems model, which is often used in general organizational and administrative theory, makes it possible to hypothesize how various components affect integrity in research. Inputs of funds and other resources can influence behavior both positively and negatively. The organizational structure and processes that typify the mission and activities of an organization can either promote or detract from the responsible conduct of research. The culture and climate that are unique to an organization both promote and perpetuate certain behaviors. Finally, the external environment, over which individuals and, often, institutions have little control, can affect behavior and alter institutional integrity for better or for worse. REFERENCES AAAS (American Association for the Advancement of Science). 2000. The Role and Activities of Scientific Societies in Promoting Research Integrity. A report of a conference, April 10, 2000, Washington, DC. [Online]. Available: http://www.aaas.org/spp/dspp/sfrl/ projects/integrity.htm [Accessed January 7, 2002]. AAMC (Association of American Medical Colleges). 1997. Developing a Code of Ethics in Research: A Guide for Scientific Societies. Washington, DC: AAMC. AAMC. 2001. Letter to Secretary Thompson on Impact of Medical Privacy Rule on Research. [Online]. Available: http://www.aamc.org/advocacy/corres/research/thompson. htm [Accessed February 1, 2002]. Anderson J, Rungtusanatham M, Schroeder R, Devaraj S. 1995. A path analytic model of a theory of quality management underlying the Deming management method: Prelimi- nary empirical findings. Decision Sciences 26:637–658. Anderson MS. 1996. Misconduct and departmental context: Evidence from the Acadia Insti- tute’s Graduate Education Project. Journal of Information Ethics 5(1):15–33. Anderson MS, Louis KS. 1994. The graduate student experience and subscription to the norms of science. Research in Higher Education 35:273–299. Anderson MS, Louis KS, Earle J. 1994. Disciplinary and departmental effects on observa- tions of faculty and graduate student misconduct. Journal of Higher Education 65:331– 350. Anderson MS, Oju EC, Falkner TMR. 2001. Help from faculty: Findings from the Acadia Institute Graduate Education Study. Science and Engineering Ethics 7:487–503. Andrews KR. 1989. Ethics in practice. Harvard Business Review Sept-Oct:99–104. Annas GJ. 2002. Medical privacy and medical research—judging the new federal regula- tions. New England Journal of Medicine 346:216–220. Ashforth BE. 1985. Climate formation: Issues and extensions. Academy of Management Re- view 10:837–847. Bebeau MJ. 2001. Influencing the moral dimensions of professional practice: Implications for teaching and assessing for research integrity. In: Steneck NH, Scheetz MD, eds. [2000]. Investigating Research Integrity: Proceedings of the First ORI Research Conference on 

THE RESEARCH ENVIRONMENT AND ITS IMPACT 69 Research Integrity. Washington, DC: Office of Research Integrity, U.S. Department of Health and Human Services. Pp. 179-188. Bebeau MJ, Rest JR, Narvaez D. 1999. Beyond the promise: A perspective on research in moral education. Educational Researcher 28(4):18–26. Beer M. 1980. Organizational Change and Development—A Systems View. Santa Monica, CA: Goodyear. Brookfield SD. 1986. Understanding and Facilitating Adult Learning: A Comprehensive Analysis of Principles and Effective Practices. San Francisco, CA: Jossey-Bass. Cross KP. 1981. Adults as Learners: Increasing Participation and Facilitating Learning. San Fran- cisco, CA: Jossey-Bass. Daft R. 1992. Organizations: Theory and Design, 4th ed. St. Paul, MN: West Publishing. Davidoff F, DeAngelis CD, Drazen JM, Nicholls MG, Hoey J, Hojgaard L, Horton R, Kotzin S, Nylenna M, Overbeke AJPM, Sox HC, Van Der Weyden MB, Wilkes MS. 2001. Sponsorship, authorship and accountability. Canadian Medical Association Journal 165:786–788. Davis D, O’Brien MAT, Freemantle N, Wolf FM, Mazmanian P, Taylor-Vaisey A. 1999. Impact of formal continuing medical education: Do conferences, workshops, rounds, and other traditional continuing education activities change physician behavior or health care outcomes? Journal of American Medical Association 282:867–874. Deming WE. 1986. Out of Crisis. Cambridge, MA: Center for Advanced Engineering Study, Massachusetts Institute of Technology. Donabedian A. 1980. Explorations in Quality Assessment and Monitoring: The Definition of Quality and Approaches to Its Assessment. Vol. 1. Ann Arbor, MI: Health Administration Press. Federal Register. 2000. Public Health Service Standards for the Protection of Research. [Online]. Available: http://frwebgate4.access.gpo.gov/cgi-bin/waisgate.cgi?WAISdocID= 47426132664+0+2+0&WAISaction=retrieve [Accessed March 18, 2002]. Fiol DC, Lyles MA. 1985. Organizational learning. Academy of Management Review 10:803– 813. Freuberg D. 1986. The Corporate Conscience: Money, Power, and Responsible Business. New York, NY: American Management Association. Hackman JR, Wageman R. 1995. Total quality management: Empirical, conceptual, and practical issues. Administrative Science Quarterly 40:309–342. Hamner WC, Organ DW. 1978. Organizational Behavior: An Applied Psychological Approach. Dallas, TX: Business Publications. Harrison MI. 1994. Diagnosing Organizations: Methods, Models, and Processes, 2nd ed. Thou- sand Oaks, CA: Sage. Hegarty WH, Sims HP. 1978. Some determinants of unethical decision behavior: An experi- ment. Journal of Applied Psychology 63:451–457. Hegarty WH, Sims HP. 1979. Organizational philosophy, policies, and objectives related to unethical decision behavior: A laboratory experiment. Journal of Applied Psychology 64:331–338. Heitman E. 2000. Ethical values in the education of biomedical researchers. Hastings Center Report 30:S40–S44. Jendrek MP. 1992. Students’ reactions to academic dishonesty. Journal of College Student Development 33:260–273. Katz D, Kahn R. 1978. The Social Psychology of Organizations, 2nd ed. New York, NY: Wiley. Katz R. 1980. Time and work: Toward an integrative perspective. In: Staw BM, Cummings LL, eds. Research in Organizational Behavior, Vol. 2. Greenwich, CT: JAI Press. Pp. 81– 127. 

70 INTEGRITY IN SCIENTIFIC RESEARCH Knowles MS. 1970. The Modern Practice of Adult Education: Andragagy Versus Pedagogy. New York, NY: New York Association Press. Kohlberg L. 1984. The Psychology of Moral Development: The Nature and Validity of Moral Stages. San Francisco: Harper & Row. Essays on Moral Development Vol. 2. Kurland N. 1996. Trust, accountability, and sales agents’ dueling loyalties. Business Ethics Quarterly 6:289–310. Louis KS, Anderson MS, Rosenberg L. 1995. Academic misconduct and values: The depart- ment’s influence. The Review of Higher Education 18:393–422. McCabe DL. 2000. New research on academic integrity: the success of “modified” honor codes. Synfax Weekly Report [Online]. Available: http://www.collegepubs.com/ref/ SFX000515.shtml [Accessed July 25, 2001]. McCabe DL, Pavela GM. 1998. The effect of institutional policies and procedures on aca- demic integrity. In: Burnett DD, Rudolph L, Clifford KO, eds. Academic Integrity Mat- ters. Washington, DC: National Association of Student Personnel Administrators, Inc. Pp. 93–108. McCabe DL, Treviño LK. 1993. Academic dishonesty: Honor codes and other contextual influences. Journal of Higher Education 64:522–538. McCabe DL, Treviño LK, Butterfield KD. 1996. The influence of collegiate and corporate codes of conduct on ethics-related behavior in the workplace. Business Ethics Quarterly 6:461–476. NAS (National Academy of Sciences). 2001. Biological and Biomedical Applications of Stem Cell Research. Washington, DC: National Academy Press. National Bioethics Advisory Commission. 1999. Ethical Issues in Human Stem Cell Research, Vol. I to III. Washington, DC: U.S. Government Printing Office. NIST (National Institute of Standards and Technology). 1999. Malcolm Baldrige National Qual- ity Award 1998 Education Criteria for Performance Excellence. Washington, DC: U.S. De- partment of Commerce. OGE (U.S. Office of Government Ethics). 2000. Executive Branch Employee Ethics: Survey 2000. Washington, DC: OGE. Perry A, Kane K, Bernesser K, Spicker P. 1990. Type A behavior, competitive achievement- striving, and cheating among college students. Psychological Reports 66:459–465. Peters TJ. 1978. Symbols, patterns, and settings: An optimistic case for getting things done. Organizational Dynamics 7(2):3–23. Peters TJ, Waterman RH, Jr. 1982. In Search of Excellence: Lessons from America’s Best-Run Companies. New York, NY: Harper & Row. Pfeffer J. 1981. Management as symbolic action: The creation and maintenance of organiza- tional paradigms. In: Cummings LL, Staw BM eds. Research in Organizational Behavior, Vol. 3. Greenwich, CT: JAI Press. Pp. 1–52. Posner B, Schmidt W. 1982. What kind of people enter the public and private sectors? An undated comparison of perceptions, stereotypes, and values. Human Resource Manage- ment 21:35–43. Posner B, Schmidt W. 1984. Values and the American manager: An update. California Man- agement Review 26(3):202–216. Rest, J. 1983. Morality. In: Mussen PH (series ed.) and Flavell J, Markman E (vol. eds.), Handbook of Child Psychology, Vol. 3, Cognitive Development, 4th ed. New York, NY: Wiley. Pp. 556–629. Rest J, Narvaez D, Bebeau MJ, Thoma SJ. 1999. Postconventional Moral Thinking: A Neo- Kohlbergian Approach. Hillsdale, NJ: L. Erlbaum Associates. Saraph JV, Benson PG, Schroeder RG. 1989. An instrument for measuring the critical factors of quality management. Decision Sciences 20:810–829. Schein EH. 1968. Organizational socialization and the profession of management. Industrial Management Review 9:1-15. 

THE RESEARCH ENVIRONMENT AND ITS IMPACT 71 Schneider B. 1975. Organizational climates: An essay. Personnel Psychology 28:447–479. Schneider B, Reichers AE. 1983. On the etiology of climates. Personnel Psychology 36:19–39. Schön DA. 1983. Organizational learning. In: Morgan G, ed. Beyond Method: Strategies for Social Research. Newbury Park, CA: Sage. Pp. 114–128. Siehl C, Martin J. 1984. The role of symbolic management: How can managers effectively transmit organizational culture? In: Hunt JG, Hosking DM, Schriesheim CA, Stewart R, eds. Leaders and Managers: International Perspectives on Managerial Behavior and Leader- ship. Elmsford, NY: Pergamon. Pp. 227–239. Swazey JP, Anderson MS. 1998. Mentors, advisors, and role models in graduate and profes- sional education. In: Rubin ER, ed. Mission Management: A New Synthesis, Vol. 2. Wash- ington, DC: Association of Academic Health Centers. Pp. 165–185. Swazey JP, Anderson MS, Louis KS. 1993. Ethical problems in academic research. American Scientist 81:542–553. Treviño LK. 1990. A cultural perspective on changing and developing organizational ethics. Research in Organizational Change and Development 4:195–230. Treviño LK, Butterfield KD, McCabe DL. 1996. The ethical context in organizations: Influ- ences on employee attitudes and behaviors. Business Ethics Quarterly 8(3):447–476. Van Maanen J, Schein EH. 1979. Toward a theory of organizational socialization. In: Staw BM, ed. Research in Organizational Behavior, Vol. 1. Greenwich, CT: JAI Press. Pp. 209– 264. Victor B, Cullen JB. 1988. The organizational bases of ethical work climates. Administrative Science Quarterly 33:101–125. Walker OC, Churchill GA, Ford NM. 1979. Where do we go from here? Selected conceptual and empirical issues concerning the motivation and performance of the industrial sales force. In: Albuam G, Churchill GA, eds. Critical Issues in Sales Management State of the Art and Future Research Needs. Eugene, OR: University of Oregon Press. Pp. 10–75. Wanous JP. 1980. Organizational Entry: Recruitment, Selection, and Socialization of Newcomers. Reading, MA: Addison-Wesley. Wimbush JC, Shepard JM. 1994. Toward an understanding of ethical climate: Its relation- ship to ethical behavior and supervisory influence. Journal of Business Ethics 13:637– 647. 

"Most people say that it is the intellect which makes a great scientist. They are wrong: it is character."—Albert Einstein

Integrity in Scientific Research attempts to define and describe those elements that encourage individuals involved with scientific research to act with integrity.

Recognizing the inconsistency of human behavior, it stresses the important role that research institutions play in providing an integrity—rich environment, citing the need for institutions to provide staff with training and education, policies and procedures, and tools and support systems. It identifies practices that characterize integrity in such areas as peer review and research on human subjects and weighs the strengths and limitations of self—evaluation efforts by these institutions. In addition, it details an approach to promoting integrity during the education of researchers, including how to develop an effective curriculum. Providing a framework for research and educational institutions, this important book will be essential for anyone concerned about ethics in the scientific community.

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Chapter 3 Research Environment

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Chapter 3 The Research Process

In Chapter 1, we saw that scientific research is the process of acquiring scientific knowledge using the scientific method. But how is such research conducted? This chapter delves into the process of scientific research, and the assumptions and outcomes of the research process.

Paradigms of Social Research

Our design and conduct of research is shaped by our mental models or frames of references that we use to organize our reasoning and observations. These mental models or frames (belief systems) are called paradigms. The word “paradigm” was popularized by

Thomas Kuhn (1962) in his book The Structure of Scientific Revolutions, where he examined the history of the natural sciences to identify patterns of activities that shape the progress of science. Similar ideas are applicable to social sciences as well, where a social reality can be viewed by different people in different ways, which may constrain their thinking and reasoning about the observed phenomenon. For instance, conservatives and liberals tend to have very different perceptions of the role of government in people’s lives, and hence, have different opinions on how to solve social problems. Conservatives may believe that lowering taxes is the best way to stimulate a stagnant economy because it increases people’s disposable income and spending, which in turn expands business output and employment. In contrast, liberals may believe that governments should invest more directly in job creation programs such as public works and infrastructure projects, which will increase employment and people’s ability to consume and drive the economy. Likewise, Western societies place greater emphasis on individual rights, such as one’s right to privacy, right of free speech, and right to bear arms. In contrast, Asian societies tend to balance the rights of individuals against the rights of families, organizations, and the government, and therefore tend to be more communal and less individualistic in their policies. Such differences in perspective often lead Westerners to criticize Asian governments for being autocratic, while Asians criticize Western societies for being greedy, having high crime rates, and creating a “cult of the individual.” Our personal paradigms are like “colored glasses” that govern how we view the world and how we structure our thoughts about what we see in the world.

Paradigms are often hard to recognize, because they are implicit, assumed, and taken for granted. However, recognizing these paradigms is key to making sense of and reconciling differences in people’ perceptions of the same social phenomenon. For instance, why do liberals believe that the best way to improve secondary education is to hire more teachers, but conservatives believe that privatizing education (using such means as school vouchers) are more effective in achieving the same goal? Because conservatives place more faith in competitive markets (i.e., in free competition between schools competing for education dollars), while liberals believe more in labor (i.e., in having more teachers and schools). Likewise, in social science research, if one were to understand why a certain technology was successfully implemented in one organization but failed miserably in another, a researcher looking at the world through a “rational lens” will look for rational explanations of the problem such as inadequate technology or poor fit between technology and the task context where it is being utilized, while another research looking at the same problem through a “social lens” may seek out social deficiencies such as inadequate user training or lack of management support, while those seeing it through a “political lens” will look for instances of organizational politics that may subvert the technology implementation process. Hence, subconscious paradigms often constrain the concepts that researchers attempt to measure, their observations, and their subsequent interpretations of a phenomenon. However, given the complex nature of social phenomenon, it is possible that all of the above paradigms are partially correct, and that a fuller understanding of the problem may require an understanding and application of multiple paradigms.

Two popular paradigms today among social science researchers are positivism and post-positivism. Positivism , based on the works of French philosopher Auguste Comte (1798-1857), was the dominant scientific paradigm until the mid-20 th century. It holds that science or knowledge creation should be restricted to what can be observed and measured. Positivism tends to rely exclusively on theories that can be directly tested. Though positivism was originally an attempt to separate scientific inquiry from religion (where the precepts could not be objectively observed), positivism led to empiricism or a blind faith in observed data and a rejection of any attempt to extend or reason beyond observable facts. Since human thoughts and emotions could not be directly measured, there were not considered to be legitimate topics for scientific research. Frustrations with the strictly empirical nature of positivist philosophy led to the development of post-positivism (or postmodernism) during the mid-late 20 th century. Post-positivism argues that one can make reasonable inferences about a phenomenon by combining empirical observations with logical reasoning. Post-positivists view science as not certain but probabilistic (i.e., based on many contingencies), and often seek to explore these contingencies to understand social reality better. The post -positivist camp has further fragmented into subjectivists , who view the world as a subjective construction of our subjective minds rather than as an objective reality, and critical realists , who believe that there is an external reality that is independent of a person’s thinking but we can never know such reality with any degree of certainty.

Burrell and Morgan (1979), in their seminal book Sociological Paradigms and Organizational Analysis, suggested that the way social science researchers view and study social phenomena is shaped by two fundamental sets of philosophical assumptions: ontology and epistemology. Ontology refers to our assumptions about how we see the world, e.g., does the world consist mostly of social order or constant change. Epistemology refers to our assumptions about the best way to study the world, e.g., should we use an objective or subjective approach to study social reality. Using these two sets of assumptions, we can categorize social science research as belonging to one of four categories (see Figure 3.1).

If researchers view the world as consisting mostly of social order (ontology) and hence seek to study patterns of ordered events or behaviors, and believe that the best way to study such a world is using objective approach (epistemology) that is independent of the person conducting the observation or interpretation, such as by using standardized data collection tools like surveys, then they are adopting a paradigm of functionalism . However, if they believe that the best way to study social order is though the subjective interpretation of participants involved, such as by interviewing different participants and reconciling differences among their responses using their own subjective perspectives, then they are employing an interpretivism paradigm. If researchers believe that the world consists of radical change and seek to understand or enact change using an objectivist approach, then they are employing a radical structuralism paradigm. If they wish to understand social change using the subjective perspectives of the participants involved, then they are following a radical humanism paradigm.

Figure 3.1. Four paradigms of social science research (Source: Burrell and Morgan, 1979)

Figure 3.2. Functionalistic research process

The first phase of research is exploration . This phase includes exploring and selecting research questions for further investigation, examining the published literature in the area of inquiry to understand the current state of knowledge in that area, and identifying theories that may help answer the research questions of interest.

The first step in the exploration phase is identifying one or more research questions dealing with a specific behavior, event, or phenomena of interest. Research questions are specific questions about a behavior, event, or phenomena of interest that you wish to seek answers for in your research. Examples include what factors motivate consumers to purchase goods and services online without knowing the vendors of these goods or services, how can we make high school students more creative, and why do some people commit terrorist acts. Research questions can delve into issues of what, why, how, when, and so forth. More interesting research questions are those that appeal to a broader population (e.g., “how can firms innovate” is a more interesting research question than “how can Chinese firms innovate in the service-sector”), address real and complex problems (in contrast to hypothetical or “toy” problems), and where the answers are not obvious. Narrowly focused research questions (often with a binary yes/no answer) tend to be less useful and less interesting and less suited to capturing the subtle nuances of social phenomena. Uninteresting research questions generally lead to uninteresting and unpublishable research findings.

The next step is to conduct a literature review of the domain of interest. The purpose of a literature review is three-fold: (1) to survey the current state of knowledge in the area of inquiry, (2) to identify key authors, articles, theories, and findings in that area, and (3) to identify gaps in knowledge in that research area. Literature review is commonly done today using computerized keyword searches in online databases. Keywords can be combined using “and” and “or” operations to narrow down or expand the search results. Once a shortlist of relevant articles is generated from the keyword search, the researcher must then manually browse through each article, or at least its abstract section, to determine the suitability of that article for a detailed review. Literature reviews should be reasonably complete, and not restricted to a few journals, a few years, or a specific methodology. Reviewed articles may be summarized in the form of tables, and can be further structured using organizing frameworks such as a concept matrix. A well-conducted literature review should indicate whether the initial research questions have already been addressed in the literature (which would obviate the need to study them again), whether there are newer or more interesting research questions available, and whether the original research questions should be modified or changed in light of findings of the literature review. The review can also provide some intuitions or potential answers to the questions of interest and/or help identify theories that have previously been used to address similar questions.

Since functionalist (deductive) research involves theory-testing, the third step is to identify one or more theories can help address the desired research questions. While the literature review may uncover a wide range of concepts or constructs potentially related to the phenomenon of interest, a theory will help identify which of these constructs is logically relevant to the target phenomenon and how. Forgoing theories may result in measuring a wide range of less relevant, marginally relevant, or irrelevant constructs, while also minimizing the chances of obtaining results that are meaningful and not by pure chance. In functionalist research, theories can be used as the logical basis for postulating hypotheses for empirical testing. Obviously, not all theories are well-suited for studying all social phenomena. Theories must be carefully selected based on their fit with the target problem and the extent to which their assumptions are consistent with that of the target problem. We will examine theories and the process of theorizing in detail in the next chapter.

The next phase in the research process is research design . This process is concerned with creating a blueprint of the activities to take in order to satisfactorily answer the research questions identified in the exploration phase. This includes selecting a research method, operationalizing constructs of interest, and devising an appropriate sampling strategy.

Operationalization is the process of designing precise measures for abstract theoretical constructs. This is a major problem in social science research, given that many of the constructs, such as prejudice, alienation, and liberalism are hard to define, let alone measure accurately. Operationalization starts with specifying an “operational definition” (or “conceptualization”) of the constructs of interest. Next, the researcher can search the literature to see if there are existing prevalidated measures matching their operational definition that can be used directly or modified to measure their constructs of interest. If such measures are not available or if existing measures are poor or reflect a different conceptualization than that intended by the researcher, new instruments may have to be designed for measuring those constructs. This means specifying exactly how exactly the desired construct will be measured (e.g., how many items, what items, and so forth). This can easily be a long and laborious process, with multiple rounds of pretests and modifications before the newly designed instrument can be accepted as “scientifically valid.” We will discuss operationalization of constructs in a future chapter on measurement.

Simultaneously with operationalization, the researcher must also decide what research method they wish to employ for collecting data to address their research questions of interest. Such methods may include quantitative methods such as experiments or survey research or qualitative methods such as case research or action research, or possibly a combination of both. If an experiment is desired, then what is the experimental design? If survey, do you plan a mail survey, telephone survey, web survey, or a combination? For complex, uncertain, and multi-faceted social phenomena, multi-method approaches may be more suitable, which may help leverage the unique strengths of each research method and generate insights that may not be obtained using a single method.

Researchers must also carefully choose the target population from which they wish to collect data, and a sampling strategy to select a sample from that population. For instance, should they survey individuals or firms or workgroups within firms? What types of individuals or firms they wish to target? Sampling strategy is closely related to the unit of analysis in a research problem. While selecting a sample, reasonable care should be taken to avoid a biased sample (e.g., sample based on convenience) that may generate biased observations. Sampling is covered in depth in a later chapter.

At this stage, it is often a good idea to write a research proposal detailing all of the decisions made in the preceding stages of the research process and the rationale behind each decision. This multi-part proposal should address what research questions you wish to study and why, the prior state of knowledge in this area, theories you wish to employ along with hypotheses to be tested, how to measure constructs, what research method to be employed and why, and desired sampling strategy. Funding agencies typically require such a proposal in order to select the best proposals for funding. Even if funding is not sought for a research project, a proposal may serve as a useful vehicle for seeking feedback from other researchers and identifying potential problems with the research project (e.g., whether some important constructs were missing from the study) before starting data collection. This initial feedback is invaluable because it is often too late to correct critical problems after data is collected in a research study.

Having decided who to study (subjects), what to measure (concepts), and how to collect data (research method), the researcher is now ready to proceed to the research execution phase. This includes pilot testing the measurement instruments, data collection, and data analysis.

Pilot testing is an often overlooked but extremely important part of the research process. It helps detect potential problems in your research design and/or instrumentation (e.g., whether the questions asked is intelligible to the targeted sample), and to ensure that the measurement instruments used in the study are reliable and valid measures of the constructs of interest. The pilot sample is usually a small subset of the target population. After a successful pilot testing, the researcher may then proceed with data collection using the sampled population. The data collected may be quantitative or qualitative, depending on the research method employed.

Following data collection, the data is analyzed and interpreted for the purpose of drawing conclusions regarding the research questions of interest. Depending on the type of data collected (quantitative or qualitative), data analysis may be quantitative (e.g., employ statistical techniques such as regression or structural equation modeling) or qualitative (e.g., coding or content analysis).

The final phase of research involves preparing the final research report documenting the entire research process and its findings in the form of a research paper, dissertation, or monograph. This report should outline in detail all the choices made during the research process (e.g., theory used, constructs selected, measures used, research methods, sampling, etc.) and why, as well as the outcomes of each phase of the research process. The research process must be described in sufficient detail so as to allow other researchers to replicate your study, test the findings, or assess whether the inferences derived are scientifically acceptable. Of course, having a ready research proposal will greatly simplify and quicken the process of writing the finished report. Note that research is of no value unless the research process and outcomes are documented for future generations; such documentation is essential for the incremental progress of science.

Common Mistakes in Research

The research process is fraught with problems and pitfalls, and novice researchers often find, after investing substantial amounts of time and effort into a research project, that their research questions were not sufficiently answered, or that the findings were not interesting enough, or that the research was not of “acceptable” scientific quality. Such problems typically result in research papers being rejected by journals. Some of the more frequent mistakes are described below.

Insufficiently motivated research questions. Often times, we choose our “pet” problems that are interesting to us but not to the scientific community at large, i.e., it does not generate new knowledge or insight about the phenomenon being investigated. Because the research process involves a significant investment of time and effort on the researcher’s part, the researcher must be certain (and be able to convince others) that the research questions they seek to answer in fact deal with real problems (and not hypothetical problems) that affect a substantial portion of a population and has not been adequately addressed in prior research.

Pursuing research fads. Another common mistake is pursuing “popular” topics with limited shelf life. A typical example is studying technologies or practices that are popular today. Because research takes several years to complete and publish, it is possible that popular interest in these fads may die down by the time the research is completed and submitted for publication. A better strategy may be to study “timeless” topics that have always persisted through the years.

Unresearchable problems. Some research problems may not be answered adequately based on observed evidence alone, or using currently accepted methods and procedures. Such problems are best avoided. However, some unresearchable, ambiguously defined problems may be modified or fine tuned into well-defined and useful researchable problems.

Favored research methods. Many researchers have a tendency to recast a research problem so that it is amenable to their favorite research method (e.g., survey research). This is an unfortunate trend. Research methods should be chosen to best fit a research problem, and not the other way around.

Blind data mining. Some researchers have the tendency to collect data first (using instruments that are already available), and then figure out what to do with it. Note that data collection is only one step in a long and elaborate process of planning, designing, and executing research. In fact, a series of other activities are needed in a research process prior to data collection. If researchers jump into data collection without such elaborate planning, the data collected will likely be irrelevant, imperfect, or useless, and their data collection efforts may be entirely wasted. An abundance of data cannot make up for deficits in research planning and design, and particularly, for the lack of interesting research questions.

• Social Science Research: Principles, Methods, and Practices. Authored by : Anol Bhattacherjee. Provided by : University of South Florida. Located at : http://scholarcommons.usf.edu/oa_textbooks/3/ . License : CC BY-NC-SA: Attribution-NonCommercial-ShareAlike

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National Academies of Sciences, Engineering, and Medicine; Policy and Global Affairs; Committee on Science, Engineering, Medicine, and Public Policy; Committee on Responsible Science. Fostering Integrity in Research. Washington (DC): National Academies Press (US); 2017 Apr 11.

Fostering Integrity in Research.

• Hardcopy Version at National Academies Press

2 Foundations of Integrity in Research: Core Values and Guiding Norms

Problems of scientific freedom and responsibility are not new; one need only consider, as examples, the passionate controversies that were stirred by the work of Galileo and Darwin. In our time, however, such problems have changed in character, and have become far more numerous, more urgent and more complex. Science and its applications have become entwined with the whole fabric of our lives and thoughts. . . . Scientific freedom, like academic freedom, is an acquired right, generally accepted by society as necessary for the advancement of knowledge from which society may benefit. Scientists possess no rights beyond those of other citizens except those necessary to fulfill the responsibility arising from their special knowledge, and from the insight arising from that knowledge. — John Edsall (1975)

Synopsis: The integrity of research is based on adherence to core values—objectivity, honesty, openness, fairness, accountability, and stewardship. These core values help to ensure that the research enterprise advances knowledge. Integrity in science means planning, proposing, performing, reporting, and reviewing research in accordance with these values. Participants in the research enterprise stray from the norms and appropriate practices of science when they commit research misconduct or other misconduct or engage in detrimental research practices.

• TRANSMITTING VALUES AND NORMS IN RESEARCH

The core values and guiding norms of science have been studied and written about extensively, with the work of Robert Merton providing a foundation for subsequent work on the sociology of science ( Merton, 1973 ). Merton posited a set of norms that govern good science: (1) Communalism (common ownership of scientific knowledge), (2) Universalism (all scientists can contribute to the advance of knowledge), (3) Disinterestedness (scientists should work for the good of the scientific enterprise as opposed to personal gain), and (4) Organized Skepticism (results should be examined critically before they are accepted). Research on scientists and scientific organizations has also led to a better understanding of counternorms that appear to conflict with the dominant Mertonian norms but that are recognized as playing an inherent part in the actual practice of science, such as the personal commitment that a scientist may have to a particular hypothesis or theory ( Mitroff, 1974 ).

More recent work on the effectiveness of responsible conduct of research education, covered in more detail in Chapter 9 , explores evidence that at least some scientists may not understand and reflect upon the ethical dimensions of their work ( McCormick et al., 2012 ). Several causes are identified, including a lack of awareness on the part of researchers of the ethical issues that can arise, confidence that they can identify and address these issues without any special training or help, or apprehension that a focus on ethical issues might hinder their progress. An additional challenge arises from the apparent gap “between the normative ideals of science and science's institutional reward system” ( Devereaux, 2014 ). Chapter 6 covers this issue in more detail. Here, it is important to note that identifying and understanding the values and norms of science do not automatically mean that they will be followed in practice. The context in which values and norms are communicated and transmitted in the professional development of scientists is critically important.

Scientists are privileged to have careers in which they explore the frontiers of knowledge. They have greater autonomy than do many other professionals and are usually respected by other members of society. They often are able to choose the questions they want to pursue and the methods used to derive answers. They have rich networks of social relationships that, for the most part, reinforce and further their work. Whether actively involved in research or employed in some other capacity within the research enterprise, scientists are able to engage in an activity about which they are passionate: learning more about the world and how it functions.

In the United States, scientific research in academia emerged during the late 19th century as an “informal, intimate, and paternalistic endeavor” ( NAS-NAE-IOM, 1992 ). Multipurpose universities emphasized teaching, and research was more of an avocation than a profession. Even today, being a scientist and engaging in research does not necessarily entail a career with characteristics traditionally associated with professions such as law, medicine, architecture, some subfields of engineering, and accounting. For example, working as a researcher does not involve state certification of the practitioner's expertise as a requirement to practice, nor does it generally involve direct relationships with fee-paying clients. Many professions also maintain an explicit expectation that practitioners will adhere to a distinctive ethical code ( Wickenden, 1949 ). In contrast, scientists do not have a formal, overarching code of ethics and professional conduct.

However, the nature of professional practice even in the traditional professions continues to evolve ( Evetts, 2013 ). Some scholars assert that the concept of professional work should include all occupations characterized by “expert knowledge, autonomy, a normative orientation grounded in community, and high status, income, and other rewards” ( Gorman and Sandefur, 2011 ). Scientific research certainly shares these characteristics. In this respect, efforts to formalize responsible conduct of research training in the education of researchers often have assumed that this training should be part of the professional development of researchers ( IOM-NRC, 2002 ; NAS-NAE-IOM, 1992 ). However, the training of researchers (and research itself) has retained some “informal, intimate, and paternalistic” features. Attempts to formalize professional development training sometimes have generated resistance in favor of essentially an apprenticeship model with informal, ad hoc approaches to how graduate students and postdoctoral fellows learn how to become professional scientists.

One challenge facing the research enterprise is that informal, ad hoc approaches to scientific professionalism do not ensure that the core values and guiding norms of science are adequately inculcated and sustained. This has become increasingly clear as the changes in the research environment described in Chapter 3 have emerged and taken hold. Indeed, the apparent inadequacy of these older forms of training to the task of socializing and training individuals into responsible research practices is a recurring theme of this report.

Individual scientists work within a much broader system that profoundly influences the integrity of research results. This system, described briefly in Chapter 1 , is characterized by a massive, interconnected web of relationships among researchers, employing institutions, public and private funders, and journals and professional societies. This web comprises unidirectional and bidirectional obligations and responsibilities between the parts of the system. The system is driven by public and private investments and results in various outcomes or products, including research results, various uses of those results, and trained students. However, the system itself has a dynamic that shapes the actions of everyone involved and produces results that reflect the functioning of the system. Because of the large number of relationships between the many players in the web of responsibility, features of one set of relationships may affect other parts of the web. These interdependencies complicate the task of devising interventions and structures that support and encourage the responsible conduct of research.

• THE CORE VALUES OF RESEARCH

The integrity of research is based on the foundational core values of science. The research system could not operate without these shared values that shape the behaviors of all who are involved with the system. Out of these values arise the web of responsibilities that make the system cohere and make scientific knowledge reliable. Many previous guides to responsible conduct in research have identified and described these values ( CCA, 2010 ; ESF-ALLEA, 2011 ; IAC-IAP, 2012 ; ICB, 2010 ; IOM-NRC, 2002 ). This report emphasizes six values that are most influential in shaping the norms that constitute research practices and relationships and the integrity of science:

Objectivity

Accountability, stewardship.

This chapter examines each of these six values in turn to consider how they shape, and are realized in, research practices.

The first of the six values discussed in this report—objectivity—describes the attitude of impartiality with which researchers should strive to approach their work. The next four values—honesty, openness, accountability, and fairness—describe relationships among those involved in the research enterprise. The final value—stewardship—involves the relationship between members of the research enterprise, the enterprise as a whole, and the broader society within which the enterprise is situated. Although we discuss stewardship last, it is an essential value that perpetuates the other values.

The hallmark of scientific thinking that differentiates it from other modes of human inquiry and expression such as literature and art is its dedication to rational and empirical inquiry. In this context, objectivity is central to the scientific worldview. Karl Popper (1999) viewed scientific objectivity as consisting of the freedom and responsibility of the researcher to (1) pose refutable hypotheses, (2) test the hypotheses with the relevant evidence, and (3) state the results clearly and unambiguously to any interested person. The goal is reproducibility, which is essential to advancing knowledge through experimental science. If these steps are followed diligently, Popper suggested, any reasonable second researcher should be able to follow the same steps to replicate the work.

Objectivity means that certain kinds of motivations should not influence a researcher's action, even though others will. For example, if a researcher in an experimental field believes in a particular hypothesis or explanation of a phenomenon, he or she is expected to design experiments that will test the hypothesis. The experiment should be designed in a way that allows the possibility for the hypothesis to be disconfirmed. Scientific objectivity is intended to ensure that scientists' personal beliefs and qualities—motivations, position, material interests, field of specialty, prominence, or other factors—do not introduce biases into their work.

As will be explored in later chapters, in practice it is not that simple. Human judgment and decisions are prone to a variety of cognitive biases and systematic errors in reasoning. Even the best scientific intentions are not always sufficient to ensure scientific objectivity. Scientific objectivity can be compromised accidentally or without recognition by individuals. In addition, broader biases of the reigning scientific paradigm influence the theory and practice of science ( Kuhn, 1962 ). A primary purpose of scientific replication is to minimize the extent to which experimental findings are distorted by biases and errors. Researchers have a responsibility to design experiments in ways that any other person with different motivations, interests, and knowledge could trust the results. Modern problems related to reproducibility are explored later in the report.

In addition, objectivity does not imply or require that researchers can or should be completely neutral or disinterested in pursuing their work. The research enterprise does not function properly without the organized efforts of researchers to convince their scientific audiences. Sometimes researchers are proven correct when they persist in trying to prove theories in the face of evidence that appears to contradict them.

It is important to note, in addition, Popper's suggestion that scientific objectivity consists of not only responsibility but freedom . The scientist must be free from pressures and influences that can bias research results. Objectivity can be compromised when institutional expectations, laboratory culture, the regulatory environment, or funding needs put pressure on the scientist to produce positive results or to produce them under time pressure. Scientists and researchers operate in social contexts, and the incentives and pressures of those contexts can have a profound effect on the exercise of scientific methodology and a researcher's commitment to scientific objectivity.

Scientific objectivity also must coexist with other human motivations that challenge it. As an example of such a challenge, a researcher might become biased in desiring definitive results evaluating the validity of high-profile theories or hypotheses that their experiments were designed to support or refute. Both personal desire to obtain a definitive answer and institutional pressures to produce “significant” conclusions can provide strong motivation to find definitive results in experimental situations. Dedication to scientific objectivity in those settings represents the best guard against scientists finding what they desire instead of what exists. Institutional support of objectivity at every level—from mentors, to research supervisors, to administrators, and to funders—is crucial in counterbalancing the very human tendency to desire definitive outcomes of research.

A researcher's freedom to advance knowledge is tied to his or her responsibility to be honest . Science as an enterprise producing reliable knowledge is based on the assumption of honesty. Science is predicated on agreed-upon systematic procedures for determining the empirical or theoretical basis of a proposition. Dishonest science violates that agreement and therefore violates a defining characteristic of science.

Honesty is the principal value that underlies all of the other relationship values. For example, without an honest foundation, realizing the values of openness, accountability, and fairness would be impossible.

Scientific institutions and stakeholders start with the assumption of honesty. Peer reviewers, granting agencies, journal editors, commercial research and development managers, policy makers, and other players in the scientific enterprise all start with an assumption of the trustworthiness of the reporting scientist and research team. Dishonesty undermines not only the results of the specific research but also the entire scientific enterprise itself, because it threatens the trustworthiness of the scientific endeavor.

Being honest is not always straightforward. It may not be easy to decide what to do with outlier data, for example, or when one suspects fraud in published research. A single outlier data point may be legitimately interpreted as a malfunctioning instrument or a contaminated sample. However, true scientific integrity requires the disclosure of the exclusion of a data point and the effect of that exclusion unless the contamination or malfunction is documented, not merely conjectured. There are accepted statistical methods and standards for dealing with outlier data, although questions are being raised about how often these are followed in certain fields ( Thiese et al., 2015 ).

Dishonesty can take many forms. It may refer to out-and-out fabrication or falsification of data or reporting of results or plagiarism. It includes such things as misrepresentation (e.g., avoiding blame, claiming that protocol requirements have been followed when they have not, or producing significant results by altering experiments that have been previously conducted), nonreporting of phenomena, cherry-picking of data, or overenhancing pictorial representations of data. Honest work includes accurate reporting of what was done, including the methods used to do that work. Thus, dishonesty can encompass lying by omission, as in leaving out data that change the overall conclusions or systematically publishing only trials that yield positive results. The “file drawer” effect was first discussed almost 40 years ago; Robert Rosenthal (1979) presented the extreme view that “journals are filled with the 5 percent of the studies that show Type I errors, while the file drawers are filled with the 95 percent of the studies that show non-significant results.” This hides the possibility of results being published from 1 significant trial in an experiment of 100 trials, as well as experiments that were conducted and then altered in order to produce the desired results. The file drawer effect is a result of publication bias and selective reporting, the probability that a study will be published depending on the significance of its results ( Scargle, 2000 ). As the incentives for researchers to publish in top journals increase, so too do these biases and the file drawer effect.

Another example of dishonesty by omission is failing to report all funding sources where that information is relevant to assessing potential biases that might influence the integrity of the work. Conversely, dishonesty can also include reporting of nonexistent funding sources, giving the impression that the research was conducted with more support and so may have been more thorough than in actuality.

Beyond the individual researcher, those engaged in assessing research, whether those who are funding it or participating in any level of the peer review process, also have fundamental responsibilities of honesty. Most centrally, those assessing the quality of science must be honest in their assessments and aware of and honest in reporting their own conflicts of interest or any cognitive biases that may skew their judgment in self-serving ways. There is also a need to guard against unconscious bias, sometimes by refusing to assess work even when a potential reviewer is convinced that he or she can be objective. Efforts to protect honesty should be reinforced by the organizations and systems within which those assessors function. Universities, research organizations, journals, funding agencies, and professional societies must all work to hold each other to honest interactions without favoritism and with potentially biasing factors disclosed.

Openness is not the same as honesty, but it is predicated on honesty. In the scientific enterprise, openness refers to the value of being transparent and presenting all the information relevant to a decision or conclusion. This is essential so that others in the web of the research enterprise can understand why a decision or conclusion was reached. Openness also means making the data on which a result is based available to others so that they may reproduce and verify results or build on them. In some contexts, openness means listening to conflicting ideas or negative results without allowing preexisting biases or expectations to cloud one's judgment. In this respect, openness reinforces objectivity and the achievement of reliable observations and results.

Openness is an ideal toward which to strive in the research enterprise. It almost always enhances the advance of knowledge and facilitates others in meeting their responsibilities, be it journal editors, reviewers, or those who use the research to build products or as an input to policy making. Researchers have to be especially conscientious about being open, since the incentive structure within science does not always explicitly reward openness and sometimes discourages it. An investigator may desire to keep data private to monopolize the conclusions that can be drawn from those data without fear of competition. Researchers may be tempted to withhold data that do not fit with their hypotheses or conclusions. In the worst cases, investigators may fail to disclose data, code, or other information underlying their published results to prevent the detection of fabrication or falsification.

Openness is an ideal that may not always be possible to achieve within the research enterprise. In research involving classified military applications, sensitive personal information, or trade secrets, researchers may have an obligation not to disseminate data and the results derived from those data. Disclosure of results and underlying data may be delayed to allow time for filing a patent application. These sorts of restrictions are more common in certain research settings—such as commercial enterprises and government laboratories—than they are in academic research institutions performing primarily fundamental work. In the latter, openness in research is a long-held principle shared by the community, and it is a requirement in the United States to avoid privileged access that would undermine the institution's nonprofit status and to maintain the fundamental research exclusion from national security-based restrictions.

As the nature of data changes, so do the demands of achieving openness. For example, modern science is often based on very large datasets and computational implementations that cannot be included in a written manuscript. However, publications describing such results could not exist without the data and code underlying the results. Therefore, as part of the publication process, the authors have an obligation to have the available data and commented code or pseudocode (a high-level description of a program's operating principle) necessary and sufficient to re-create the results listed in the manuscript. Again, in some situations where a code implementation is patentable, a brief delay in releasing the code in order to secure intellectual property protection may be acceptable. When the resources needed to make data and code available are insufficient, authors should openly provide them upon request. Similar considerations apply to such varied forms of data as websites, videos, and still images with associated text or voiceovers.

Central to the functioning of the research enterprise is the fundamental value that members of the community are responsible for and stand behind their work, statements, actions, and roles in the conduct of their work. At its core, accountability implies an obligation to explain and/or justify one's behavior. Accountability requires that individuals be willing and able to demonstrate the validity of their work or the reasons for their actions. Accountability goes hand in hand with the credit researchers receive for their contributions to science and how this credit builds their reputations as members of the research enterprise. Accountability also enables those in the web of relationships to rely on work presented by others as a foundation for additional advances.

Individual accountability builds the trustworthiness of the research enterprise as a whole. Each participant in the research system, including researchers, institutional administrators, sponsors, and scholarly publishers, has obligations to others in the web of science and in return should be able to expect consistent and honest actions by others in the system. Mutual accountability therefore builds trust, which is a consequence of the application of the values described in this report.

The purpose of scientific publishing is to advance the state of knowledge through examination by peers who can assess, test, replicate where appropriate, and build on the work being described. Investigators reporting on their work thus must be accountable for the accuracy of their work. Through this accountability, they form a compact with the users of their work. Readers should be able to trust that the work was performed by the authors as described, with honest and accurate reporting of results. Accountability means that any deviations from the compact would be flagged and explained. Readers then could use these explanations in interpreting and evaluating the work.

Investigators are accountable to colleagues in their discipline or field of research, to the employer and institution at which the work is done, to the funders or other sponsors of the research, to the editors and institutions that disseminate their findings, and to the public, which supports research in the expectation that it will produce widespread benefits. Other participants in the research system have other forms of accountability. Journals are accountable to authors, reviewers, readers, the institutions they represent, and other journals (for the reuse of material, violation of copyright, or other issues of mutual concern). Institutions are accountable to their employees, to students, to the funders of both research and education, and to the communities in which they are located. Organizations that sponsor research are accountable to the researchers whose work they support and to their governing bodies or other sources of support, including the public. These networks of accountability support the web of relationships and responsibilities that define the research enterprise.

The accountability expected of individuals and organizations involved with research may be formally specified in policies or regulations. Accountability under institutional research misconduct policies, for example, could mean that researchers will face reprimand or other corrective actions if they fail to meet their responsibilities.

While responsibilities that are formally defined in policies or regulations are important to accountability in the research enterprise, responsibilities that may not be formally specified should also be included in the concept. For example, senior researchers who supervise others are accountable to their employers and the researchers whom they supervise to conduct themselves as professionals, as this is defined by formal organizational policies. On a less formal level, research supervisors are also accountable for being attentive to the educational and career development needs of students, postdoctoral fellows, and other junior researchers whom they oversee. The same principle holds for individuals working for research institutions, sponsoring organizations, and journals.

The scientific enterprise is filled with professional relationships. Many of them involve judging others' work for purposes of funding, publication, or deciding who is hired or promoted. Being fair in these contexts means making professional judgments based on appropriate and announced criteria, including processes used to determine outcomes. Fairness in adhering to explicit criteria and processes reinforces a system in which the core values can operate and trust among the parties can be maintained.

Fairness takes on another dimension in designing criteria and evaluation mechanisms. Research has demonstrated, for example, that grant proposals in which reviewers were blinded to applicant identity and institution receive systematically different funding decisions compared with the outcomes of unblinded reviews ( Ross et al., 2006 ). Truly blinded reviews may be difficult or impossible in a small field. Nevertheless, to the extent possible, the criteria and mechanisms involved in evaluation must be designed so as to ensure against unfair incentive structures or preexisting cultural biases. Fairness is also important in other review contexts, such as the process of peer reviewing articles and the production of book reviews for publication.

Fairness is a particularly important consideration in the list of authors for a publication and in the citations included in reports of research results. Investigators may be tempted to claim that senior or well-known authors played a larger role than they actually did so that their names may help carry the paper to publication and readership. But such a practice is unfair both to the people who actually did the work and to the honorary author, who may not want to be listed prominently or at all. Similarly, nonattribution of credit for contributions to the reported work or careless or negligent crediting of prior work violates the value of fairness. Best practices in authorship, which are based on the value of fairness, honesty, openness, and accountability, are discussed further in Chapter 9 .

Upholding fairness also requires researchers to acknowledge those whose work contributed to their advances. This is usually done through citing relevant work in reporting results. Also, since research is often a highly competitive activity, sometimes there is a race to make a discovery that results in clear winners and losers. Sometimes two groups of researchers make the same discovery nearly simultaneously. Being fair in these situations involves treating research competitors with generosity and magnanimity.

The importance of fairness is also evident in issues involving the duty of care toward human and animal research subjects. Researchers often depend on the use of human and animal subjects for their research, and they have an obligation to treat those subjects fairly—with respect in the case of human subjects and humanely in the case of laboratory animals. They also have obligations to other living things and to those aspects of the environment that affect humans and other living things. These responsibilities need to be balanced and informed by an appreciation for the potential benefits of research.

The research enterprise cannot continue to function unless the members of that system exhibit good stewardship both toward the other members of the system and toward the system itself. Good stewardship implies being aware of and attending carefully to the dynamics of the relationships within the lab, at the institutional level, and at the broad level of the research enterprise itself. Although we have listed stewardship as the final value in the six we discuss in this report, it supports all the others. Here we take up stewardship within the research enterprise but pause to acknowledge the extension of this value to encompass the larger society.

One area where individual researchers exercise stewardship is by performing service for their institution, discipline, or the broader research enterprise that may not necessarily be recognized or rewarded. These service activities include reviewing, editing, serving on faculty committees, and performing various roles in scientific societies. Senior researchers may also serve as mentors to younger researchers whom they are not directly supervising or formally responsible for. At a broader level, researchers, institutions, sponsors, journals, and societies can contribute to the development and updating of policies and practices affecting research. As will be discussed in Chapter 9 , professional societies perform a valuable service by developing scientific integrity policies for their fields and keeping them updated. Individual journals, journal editors, and member organizations have contributed by developing standards and guidelines in areas such as authorship, data sharing, and the responsibilities of journals when they suspect that submitted work has been fabricated or plagiarized.

Stewardship also involves decisions about support and influences on science. Some aspects of the research system are influenced or determined by outside factors. Public demand, political considerations, concerns about national security, and even the prospects for our species' survival can inform and influence decisions about the amount of public and private resources devoted to the research enterprise. Such forces also play important roles in determining the balance of resources invested in various fields of study (e.g., both among and within federal agencies), as well as the balance of effort devoted to fundamental versus applied work and the use of various funding mechanisms.

In some cases, good stewardship requires attending to situations in which the broader research enterprise may not be operating optimally. Chapter 6 discusses issues where problems have been identified and are being debated, such as workforce imbalances, the poor career prospects of academic researchers in some fields, and the incentive structures of modern research environments.

Stewardship is particularly evident in the commitment of the research enterprise to education, both of the next generation of researchers and of individuals who do not expect to become scientists. In particular, Chapter 10 discusses the need to educate all members of the research enterprise in the responsible conduct of research. Education is one way in which engaging in science provides benefits both to those within the research system and to the general public outside the system.

• A DEFINITION OF RESEARCH INTEGRITY

Making judgments about definitions and terminology as they relate to research integrity and breaches of integrity is a significant component of this committee's statement of task. Practicing integrity in research means planning, proposing, performing, reporting, and reviewing research in accordance with the values described above. These values should be upheld by research institutions, research sponsors, journals, and learned societies as well as by individual researchers and research groups. General norms and specific research practices that conform to these values have developed over time. Sometimes norms and practices need to be updated as technologies and the institutions that compose the research enterprise evolve. There are also disciplinary differences in some specific research practices, but norms and appropriate practices generally apply across science and engineering research fields. As described more fully in Chapter 9 , best practices in research are those actions undertaken by individuals and organizations that are based on the core values of science and enable good research. They should be embraced, practiced, and promoted.

• Cite this Page National Academies of Sciences, Engineering, and Medicine; Policy and Global Affairs; Committee on Science, Engineering, Medicine, and Public Policy; Committee on Responsible Science. Fostering Integrity in Research. Washington (DC): National Academies Press (US); 2017 Apr 11. 2, Foundations of Integrity in Research: Core Values and Guiding Norms.
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Research Environment

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• First Online: 28 March 2023

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• Lana Barać   ORCID: orcid.org/0000-0002-0170-5972 3  

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Successful research environment requires joint effort by individual researchers, research groups and the organization. This chapter describes the basic principles and good research practices in the context of the research environment and serves as a guide to good, responsible research for research newcomers – researchers at the beginning of their scientific career. In this chapter we will help you navigate the organizational pathway to doing good research. The first step to understanding your rights, obligations and responsibilities in research is knowing that they exist. This chapter offers an introductory level orientation to codes, rules and regulations but also serves as a guide on how to identify whether your organization goes above and beyond offering guidance and assistance regarding research integrity or whether it provides a bare minimum or even nothing at all, and who/what you can turn to in the latter case. Furthermore, this chapter also describes the responsibilities that you as a researcher have towards the organisation regarding the importance of maintaining research integrity, so that you are aware of your accountability and the possible consequences if you disregard organizational responsibility for responsible research.

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• Research climate
• Research culture
• Research ethics structures
• Research integrity structures

What This Chapter Is About

Successful research environment requires joint effort by individual researchers, research groups and the organization. This chapter describes the basic principles and good research practices in the context of research environment and serves as a guide to good, responsible research for research newcomers – researchers at the beginning of their scientific career. In this chapter we will help you navigate the organizational pathway to doing good research. The first step to understanding your rights, obligations and responsibilities in research is knowing that they exist. This chapter offers an introductory level orientation to codes, rules and regulations but also serves as a guide on how to identify whether your organization goes above and beyond offering guidance and assistance regarding research integrity or whether it provides a bare minimum or even nothing at all, and who/what you can turn to in the latter case. Furthermore, this chapter also describes the responsibilities that you as a researcher have towards the organisation regarding the importance of maintaining research integrity, so that you are aware of your accountability and the possible consequences if you disregard organizational responsibility for responsible research.

Case Scenario: Research Environment and Research Integrity

This hypothetical scenario was adapted from a narrative concerning the links between research environments and research integrity. The case scenario was developed by the Members of The Embassy of Good Science and is available at the Embassy of Good Science . The case below is published under Creative Commons Attribution-ShareAlike license, version 4.0 (CC BY-SA 4.0).

After 6 months of working as a novice researcher in a research lab at a university school, you meet up with a colleague who graduated with you and is now working as a novice researcher in a commercial research organization. She tells you that she may have encountered a potential research misconduct concerning intellectual property. She knew what she had to do because the company is very committed to making sure all employees are fully informed about all existing rules and regulations. Her action prevented the misconduct. That conversation made you think that you were never been briefed or informed in detail about rules and regulations regarding research when you signed your employment contract with your organization. You heard your mentor casually mention “standard rules of conduct in research,” expecting you to know what they are. The day after your meeting with your colleague, you check your school’s webpages for information on research integrity. Although there is no explicit mention of research integrity, your University’s website refers to its own code of conduct as well as the European Code of Conduct for Research Integrity. Furthermore, a university-wide academic integrity complaints procedure and a research integrity committee are mentioned but details of which, however, cannot be found on the university’s public webpages. After talking to your fellow novice researchers, you realize that they too are uncertain about whether your school has written guidelines for research integrity. You also realize that they feel pressurized to generate more and more research outputs and that insecurity, linked to short-term contracts and scarce opportunities for professional advancement, means that they perceive the incentives to succeed in research and academia as outweighing the incentives to comply with the norms of good research practices. They not only feel that your school does not adequately promote research integrity but that that pressure comes within the organization, also as a result of the culture of “ publish or perish ” After talking to them you realise that there is more to this problem than just ignorance or integrity issues with individual novice researchers and that their views could indicate an environmental problem in academia.

Questions for You

In light of this case scenario, what do you think which person(s) or groups should be responsible for the early-career researchers’ general lack of knowledge concerning the university’s research integrity guidelines, codes of conduct and complaints procedures? What are the reasons for your answer?

In what ways could a research organization make its research integrity standards, guidelines and processes more visible to its researchers, especially early-career researchers? What initiatives should be promoted in a research organization in order to engage early-career researchers with research integrity standards, guidelines and processes?

Thinking about the ways in which your organization currently engages early-career researchers with research integrity standards, guidelines and processes, what could be done to improve such engagement at the level of your organization and the level of your department or laboratory?

The Responsibilities of the Organization: Above and Beyond, or the Bare Minimum?

Good research practice from the european code of conduct for research integrity:.

Research institutions and organisations promote awareness and ensure a prevailing culture of research integrity .

When starting at a new job in a new research organization you have to understand that an organization is a living organism – a system with organized structure that functions as an individual entity and is, as all organisms are, prone to constant change. One change that has been having a huge momentum in Europe in recent years is the initiative to encourage activities that show commitment of organizations to make research integrity (RI) and responsible research in general as a top priority. Empowering sound and verifiable research and fostering a research integrity culture, thus creating a proper research environment, is now empowered by embedding these principles as requirements in EU funding schemes. As research environment is a dimension that needs to be considered by all involved stakeholders, activities conducted in order to foster good research practices and a culture of research integrity will impact researchers at all levels.

When we talk about organization as a system, the terms organizational climate and organizational culture are sometimes used interchangeably or considered as complementary constructs. The two terms are different. Organizational climate is usually defined as shared perceptions of policies, practices and procedures experienced by the employees, as well as the behaviours the employees perceive as rewarding. It is considered to be the measurable manifestation of organizational culture , which is defined as the system of basic assumptions, deep values and beliefs that are prevalent in the organization. Organizational culture is something that has to be built, maintained and nurtured by supportive environment.

As a part of organizational culture, research integrity has become an integral part of a university’s mission, vision and strategy. For example; universities in France will, in the near future, in what seems to be the first national initiative of its kind, go as far as requiring Ph.D. recipients to take an integrity oath on the day they successfully defend their thesis. Research integrity is also dependent on human factors – collegiality, openness, reflection, shared responsibility and work satisfaction are vital elements of a successful working environment. As a novice researcher, you should try, from the very beginning of your career, to comply with the highest standards of ethics and integrity in the performance of your research.

How can you figure out the ethical landscape at the very start of your career? The first step to understanding your rights, obligations and responsibilities is knowing that they exist .

Rules, codes and regulations can be created by the organization itself but also by national or international bodies. They can have different names and vary in scope, but they are always a written set of instructions issued by an organization. Depending on the scope of action, codes can cover issues prescribed by legal regulations such as: human subject’s protection, animal care, intellectual property and confidentiality, legality and mechanisms to identify and procedure for reporting and dealing with research misconduct. Other than binding legal issues, codes can also cover fundamental principles of research which serve organisations in creating and preserving an environment for responsible research. Fundamental principles presented by the most widely recognized and accepted documents – European Code of Conduct for Research Integrity (All European Academies 2017) and Fostering Integrity in Research (US National Academies of Sciences, Engineering, and Medicine 2017), might not be identical in the naming of the principles but the meaning of the principles in RI perspective is similar (Table 1.1 ).

Not all research or academic organizations are as big or as well developed to have the resources to promptly and adequately inform you about all rules and obligations regarding research. That does not mean you are not required to follow them or that your rights are not protected by them. Organizational guides and codes should be easily accessible on the organization’s webpages and/or intranet. You should be provided with adequate training, tailored to the research discipline and the type of organization, and briefed about standard rules of conduct in research. Bear in mind that the organizational support structure is usually proportional to the size and complexity of the organization. Apart from having binding documents about responsible research, your organization should have established channels to facilitate an open dialogue at and between all levels; from management and senior researchers to novice researchers and other members of staff. Ideally, your organization should, apart from the standard rules and regulations, develop and implement a research integrity promotion plan (RIPP). This is a document that describes, on a general level, how the organization promotes research integrity and which concrete methods are employed or are being developed to foster research integrity and to deal with allegations of breaches of research integrity. Procedures to increase transparency of research investigation procedure and safe and effective whistle-blowing channels and the protection of alleged perpetrators should also be implemented in line with the legal principle of the presumption of innocence – someone accused of research misconduct is considered innocent until proven guilty.

When navigating the research environment, it is always advisable to consider the human factor. Some organizations are very organized. Some are not. Even though an organization may be committed to following the prescribed rules, do not expect to be given a clear and user-friendly version of these rules upon arrival. Some organizations have rules and regulations because they had to comply with national or international regulations. Other organizations have them because the management is devoted to actively promoting responsible research. Some organizations are understaffed, so the lack of organizational documents may not necessarily reflect the moral of the organization. In brief, even if your organization does not have instructions for the new employees written on a (virtual) bulletin board, that does not mean that they do not exist, so no matter whether you were briefed or not these rules apply to you and you should be governed by those rules.

Here is some advice for you on how to navigate responsible research environment in your organization:

Always get familiar with existing laws, codes and regulations in the organization and country where you work. If you are a member of a professional organization or if you are professionally bound to the code of ethics of your profession, check whether the professional code is aligned with that of your organisation. Some organizations may provide a checklist with sources and links to different guidelines and rules of procedure for good research practice available online. Do not forget to get familiar with international principles and EU standards such as The European Code of Conduct for Research Integrity , principles prescribed for different professions (e.g., The Declaration of Helsinki or Convention on Biological Diversity ) and national guidelines, but first and foremost to the documents and guidance provided by your organization.

Consider that different views of research ethics around the world reflect differences in culture and legal frameworks, which can lead to differences in regulations. For example, the European General Data Protection Regulation (GDPR) has a very expansive definition of personal information that may warrant protection, whereas in the United States (US), there is a narrower (and often domain-specific) characterization of privacy-sensitive information. Even within the EU, there are differences among EU member countries – the examples are different laws on stem-cell research and human embryos. Differences in regulations unfortunately may lead to ethics dumping – the practice of researchers trained in cultures with rigorous ethical standards to go and conduct research in countries with laxer ethical rules and oversight, in order to circumvent the regulations, policies, or processes that exist in their home countries.

Keep in mind that codes and regulations change and can evolve. For example, The Nuremberg Code; which is a set of research ethics principles for human experimentation was created by the US vs. Brandt et al. court case, as a result of the Nuremberg trials at the end of the World War 2. The core elements of the Nuremberg Code are the requirements for voluntary and informed consent, a favourable risk/benefit analysis, and the right to withdraw from a study without consequences. That standard was confirmed in 1964, when the WMA’s Declaration of Helsinki was endorsed and again specified that experiments involving human beings needed the informed consent of participants. The Declaration of Helsinki has been updated overe the years, so make sure that you consult its latest version. Another example is the infamous Tuskegee syphilis study , funded by the US Public Health Service. The study was conducted between 1932 and 1972 at Tuskegee Institute in Alabama to evaluate the natural history of untreated syphilis in African American males. The study was conducted for 40 years without ethical review and denied participants the effective treatment for this curable disease. The study became a milestone in the history of US research regulations, as it was conducted without ethical re-evaluation in spite of both The Nuremberg Code and the Declaration of Helsinki being accepted and established as a standard during the study. The aftermath of the public disclosure of the Tuskegee study led to the establishment of the National Commission for the Protection of Human Subjects of Biomedical and Behavioural Research and the National Research Act that requires the establishment of institutional review boards (IRBs) at institutions receiving federal support.

Codes and regulations can also change due to scientific advancements that lead to new fields of research (e.g., the emergence of experimental psychology) or new technologies (e.g., gene editing, artificial intelligence). The changes can also come in response to changes in cultural values and behavioural norms that evolve over time (e.g., perceptions of privacy and confidentiality).

Consider emerging ethics topics , even if they are not listed or mentioned in current codes of your organization, such as bystander risk (impacts of research on other people; e.g. genetic testing and genetic research, second-hand exposure to a contagious disease) big data and open science (concerns about the potential to compromise privacy), and citizen science (involving community participation in science, allowing the research population to become researchers).

Research institutions and organisations demonstrate leadership in providing clear policies and procedures on good research practice and the transparent and proper handling of violations.

Knowing, understanding and using existing codes and regulations for good research is important and useful, but there may be times when you are in doubt about how what is written in a code translates into real life. Therefore, it is important to learn how to interpret, assess, and apply different research rules and how to make decisions to act ethically and responsibly in different situations or at least know who to turn to when in doubt . To put it simply: pure existence of the codes does not make an ethical environment. Or, in words of Aristotle: “One swallow does not a summer make.”

If codes, rules and regulations are the foundation of research integrity culture, building strong pillars to rest upon, establishing research ethics structures is the next crucial step for organizations to ensure proper research environment.

Different organizations may have different supportive mechanisms to ensure that researchers adhere to research ethics and integrity requirements. Depending on the size and the type of the organization, key organizational bodies and staff dealing with research ethics and integrity might quite vary in name and scope of work. It is important to understand that, depending on type of research organisation, you may encounter organisational bodies (or individuals) with various scope of activities regarding research ethics and integrity. This may seem confusing at first, as the concepts of ethics and integrity may seem intertwined and actually, for the most part, they are. Research ethics (RE) is the term that encompassed fundamental moral principles and research integrity (RI) is the quality of having moral principles, defined as active adherence to the ethical principles and professional standards essential for the responsible practice of research. Both of them are a necessary part of responsible conduct of research.

Ideally, your organisation will have all necessary structures, processes, and dedicated and adequately trained staff to uphold best research practices and standards, and deal with procedures relevant to the various research areas and disciplines within the organisation. Listed below are some of the common research ethics and integrity bodies (names might vary). If there is only one of these at your organisation, the scope of their responsibilities is probably wider and you can still contact them regarding any doubt and insecurity you might have about responsible research.

Ethics Committee or Institutional Review Board is probably the most common body at academic and research organizations, because it has the longest history. Research Ethics Committees were developed after the World War 2, particularly in response to The Nuremberg Trials, as bodies responsible for oversight of medical or human research studies. The role of an Ethics Committee is to scrutinise research proposals and ensure that the proposed research adequately addressed all relevant ethics issues. This means that they make sure that proposed research protocols protect rights, safety, dignity and well-being of participants, that research protocols involving animals follow the highest animal care standards and that they facilitate and promote ethical research that is of potential benefit to participants, science and society. In smaller organisations that do not necessarily have other bodies, the role of the Ethics Committee would also be to facilitate and promote research integrity and good research practices, to have mechanisms to identify and procedure for reporting and dealing with allegations of breaches of research integrity (research misconduct).

Board/Office/ Commission for Research Integrity is a body that promotes responsible research conduct, serves as a knowledge base for questions regarding research integrity and research misconduct, informs on policies and procedures in and outside of the organization, handles allegations of research misconduct and conducts investigations, advises on administrative action and also responds to allegations of retaliation against whistle-blowers. It is responsible for providing advice for researchers on how to adhere to responsible research practices, usually through guidelines, checklists and other documents in which good research practices are presented. The organisational structures of RI committees and their responsibilities regarding cases of research misconduct may vary depending on the organisational or national regulations. For example, the Office for Research Integrity in the US is a governmental body that has monitoring and oversight role to ensure that researchers and organisations which receive federal funding for health research comply with existing regulations; it offers support to further good practice research and promote integrity and high ethical standards, as well as to have robust and fair methods to address poor research practices and misconduct.

Another individual position you may encounter at your organisation is the Research Integrity Officer (RIO) , a professional with a complex role. An organisation’s RIO promotes responsible research, conducts research training, discourages research misconduct, and deals with allegations of or evidence of possible research misconduct. The details of an RIO’s job vary from country to country, but the position is mandatory in many. For example, in US organisations, a RIO serves as the liaison between the federal Office for Research Integrity and the organisation of the researchers. In the EU, countries have different requirements and roles for their RIOs, but their task is essentially the same. Some countries do not have such bodies, and their role is most often taken by Ethics Committees.

Your organisation may have a Research Integrity Ombudsperson or Confidential Advisor on Scientific Integrity or Research Integrity Advisor . The aim of such an advisor is to promote fair, non-discriminatory and equitable treatment related to research integrity within the organisation and improve the overall quality of the research working environment. Such a position should be well known in the organisation, and there should be a low threshold for contacting this person. Researchers who experience research integrity dilemmas or have come into an integrity-related conflict should be able to discuss their case with the ombudsperson in a strictly confidential manner. The function of the ombudsperson should be clearly separated from a formal research integrity committee or ethics committee, so that it is clear to researchers that contacting the ombudsperson does not imply a formal registration of an allegation but a confidential and informal assistance in resolving research work-related conflicts, disputes and grievances (including, but not limited to complaints/appeals of researchers regarding conflicts between supervisor(s) and early-stage researchers).

Research institutions and organisations support proper infrastructure for the management and protection of data and research materials in all their forms (encompassing qualitative and quantitative data, protocols, processes, other research artefacts and associated metadata) that are necessary for reproducibility, traceability and accountability.

Even as an early-career researcher you probably realise that, while doing research, dealing with a fair amount of different types of data is inevitable. Ten years ago the Science journal polled their peer reviewers from the previous year on the availability and use of research data, and, about half of those polled stored their data only in their laboratories. If you had walked in any type of research organisation 10 years ago you would have had probably been briefed about keeping your lab notebook records and advised about keeping your data somewhere other than your lab desktop computer. Today, when we talk about data management, we go well beyond keeping your lab or research notebook in order. While maintaining a lab notebook is still essential for anybody performing research as a document of completed work so that research can be replicated and validated; or a legal document to prove intellectual property/invention, data management on an organisational level entails much more . It comprises the infrastructure (technology, services and staff support), training for researchers, and policies on data management (DMPs). Therefore, you should expect from your organisation to provide instructions and policies regarding data curation (repositories), management, use, access, publishing, and sharing. Regarding the technology for data management, your organisation should provide appropriate storage media that enables collecting, organizing, protecting, storing, and sharing data. It should also inform you about available data repositories, networks and different authentication systems. Research organisations should make DMPs easily accessible and organisations’ websites should provide extensive information about the concept of data sharing in general, as well as detailed information on DMP requirements and how to comply with them. Services and staff support for data management are highly dependent on the amount of funding and size of an organisation because the amount of work and time involved in these processes is extensive and costly. Some organisations have whole departments and others at best a single person for data management.

In 2019, Science Europe released its Practical Guide to the International Alignment of Research Data Management , and, as a follow-up, compiled the document to showcase some best practices. The document also demonstrated the variability of data management processes in different organisations. Although the readiness to develop DMPs can differ according to discipline, most research funders require researchers to include a DMP in their project proposals. You should expect from your organisation to have in place the structures and procedures to facilitate data management and curation procedures that are aligned with FAIR principles, which say that data should be F indable, A ccessible, I nteroperable, and R eusable. Bear in mind that researchers’ knowledge about research data management could be limited in countries and organisations where open science policies are not well developed. This leads to misunderstandings about the need to store and archive data. For detailed guidance on data practices and management throughout the lifecycle of research data and instructions to preparation of data management plans (DMPs) see Chap. 5 .

Research institutions and organisations reward open and reproducible practices in hiring and promotion of researchers.

No matter whether you have been in research for some time or you are a novice researcher, you have probably heard the catchphrase “ publish or perish !” because it has been uttered in whisper by stressed and burned-out researchers all over the world for years, putting pressures on individual integrity and potentially fostering practices harmful to scientific research. Publish or perish culture thrives on metrics (number of articles published and impact factors of journals) but fails to adequately take societal and broader impact into account . Some aspects of research are indeed quantifiable and cannot be and will not be ignored, but recent efforts towards more inclusive evaluation scheme of research and researchers could be a “game-changer”, meaning that yes, you are still required to publish, but the scientific efforts that translate better to a broader community will not be ignored.

When it comes to hiring and promotion in research, the need for transparency should be self-explanatory, but what does promoting open practices mean in reality? Geographically speaking, Europe might be ahead of the curve in endorsing and implementing changes as the new framework programme Horizon Europe makes Open Science mandatory throughout the programme and includes Open Innovation as one of three framework pillars. What does this mean for you? Although the attitude and the level of commitment of the organisation toward endorsing open science principles could vary and very much depend on the human factor, there is no reason for you not to be aware of the change to come and strive to fulfil the general idea of quality . Producing quality science would imply producing substantive, impactful science , science that reaches broader audience and addresses valuable questions, but is also reliable enough to build upon. This mean that evaluation and appraisal procedures may assess a researcher’s contribution to addressing societal needs and publishing all research completely and transparently, regardless of whether the results were positive or negative. This would also imply implementing open research practices and embedding these skills in training of early-career researchers, making preliminary results and final results available to the general public, potential users and the research community, in order to facilitate broader assessment and accountability of research.

There are also indications that the EU is moving towards a structured CV which would include Responsible Indicators for Assessing Scientists (RIAS), and other related information. For example; the department of psychology at LMU München added a paragraph to a professorship job advertisement which asks for an open science statement from the candidates: “Our department embraces the values of open science and strives for replicable and reproducible research. For this goal we support transparent research with open data, open material, and pre-registrations. Candidates are asked to describe in what way they already pursued and plan to pursue these goals.” Another example is University of Liège , where depositing papers in the repository is now the sole mechanism for submitting them to be considered when researchers underwent performance review.

Check whether your organisation has procedures related to the publication and communication of research results, such as preregistration, preprints, and online repositories, the organisational approach to open access, FAIR data curation, expectations about the use of reporting guidelines, procedures for avoiding predatory journals, strategies for responsible peer review practices, and mechanisms to support and acknowledge public communication of research findings. Also, check whether your organisation is ahead of the curve in promoting Open Science (Fig. 1.1 ) check for procedures and practices through the organisation’s own website or other established platforms on organisational or national level, check whether your organisation has signed any declaration relevant to Open Science .

Core principles of Open Science. For details, see the FOSTER project

The Responsibilities of the Researcher

Ask not what your organisation can do for you – ask what you can do for your organisation.

While The European Code of Conduct for Research Integrity (ECoC RI) provides general guidance for good research practices and serves as a framework for self-regulation, the document that details your role, responsibilities and entitlements as a researcher is The European Charter for Researchers . The Charter is a set of general principles and requirements that addresses all researchers in the European Union at all stages of their career, covers all fields of research and takes into account the multiple roles that researchers can have.

Being a researcher is highly related to context and not defined only by job positions, formal qualifications level of education or by seniority at work. According to The Frascati definition ; Researchers are professionals engaged in the conception or creation of new knowledge . They conduct research and improve or develop concepts, theories, models, techniques instrumentation, software or operational methods. The tasks performed depend on job characteristics and personal strengths but have to be related to research and innovation. Activities of a researcher are many, but first and foremost entail: conducting and evaluating research and innovation, applying for research funding, managing projects and teams, managing, sharing and transferring the generated knowledge (including through scholarly communication, science communication to society, knowledge management for policy, and knowledge transfer to industry) and higher education teaching.

As an early-career researcher, you should keep in mind that everything you do reflects upon your organisation . So be sure to comply with the highest values and ethical standards and aim at excellence. Even as a novice researcher, at a beginning of your career be aware that your organisation will treat you as a responsible adult and will hold you accountable . Also, depending on the applicable rules, your organisation might be held accountable for your wrongdoing, so, even if you are there for a brief amount of time (post-doctoral or project-based position) remember that you are a part of the research environment and are expected to contribute to a positive, fair and stimulating research culture.

Science is by definition a joint endeavour and you should learn to accept responsibility because that is what being accountable entails. Accountability refers to an obligation or willingness to accept responsibility for one’s actions, meaning that, when individuals are accountable, they understand and accept the consequences of their actions for the areas in which they assume responsibility. Remember that you, as an employee, have contractual and legal obligations. That basically means that you are liable in case of breach of contract and you have to adhere to such regulations by delivering the required results (e.g. thesis, publications, patents, reports, new products development, etc), as set out in the terms and conditions of the contract or equivalent document. You should be familiar with the strategic goals, seek all necessary approvals before starting your research or accessing the resources provided. You should, at all times, keep a professional attitude . This included maintaining a professional etiquette at workplace – respectful and courteous demeanour towards colleagues and respect in the sense of responsibilities (e.g. informing your supervisor if you are not able to meet deadlines).

As a researcher, you should, first and foremost, focus your research for the good of mankind and for expanding the frontiers of scientific knowledge. You should be guaranteed the freedom of thought and expression , and the freedom to identify methods by which problems are solved, according to recognized ethical principles and practices. But, bear in mind that there is a difference between using research freedom and abusing it. You should, by all means, recognize the limitations to this freedom that could arise as a result of particular research circumstances or operational constraints (e.g. for budgetary or infrastructural reasons or, especially in the industrial sector, for reasons of intellectual property protection). Such limitations should not contravene recognized ethical principles and practices in research. When it comes to ethical principles , you should adhere to the recognized ethical practices and fundamental ethical principles appropriate to your discipline, as well as to ethical standards defined in different national, sectoral or organisational codes of ethics. It is highly recommended to conduct ethics self-assessment at the very beginning of planning your research. Ethics self-assessment helps getting your research protocol ethics-ready , as it may give rise to binding obligations that may later on be checked through ethics checks and reviews. Consider that ethics issues arise in many areas of research and, as of recently, major scientific journals require researchers to provide ethics committee approval before publishing research articles. You should also adopt safe working practices, in line with national legislation, including taking the necessary precautions by preparing proper back-up strategies.

As we mentioned before, Open Science practices should be the norm, especially when performing publicly funded research, as they improve the quality, efficiency, responsiveness of research and trust in science. You should guarantee open access to research publications and research data and foster innovation in sharing research knowledge as early as possible in the research process, through adequate infrastructures and tools. You should ensure, in compliance with your contractual arrangements, that the results of your research are disseminated and exploited. Be public and open about your research . There are, of course, legitimate reasons to restrict access to certain data sets (for instance in order to protect the privacy of research subjects) so be guided by the principle “ As open as possible, as closed as necessary” . Ensure that your research activities are made known to society at large in such a way that they can be understood by non-specialists, thereby improving public understanding of science. Direct engagement with the public will help researchers better understand public interest in priorities for science and technology and also their concerns.

You should seek to continually improve yourself by regularly updating and expanding your skills and competencies. This may be achieved by a variety of means including, but not restricted to, formal training, workshops, conferences and e-learning.

Do not be afraid to diversify your research career , as research community is diverse in talents and expertise and can produce a wide range of research outputs (from scholar publications to scientific advice for policy makers, science communication to the public, higher education teaching, knowledge transfer to industry, and many others). Explore different career paths within the research profession, so that your talent finds the best place to produce richer research results.

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Qin J (2013) Infrastructure, standards, and policies for research data management. In: Sharing of scientific and technical resources in the era of big data: the proceedings of COINFO 2013. Science Press, Beijing, pp 214–219

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Ščepanović R, Labib K, Buljan I, Tijdink J, Marušić A (2021) Practices for research integrity promotion in research performing organisations and research funding organisations: a scoping review. Sci Eng Ethics 27(1):4. https://doi.org/10.1007/s11948-021-00281-1

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National Academies of Sciences, Engineering, and Medicine (NASEM). (2017). Fostering integrity in research. Washington, DC: The National Academies Press. http://nap.nationalacademies.org/21896

Zohar DM, Hofmann DA (2012) Organizational culture and climate. In: Kozlowski SWJ (ed) The Oxford handbook of organizational psychology, vol 1. Oxford University Press, Oxford, pp 643–666

The European Code of Conduct for Research Integrity - framework for self-regulation across all scientific and scholarly disciplines and for all research settings. ECoC is a reference document for research integrity for all EU-funded research projects and as a model for organisations and researchers across Europe. All European Academies (ALLEA). (2017). https://allea.org/code-of-conduct/

The Bonn PRINTEGER Statement – Working with research integrity; guidance for research performing organisations

SOPs4RI Toolbox – Standard Operating Procedures and Guidelines that Research Performing and Funding Organisations can use to develop their own Research Integrity Promotion Plans

LERU – The League of European Research Universities (LERU) is a prominent advocate for the promotion of basic research at European research universities comprising of League of European Research Universities 23 leading universities pushing the frontiers of innovative research

Science Europe – Implementing Research Data Management Policies Across Europe: Experiences from Science Europe Member Organisations

Ask Open Science – Hosted by Bielefeld University, discussion (Q & A) on Open Science

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Barać, L. (2023). Research Environment. In: Marusic, A. (eds) A Guide to Responsible Research. Collaborative Bioethics, vol 1. Springer, Cham. https://doi.org/10.1007/978-3-031-22412-6_1

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EPA Awards Two Texas Institutions $3.2 Million for Research on PFAS Exposure and Reduction in Agriculture

September 12, 2024

DALLAS (September 12, 2024)  –The U.S. Environmental Protection Agency announced $3.2 million in total research grant funding for two Texas institutions for research to reduce per-and polyfluoroalkyl substances (PFAS) exposure from food and protect our farmlands and farming communities. The recipient institutions receiving this funding are Texas A&M University and Texas Tech University, both institutions will receive $1,600,000 each. These community-engaged research projects will collect PFAS bioaccumulation data in agricultural plants and livestock and explore strategies for reducing PFAS exposure, which are important parts of EPA’s commitment to protecting human health and the environment from PFAS.

“Farming communities are the lifeblood of this nation,”  said Christopher Frey, Assistant Administrator for EPA’s Office of Research and Development . “The research supported by these grants will increase our knowledge of how PFAS is impacting our farmlands and food supply and help ensure our farming communities stay viable for years to come.”

Texas A&M University which is based in College Station, Texas is receiving $1,600,000 to comprehensively understand PFAS uptake and bioaccumulation in plants and advance strategies to remediate PFAS in biosolids and biosolid-amended soils. Researchers will screen, design, and develop plant-based biosensors for PFAS detection in biosolids, soils, and water. They will also demonstrate the effectiveness of technologies in remediating PFAS in biosolids, reducing PFAS bioavailability to plants in biosolid-amended soils, and evaluating the sensitivity of developed biosensors in monitoring PFAS contamination. If successful, this research could empower agricultural communities, wastewater professionals, and decision makers to increase their ability to manage PFAS risk associated with the beneficial uses of biosolids and reclaimed water. 

Texas Tech University which is based in Lubbock, Texas is receiving $1,600,000  to investigate potential non-traditional PFAS sources in farming operations. Through lab and modeling studies, researchers will conduct a detailed survey and characterization of the impacts of manure and biosolid pre-application treatment or processing. They will also conduct plant cultivation studies to measure PFAS partitioning and bioavailability as a function of soil type and biosolid amendment and look at fish cultivation to measure PFAS uptake, partitioning, and elimination due to exposure to water and dietary sources, among other potential PFAS sources. The team will use data from lab studies to evaluate PFAS management strategies in agricultural settings.

PFAS, also known as ‘forever chemicals,’ are prevalent and persistent in the environment. PFAS are a category of chemicals used since the 1940s to repel oil and water and resist heat, which makes them useful in everyday products. Some PFAS do not easily degrade and can bioaccumulate – or build up – in the environment and the human body over time resulting in potential adverse health impacts. Given their persistence and potential health impacts, it is important to understand how PFAS may impact our food system and people living in agricultural areas so we can develop strategies to reduce and prevent these exposures. 

Using EPA’s funding, research teams will investigate topics including how PFAS accumulates in crops and livestock; the effects of biosolids, compost and irrigation water on PFAS plant uptake and accumulation; and strategies to reduce the risks of PFAS contamination in the food supply. The following institutions have been selected for awards, which are contingent on completion of all legal and administrative requirements relating to the grant:

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Global progress on adaptation implementation (Chapter in UNEP’s Adaptation Gap Report 2023)

Where do we stand globally on adaptation? One of UNEP’s annual flagship reports, the  Adaptation Gap Report  provides a detailed account and is an important input to COP28. It was cited in the outcome of the 1 st  Global Stocktake under the Paris Agreement (Decision 1/CMA.5) and informed the negotiations on the framework for the  Global Goal on Adaptation.

The Grantham Research Institute has been an important contributor to the  Adaptation Gap Report . Since 2020, Timo Leiter has been the lead author of the chapter ‘Global progress on adaptation implementation’. This chapter provides an overview of implemented adaptation worldwide, analysing what adaptation actions have been undertaken, for whom, where and against which climate hazards and risks. In 2023, the chapter undertook the first global analysis of  Adaptation Communications that Parties submitted to the UNFCCC secretariat.

Key messages from Chapter 3, Global progress on adaptation implementation

• In 2022, new adaptation projects at a combined value of US$559 million in grants from the Adaptation Fund (AF), the Green Climate Fund (GCF) and the Global Environment Facility (the GEF via its Least Developed Countries Fund [LDCF] and Special Climate Change Fund [SCCF]) started implementation. This is 10 per cent higher than the average amount implemented over the preceding five years (2017–2021).
• The average number of new adaptation projects that started under these three multilateral funds plateaued at just under 40 projects per year during the decade 2013–2022. Due to GCF, the average size of grant-funded adaptation projects has increased. Since 2017, an average of 15 per cent of new adaptation projects have grant funding of over US$25 million.
• Over 1,100 implemented adaptation actions are listed by 35 countries in their adaptation communications. However, details are provided for just 670 actions (60 per cent). Of these, almost half were reported as completed and 37 per cent as ongoing. The implementation status of the remaining 17 per cent of actions was unclear based on the information reported.
• Information on the outcomes of implementation was reported for only 6 per cent of the 670 adaptation actions. This finding underscores the continued need for information on results beyond the outputs of adaptation actions, in order to determine their effectiveness.
• More than half (57 per cent) of stand-alone adaptation communications acknowledge that vulnerability differs across demographics, and a majority underscores the imperative of addressing gender inequality. However, only a third of actions indicated that they were targeting vulnerable groups. Of those that did, farmers were the most targeted vulnerable group (46 per cent of actions targeting vulnerable groups), while women, fisherfolk and Indigenous Peoples were targeted marginally.
• Just over half of the actions for which a funding source was reported were funded by domestic sources. For developing (non-Annex I) countries, this proportion was one third. Stand-alone adaptation communications therefore provide a new source of information on domestically funded adaptation implementation that can help recognize adaptation efforts by developing countries.
• Three quarters of the developing (non-Annex I) countries that submitted a stand-alone adaptation communication received support for its compilation, demonstrating the importance of providing adequate support for adaptation reporting, especially for least developed countries (LDCs) and small island developing States (SIDS). This finding is also highly relevant for the development of biennial transparency reports, which are due by the end of 2024.

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• Published: 12 September 2024

A Late Devonian coelacanth reconfigures actinistian phylogeny, disparity, and evolutionary dynamics

• Alice M. Clement   ORCID: orcid.org/0000-0003-0380-7347 1   na1 ,
• Richard Cloutier   ORCID: orcid.org/0000-0001-5780-3304 1 , 2 , 3   na1 ,
• Michael S. Y. Lee 1 , 4 ,
• Benedict King 5 ,
• Olivia Vanhaesebroucke 2 ,
• Corey J. A. Bradshaw   ORCID: orcid.org/0000-0002-5328-7741 6 ,
• Hugo Dutel   ORCID: orcid.org/0000-0002-1908-5150 7 ,
• Kate Trinajstic   ORCID: orcid.org/0000-0002-6519-6396 8 , 9 &
• John A. Long   ORCID: orcid.org/0000-0001-8012-0114 1 , 9   na1  

Nature Communications volume  15 , Article number:  7529 ( 2024 ) Cite this article

Metrics details

• Evolutionary ecology
• Ichthyology
• Palaeontology

The living coelacanth Latimeria (Sarcopterygii: Actinistia) is an iconic, so-called ‘living fossil’ within one of the most apparently morphologically conservative vertebrate groups. We describe a new, 3-D preserved coelacanth from the Late Devonian Gogo Formation in Western Australia. We assemble a comprehensive analysis of the group to assess the phylogeny, evolutionary rates, and morphological disparity of all coelacanths. We reveal a major shift in morphological disparity between Devonian and post-Devonian coelacanths. The newly described fossil fish fills a critical transitional stage in coelacanth disparity and evolution. Since the mid-Cretaceous, discrete character changes (representing major morphological innovations) have essentially ceased, while meristic and continuous characters have continued to evolve within coelacanths. Considering a range of putative environmental drivers, tectonic activity best explains variation in the rates of coelacanth evolution.

Introduction

Coelacanths are evolutionarily unique, lobe-finned fishes that first appeared in the fossil record in the Lower Devonian Period (late Lochkovian, ~ 419–411 million years ago [Ma]) 1 , with over 175 fossil taxa described throughout the Palaeozoic and Mesozoic eras. Since the discovery of Latimeria chalumnae by Western scientists in 1938, the phylogenetic relationships among coelacanths have been investigated in more than 20 studies (see Supplementary Text for full list). In most analyses, a good congruence exists between the phylogeny and the stratigraphic record. Coelacanths are considered to be morphologically conservative in terms of body plan 2 , 3 , 4 , 5 , 6 , 7 and they achieved a peak of diversity during the Triassic 6 , 8 , 9 , 10 , 11 . Meanwhile, rates of morphological evolution have been examined stratophenetically 12 and phylogenetically 3 , 9 , 13 , indicating that there was an early burst of evolution during the Devonian followed by a precipitous decrease and then a steady, low rate of morphological evolution. However, no driver has ever been proposed to explain these distinctive evolutionary dynamics of coelacanths, nor has their status as ‘living fossils’ been quantitatively evaluated.

Devonian coelacanth material is rare, representing only a small component of the ~175 fossil coelacanth species—there are only 20 known taxa, about half of which are too incomplete to describe formally. Their earliest fossils (Early Devonian) are known from mostly isolated bones from the late Lochkovian and Pragian of China 1 , 14 and the mid–late Pragian of Australia 15 . Most Devonian coelacanths are rare and fragmentary, except for the middle Frasnian Miguashaia bureaui from eastern Canada 16 , 17 , and the late Famennian Serenichthys kowiensis 18 based on juvenile specimens from South Africa. Until now, Diplocercides kayseri 19 from Gerolstein in Germany is the only Devonian coelacanth known from three dimensions (3-D) and revealing part of the neurocranium, but it has since been destroyed by serial grinding.

The material presented here, comprising two specimens (Fig.  1 ), represents the first-known coelacanth from the Late Devonian Gogo Formation of Australia 20 , 21 , 22 , 23 , 24 , 25 . Exceptional 3-D preservation of our specimens facilitates rare insight into the neurocranial, branchial, and palaeoneurological conditions of the group. These data also allow us to re-evaluate the phylogeny and phenotypic evolution of all coelacanths in detail, using an expanded character matrix, as well as the first geometric morphometric study of the group to our knowledge, and an analysis of putative drivers of evolutionary rates. Along with this description, such an expansive time series of detailed evolutionary patterns for a single taxon extending right up to the present offers an opportunity to determine the global processes steering evolution more generally.

A, B ‘Part a’ of WAM 09.6.148 (holotype) shown in left dorsolateral view and skull close up in left lateral view. C ‘Part b’ of WAM 09.6.148 (holotype) showing all exposed elements; D partial braincase of NMV P231504 (paratype) shown in right lateral view; E cleithrum of NMV P231504 (paratype) in mesial and lateral view; F , G skull reconstruction in dorsal and left lateral view. Abbreviations: Ang angular, Cl cleithrum, Clv clavicle, Dt dentary, Exc extracleithrum, icj intracranial joint, ioc infraorbital canal, L.Gu lateral gular, Lj lachrymojugal, mc mandibular canal, L.Ex lateral extrascapular, Op operculum, Par Parietal, Po postorbital, Pop preoperculum, Pp postparietal, Pmx premaxilla, Psym parasymphysial, Q quadrate, Ro.p1 anterior pore of the rostral organ, Ro.p2 antero-lateral pore of the rostral organ, Ro.p3 postero-lateral pore of the rostral organ, So supraorbitals, soc supraorbital canal, Sop Suboperculum, Spl splenial, Sq squamosal.

Systematic palaeontology

Osteichthyes Huxley 1880

Sarcopterygii Romer 1955

Actinistia Cope 1871

Ngamugawi wirngarri gen. et sp. nov.

Generic name meaning “ancient fish” in Gooniyandi/Guniyandi, language of the First Nations people from Country around Fitzroy Crossing in the Kimberley region of Western Australia. Specific name is given in honour of respected Gooniyandi elder and ancestor Wirngarri, who lived in the Emanuel Range. Generic and specific names were both provided to Prof. John Long in September 2023, who has a longstanding and ongoing relationship with the community, with permissions to use the language granted by elder Rosemary Nuggett, on behalf of the Gooniyandi people of the Mimbi community.

The holotype (WAM 09.6.148; Figs.  1 , 2 ) is a small but mostly complete skull (measuring just over 2 cm in length) with all dermal skull bones, an intact neurocranium, gill-arch skeleton, and pectoral girdle preserved in close articulation. The anterior section of the body is also present comprising many scales and vertebral arch elements, but the pectoral fin and its endoskeleton are missing.

A–D ‘Part a’ of WAM 09.6.148 (holotype) shown in two views; E–G cranial endocast reconstruction from WAM 09.6.148 in dorsal, ventral and left lateral view; H – J partial braincase of NMV P231504 (paratype) shown in left lateral, posterior and ventral views; K–N left mandible of WAM 09.6.148 (holotype) shown in left lateral, medial/mesial, dorsal and ventral views. Abbreviations: Ang Angular, ant.scc anterior semicircular canal, Bb basibranchial, Bpt Basipterygoid process, Cb ceratobranchial Cor coronoids, Dt dentary, end canals for endolymphatic ducts, Enpt entopterygoid EthSph ethmosphenoid, hf hypophysis, ica canal for internal carotid artery, lat.scc lateral semicircular canal, L.Gu lateral gular, Lj lachrymojugal, n.I-VII cranial nerves I to VII, Mand mandible, nc nasal capsule, nc notochordal canal, Op operculum, OtOcc otico-occipital, Pa parietal, Po postorbital, Pop preoperculum, Pp postparietal, post.scc posterior semicircular canal, PQ palatoquadrate, pr.a antotic process, pr.c processes connectens, Psph parasphenoid, Psym parasymphysial, pv canal for pituitary vein, ro rostral organ, sacc sacculus, Spl Splenial, Sq squamosal, soph canal for superficial ophthalmic nerve. All CT data and models are available via:  www.morphosource.org/projects/000485769?locale=en .

Referred material

The paratype (NMV P231504; Figs.  1 , 2 ) contains associated elements comprising two cleithra, the ventral portion of the basisphenoid and parasphenoid, and several isolated scales.

Locality and horizon

Canning Basin, in northern Western Australia, circa 100 km southeast of Fitzroy Crossing; Gogo Formation, early Frasnian, Late Devonian (~384–382 Ma). The holotype was found between Stromatoporoid Camp and Longs Well, the paratype was found in Paddys Valley (see map of Gogo fossil localities in figure 1 within ref. 23 ).

Ngamugawi wirngarri gen. et sp. nov. is distinguished from all other coelacanths by the following apomorphies: jugal canal with prominent branches; large sensory pore openings between supraorbitals and parietals; teeth on parasymphysial tooth plate, but not on the dentary; prearticular and/or coronoid teeth rounded; cleithra and extracleithra with broad triangular anteroventral overlap for clavicle bearing a large ventral foramen; and scales with long ornamental ridges extending beyond the posterior margin of the base (Figs.  1 , 2 , Supplementary Fig.  1 ).

This published work and the nomenclatural acts it contains have been registered in ZooBank, the proposed online registration system for the International Code of Zoological Nomenclature (ICZN). The ZooBank LSIDs (Life Science Identifiers) can be resolved and the associated information viewed through any standard web browser by appending the LSID to the prefix “ http://zoobank.org/ ”. The LSIDs for this publication are: B2B4AA94-E9A5-4D05-9724-CBE5B54760EA; 567A96D6-654A-4201-BFDB-0D81BBBF6226.

Description

The holotype (WAM 09.6.148) was fossilised in an inter-reef palaeoenvironment with the dorsal surface of the skull roof in contact with the substrate, so that during decay the lower jaws and some cheek elements disarticulated, resting anterior to the skull, while the snout has collapsed inwards. The main block (part A) contains the complete skull including neurocranium, left mandible, cheek, pectoral girdle, and branchial elements, while the counterpart (block B) includes the parasphenoid and right-side mandibular ramus, operculum, entopterygoid, as well as a complete set of branchial arches. The specimen lacks the posterior portion of the body.

The well-preserved skull roof is ornamented with enamel-capped tubercles. The well-developed dorsal lamina of the premaxilla is pierced by a single large opening for the anterior tube of the rostral organ, which is diagnostic for coelacanths. There are paired parietals and postparietals partially fused in their anterior half, preparietals, and no pineal opening (Figs.  1 , 2 ). The parietals and postparietals are approximately equidimensional in length each about 10 mm long (parietal length ÷ postparietal length = 0.8252; mean = 0.7824, n  = 47 coelacanth species). The parietal/postparietal ratio varies greatly among Devonian coelacanths: ranging from 0.38 for Diplocercides kayseri 26 , 0.51 for Serenichthys kowiensis 18 , to 0.70 for Miguashaia bureaui 17 . The preorbital, orbital, and postorbital regions of the ethmoidal shield (parietonasal shield) make up 48%, 34%, and 18% of the total length of the shield, respectively, consistent with the proportions of “anatomically modern coelacanths” sensu Zhu et al. 14 with elongate preorbital and orbital regions. There are six or seven supraorbitals preserved as in D. kayseri 26 ; the posteriormost supraorbital corresponds most likely to a fusion of two or three elements. The supraorbital sensory canal passes through the sutures between the supraorbitals and the parietals, with 7–8 large pores opening through the skull roof highlighting its lyre-shaped course (Fig.  1 ). Narrow tabulars are fused to the postparietals.

Similar to other Devonian coelacanths (e.g., Gavinia, Miguashaia, Diplocercides ), the cheek region of Ngamugawi is long compared to post-Devonian coelacanths. The postorbital, squamosal, preopercular, and lachrymojugal bones are arranged as in D. kayseri 9 , 27 and Serenichthys 18 in having the squamosal and preoperculum set atop one another, the postorbital farther anteriorly, and an elbow-shaped lachrymojugal expanded ventrally and bearing large, medial sensory pores as in D. kayseri . The sub-oval postorbital has a short orbital margin and bears six infraorbital sensory canal pores. Unlike the condition in Serenichthys, Gavinia , and post-Devonian coelacanths, whereby the postorbital anterior margin is long and curved to fit behind the orbit, in Ngamugawi the orbital margin is short as in D. heiligenstockiensis 27 and M. bureaui 17 . The squamosal is sub-triangular and bears a vertical cheek pit line posteroventrally, and pores for the jugal and preopercular sensory canals. The preoperculum is trapezoidal, with four or five large pores of the preopercular canal, and abuts the squamosal ventrally, yet is separated from the lachrymojugal. The operculum bears a distinctive, strong ridge running anteroposteriorly through the bone, with a series of associated foramina likely to be the “epibranchial line” of Northcutt 28 as in M. bureaui 17 .

The lower jaw of Ngamugawi is distinctive, with a long dentary (40% of the mandible length), a long splenial, a unique arrangement of coronoids, and lacking a dentary sensory pore (Fig.  2K–N ). The dentary is unusually long compared to most other coelacanths (35% of the mandible length), but similar to the proportion of the dentary observed in the most primitive coelacanth Styloichthys (50%) as well as some Carboniferous taxa (e.g., Rhabdoderma elegans 40%; Caridosuctor populosum 43%; Allenypterus montanus 42%). Unique among coelacanths, Ngamugawi has a large, denticulated (not ‘toothed’, nor bearing ‘pointed teeth’) bone sutured medially to the dentary, which we interpret as a parasymphysial bone (Fig.  1G ). Enlarged parasymphysials are also found in onychodontids and porolepiforms, so we propose that the specific position and elongation of this bone is a sarcopterygian synapomophy. There are three equidimensional coronoids, and an additional, enlarged principal coronoid. The angular bears an oral pit-line in its anterior half and some large sensory pores along its ventral margin. The prearticular bone lacks elongate ridges in its ventral portion. The glenoid fossa has a single posterodorsally facing facet, and the Meckelian bone bears an articulation point for the symplectic posteriorly. The left lateral gular is long and flat, only slightly shorter than the mandible as in most coelacanths. It has a small pit-line located posterior to the centre of the bone as in D. heiligenstockensis 29 and Chagrinia enodis 30 .

The braincase of Ngamugawi is exceptionally well-preserved in 3-D (Figs.  1 B, D, 2A–D , H–J), and is the best-preserved braincase known for a Palaeozoic coelacanth. Much of the braincase is well-ossified, preserving most of the ethmosphenoid and otico-occipital, with the unossified areas of the braincase where cartilage prevailed precisely matching the same regions of cartilage formation in Latimeria 31 . The braincase, cranial endocast, and palate bears many similarities to that of D. kayseri 32 . The interorbital cartilage is ossified. The processus connectens extends to the level of the antotic process and does not meet the parasphenoid. The antotic processes are large and teardrop-shaped, whereas the basipterygoid processes are smaller and knob-like. The occipital area appears to have been less-ossified than more anterior portions and might have been cartilaginous as in Latimeria 33 . The posterolateral wall of the otico-occipital bears a distinct, short otic process not seen in any other coelacanth, nor sarcopterygian. Two endolymphatic ducts face dorsally, opening through the endoskeletal cranial roof (Fig.  2E ). The parasphenoid forms an elongate ‘spatulate’ outline as in Diplocercides 17 , 34 , with a gently rounded anterior margin and covered in a denticle field that ends abruptly posterior to the internal carotid foramen (Supplementary Fig.  2E–H ). The parasphenoid is medially concave with an open buccohypophyseal canal. The entopterygoids are sub-triangular with a broad posterior flange as in other coelacanths. They are smooth laterally but ridged across most of their palatal surface.

The nasal capsules are shallow and rounded, situated in line with the cranial cavity as in many sarcopterygians (contra Latimeria ). The general proportions of the rostral organ can be reconstructed from the position of the pore openings and by comparison with that of Latimeria 33 (Fig.  2E–G ). The olfactory tracts seemingly travelled through the large common anterior section of the endocranial cavity, rather than via separate olfactory tracts as in dipnomorphs and tetrapodomorphs. Canals for the optic nerves (n.II), oculomotor nerves (n.III), and trochlear nerves (n.IV) all exit the cranial cavity laterally. Those of the trochlear nerves travel just over a millimetre anterolaterally before meeting the superficial ophthalmic canals. The hypophysial fossa is short compared to that of juvenile and adult Latimeria specimens 33 . It extends anteroventrally as in that taxon but lacks an obvious posterior lobe as in Diplocercides kayseri 32 . There is no evidence of pineal or parapineal recesses. The endocast is narrow in the ethmosphenoid region but broadens from the level of the intracranial joint to reach its maximum width anterior to the labyrinths (Fig.  2E–G ). Posterior to this, a large canal for the facial nerve (n.VII) exits the braincase laterally before splitting into three branches, and a canal for the auditory nerve (n.VIII) leads into the labyrinths.

The inner-ear region and the posterior portion of the endocast are more poorly ossified and were likely cartilaginous as in Latimeria 33 . Two long, open endolymphatic ducts are situated at the posterior of the skull roof. Anterior and posterior semicircular canals are preserved on the right-hand side of the specimen, and portions of the external semicircular canal and the sacculus are preserved on the left (Fig.  2E–G ). The labyrinth region shows a large ampulla on the anterior semicircular canal, but the condition for the other two is unknown. The sacculus appears to have been large and deep as in Diplocercides , with the sinus superior not projecting above the cranial cavity dorsally.

Ngamugawi contains the best-preserved visceral skeleton of any Palaeozoic coelacanth (Supplementary Fig.  1G, H ). While most of the visceral skeleton is preserved as a thin, ossified perichondral layer, we note an ossified hyomandibular is absent; we consider this due to it being cartilaginous as in Latimeria . The anterior end of the urohyal forms a single point, but the posterior bifurcation of the urohyal is pronounced as in most coelacanths. The single basibranchial has parallel lateral margins, and the ceratohyal is long and narrow. Five ceratobranchials are strongly curved and expanded proximally, while the epibranchials are triradiate, rod-like elements similar to those of Latimeria chalumnae .

Within the pectoral girdle, the cleithrum, extracleithrum, and clavicle form a prominent postbranchial lamina (Fig.  1E, G ; Supplementary Fig.  1I ). The cleithra are rounded dorsally, bear a ridged ornament, have a distinct anterior grove for the articulation of the operculum, and are partially fused with the broad extracleithrum (a synapomorphy of coelacanths). There is a broad, triangular anteroventral overlap between the extracleithrum and the clavicle. A large foramen lies on the visceral surface on the smooth overlap area for the clavicle lateral surface. The triangular clavicle is short as in Miguashaia . The sigmoid anocleithrum bears no ornament and has an anteriorly-pointed tip with an articular facet.

The scales are either teardrop-shaped, similar to Lualabaea or Caridosuctor 35 , or ovate, with a longitudinal, ridged enamel ornament. The spiny apices of the thicker ridges protrude from the posterior margin of the scales (Supplementary Fig.  1D ); this feature seems to be unique to Ngamugawi among coelacanths. Lateral line scales have large pore openings. There are no bumps on the inner surface of the scales as for Miguashaia 17 , 35 .

Although the two specimens are small, they likely represent adults based on the presence of many fusions between bones, the degree of ossification of the branchial elements, and the degree of development of the scales.

Phylogenetic and Evolutionary Analyses

First, we evaluated the phylogenetic position of Ngamugawi wirngarri gen. et sp. nov. via Bayesian inference and maximum parsimony using an exhaustive and greatly expanded data matrix of 87 species (82 coelacanths and 5 onychodontiform outgroups) coded for 322 total characters (268 discrete, 14 meristic, and 40 continuous — see Supplementary Text for detailed description of all characters and analyses and Supplementary Fig.  3 for the position of the 88 landmarks for the 40 continuous characters). These matrices combine characters from 16 previous analyses including Forey’s 9 classic matrix (some original characters have been deleted, split, or redefined; Forey’s matrix has been used in 20 analyses so far), in addition to 85 new characters. Autapomorphies (unique characters of terminal taxa) have been scored and coded. We double-checked all characters for each taxon, validating or invalidating previous coding. Both Bayesian inference (Fig.  3 ) and maximum parsimony (Supplementary Fig.  6 ) recover broadly congruent topologies: Ngamugawi is recovered as sister taxon to Gavinia , crownward of Miguashaia spp. and Holopterygius , and basal to Diplocercides and Serenichthys. Styloichthys is sister taxon to all other coelacanths.

Ngamugawi wirngarri gen. et sp. nov., shown in enlarged black text. Each branch is coloured according to median rate of morphological evolution of discrete characters under the uncorrelated lognormal relaxed clock (details in Fig.  4 ). Numbers at branches refer to posterior probability. Identification of, and credit for, the coelacanth silhouettes is provided in Supplementary Fig.  4 .

Bayesian tip-dating revealed a striking uncoupling between rates of evolution of discrete, meristic, and continuous character types. The uncorrelated log-normal clock (which allowed all branches to have separate rates: Fig.  4 ) and the epoch clock (which constrained rates to be the same within time slices: Supplementary Fig.  6 ) retrieved similar patterns. We found that coelacanths experienced a rapid burst of morphological evolution with the highest rates occurring early in their history during the Devonian Period, but these rates then slowed substantially (with rare exceptions). Discrete characters, which often reflect evolutionary innovations, virtually stopped evolving after the Cretaceous (Fig.  4D ); the substitution tree reveals Latimeria has undergone no more anagenesis than Cretaceous relatives, i.e. for discrete characters, it has indeed been frozen in evolutionary time. In contrast, meristic and continuous characters, which often reflect changes in proportions, have continued to evolve at typical Mesozoic rates (Fig.  4E-F ). There are other instances of uncoupled rates of evolution for different character types: Holopterygius and Allenypterus exhibit fast rates for continuous and meristic changes, but unremarkable rates for discrete characters. These are explicable, e.g., Holopterygius and Allenypterus are unusually shaped coelacanths, but have retained most typical coelacanth traits.

Rates of evolution through time for A discrete, B meristic, and C continuous characters; each plot shows the duration and rate for every branch in the MCMC tree sample. Median rates for each branch for D discrete, E meristic, and F continuous characters; taxon labels for trees are as in Fig.  3 . Due to constraints in BEAST2, absolute rates of change are shown for discrete characters, but relative rates (weighted average =1) shown for meristic and continuous characters. In A – C , fuzzy plots depict branch rates in 1000 MCMC tree samples (8000 post-burnin trees, thinned by factor of 8); box and whisker plots depict interquartile (50%) and range for the average rate in each sample for the relevant geological period. In D – F , branch rates are median rates for 8000 post-burnin trees.

Next, we constructed a resampled boosted regression tree analysis to identify the relative contribution of five putative palaeoenvironmental drivers to rates of coelacanth evolution: namely, subduction flux; continental flooded area (incorporating percentage of shallow sea); sea surface temperature; atmospheric CO 2 ; and dissolved O 2 , (see Supplementary Information  3a ) (Fig.  5 ). We used a combined rate of evolution, considering the discrete, meristic, and continuous characters, for each species (i.e., the rate associated exclusively to the species on the leading phylogenetic branch). The resampled final trees had high coefficients of variation (a measure of goodness of fit) ranging from 48% to 91%. Of the putative environmental drivers considered, the influence of subduction flux (a proxy of tectonic activity) was the most strongly associated environmental measure to the rate of evolution (median relative influence = 36%; range = 13–60%) — thus, indicating that coelacanth species evolved more rapidly during periods of higher global tectonic activity (Fig.  5B ), suggesting that the creation of new habitats favoured rapid morphological evolution. The percentage of continental flooded area (Fig.  5C ) had the next-highest explanatory power, albeit considerably lower than subduction flux (median relative influence = 24%; range = 2–46%). There was little support for a relationship between the remaining environmental drivers (atmospheric CO 2 , sea surface temperature, dissolved O 2 ) and the rate of coelacanth evolution (Fig.  5 ).

A Scaled and centred rate of evolution of all coelacanths, B subduction flux; C continental flooded area (incorporating % shallow seas), D sea surface temperature; E atmospheric CO 2 concentration, F dissolved (marine) O 2 , and G relative influence of each environmental driver on rate of coelacanth evolution. x -axis error bars in A-F are standard errors derived from the source literature, y -axis error bars are 95% confidence limits; error bars in G represent 95% confidence limits and are derived from 1000 iterations of the boosted regression tree analysis. Green = Palaeozoic, blue = Mesozoic, yellow = Cenozoic.

Lastly, we evaluated disparity of coelacanth morphology using two approaches: ( i ) principal coordinates analysis (PCoA) applied to the discrete phylogenetic matrix (with missing data for each coelacanth species reconstructed using parsimony), and ( ii ) principal component analysis (PCA) of the 2-D geometric morphometrics to analyse shape of the body, lower jaw, and cheek (Fig.  6 ; Supplementary Fig.  7 ). Variation in body shape and lower jaw are conservative 2 , 3 , 9 , while the cheek region is more variable among species (or disparate) 3 , 9 , 36 .

A Principal coordinates analysis plot showing principal coordinate 1 versus principal coordinate 2, disparity based on discrete characters for all coelacanth taxa ( n  = 82 species). B–D Principal component analysis plot showing principal component 1 versus principal component 2 disparity based on 2-D geometric morphometrics for B body shape ( n  = 35 species); C cheek bones ( n  = 34 species); and D lower jaw shape ( n  = 38 species). Time-binned morphospaces per geological period compare the distinctiveness, similarity, and temporal evolution of the morphological disparity of coelacanths over a period of 410 Ma. Larger morphospaces indicate greater morphological disparity; overlapping morphospaces indicate similar body plans. There are distinct morphospaces for Devonian and post-Devonian coelacanths. Latimeria falls close to its closest, Mesozoic relatives for discrete characters ( A ) and cheek shape ( C ) but is quite distantly separated from Mesozoic forms for overall body shape ( B ) and lower jaw shape ( D ). All individual species data points plotted and identified in Supplementary Fig.  8 . Identification of coelacanth silhouettes is provided in Supplementary Fig.  4 (complete body) and Fig. 11 (cheek region and lower jaw).

For the principal coordinates analysis of discrete characters, we recovered a profound shift in overall disparity between Devonian and all post-Devonian coelacanths, but the highest disparity (discrete) during the Devonian and Triassic (Fig.  6A ; Supplementary Fig.  8  A). Again, Latimeria appears to have moved little outside the morphospace of its closest Mesozoic relatives, despite having an additional 66 million years to evolve, consistent with the stasis for discrete characters found in the tip-dated phylogenetic analyses.

For the principal component analysis of overall body shape (Fig.  6B ; Supplementary Fig.  8B ), the Devonian Miguashaia bureaui , the Carboniferous Allenypterus montanus , and the Triassic Foreyia maxkuhni are three outliers highly modified in body shape compared to the generalised coelacanth body type, accounting for approximately 35% of the total variation. A second source of body-shape variation considers the discrepancies associated with the heterocercal and triphycercal caudal fins (Supplementary Fig.  9A ). A major shift of disparity occurred between Devonian and post-Devonian species. Latimeria is positioned away from its closest Mesozoic relatives, again consistent with the lack of stasis found for continuous (shape) characters in the tip-dated phylogenetic analyses. The disparity in the cheek region offers a distinct pattern of temporal evolutionary disparity. Two temporal shifts characterized the cheek disparity (Fig.  6C ; Supplementary Fig.  8C ): one post-Devonian (narrowing of the cheek, Supplementary Fig.  9B ) and the second between the Triassic and Jurassic (deepening of the cheek, Supplementary Fig.  9B ). The disparity of the cheek region is greater than that of body shape and lower jaw, while the disparity of the lower jaw is slightly greater than that of the body shape and shows a relatively constant temporal overlap (Fig.  6D , Supplementary Fig.  10 ).

Ngamugawi shows characteristics intermediate between ‘anatomically primitive’ (e.g., Styloichthys , Miguashaia ) and ‘anatomically modern’ (e.g., Diplocercides , Euporosteus , and post-Devonian species) coelacanths sensu Zhu et al. 14 , both in its phylogenetic position and morphological disparity. Phylogenetically, Ngamugawi is closely related to another Australian Devonian coelacanth — Gavinia — both are basal to Diplocercides and Serenichthys , and post-Devonian coelacanths. Anatomically modern coelacanths were thought to be characterized by two pairs of parietals (i.e., one pair of parietals and one pair of preparietals), enlarged preorbital and orbital regions of the ethmosphenoid shield (~40% preorbital, 50% orbital, and 10% postorbital regions), and a trilobate tail (i.e., triphycercal caudal fin) 14 , features absent in ‘anatomically primitive’ forms. Ngamugawi bears one pair of parietals and preparietals, but the proportions of the three ethmosphenoid regions are intermediate between the so-called ‘primitive’ and ‘modern’ coelacanths (48%, 34%, and 18%). Furthermore, Miguashaia bureaui was considered anatomically primitive 14 , due to features inferred in its reconstruction 17 , such as the presence of a heterocercal caudal fin and the proportions of the ethmosphenoid shield (34%, 21%, and 45%). However, new M. bureaui material shows an ethmosphenoid condition more intermediate between ‘anatomically primitive’ and ‘modern’ coelacanths (51%, 30%, and 19%). Thus, the gap between ‘anatomically primitive’ and ‘anatomically modern’ coelacanths is now bridged, leaving only Styloichthys discriminated from all remaining coelacanths. Ngamugawi was crucial to this interpretation, and thus holds a key position in the early evolution of coelacanths (with most other taxa in this region of the tree being poorly known). The undistorted, 3-D-preserved neurocranium of Ngamugawi wirngarri thus provides valuable insight into the neurobiological evolution of early coelacanths more generally.

The detailed analyses of evolutionary rates also substantiate the ‘living fossil’ status of Latimeria , but with important nuances. After the Mesozoic, there was a sharp decline in rates of evolution of discrete characters, but rates in meristic and continuous (i.e., shape) traits have not declined; these patterns are also reflected in the morphospace analyses of discrete characters and body shape. Discrete characters often refer to evolutionary innovations, such as the presence or absence of novel structures that are difficult to encapsulate as meristic or continuous traits. In contrast, meristic and continuous characters typically refer to more subtle evolutionary changes in proportions. Thus, a biological interpretation of the rate results is that, since the Cretaceous, coelacanths have largely ceased evolving major innovations (discrete characters), yet finer-scale tinkering (meristic and continuous characters) has continued unabated, as indeed has genomic evolution 37 , 38 . Hence, coelacanths might indeed be considered living fossils due to their lack of major recent innovations, but in more subtle features and their DNA 38 , they have continued to evolve at more normal rates for vertebrates. Although slowly evolving organisms, higher rates of global tectonic activity appear to have been one of the main putative abiotic drivers of faster rates of morphological evolution in coelacanths by facilitating episodes of biogeographic differentiation.

Both specimens were collected during the 2008 Museum Victoria Gogo Expedition led by JAL and funded by the Australian Research Council. Landowners and leaseholders gave permission to do field work, and no additional permits were required under the Lands Administration Act. The specimens are registered in the collections of the Western Australian Museum as WAM 09.6.148 (holotype) and Museum Victoria as NMV P231504 (paratype). David Pickering and John A. Long (MV) extracted the specimens from their limestone matrix using repeated 10% acetic acid baths, with newly exposed bones strengthened with Paraloid/Mowital B30 in ethanol. JAL dusted specimens with a sublimate of ammonium chloride prior to photography and drew illustrations using a camera lucida.

Computed tomography

We were granted permission to CT scan the material by Rosemary Nuggett, on behalf of the Gooniyandi people of the Mimbi community, and Mikael Siversson of the Western Australian Museum. We imaged part and counterpart (parts A & B) of the holotype WAM 09.6.148 at the Australian National University (ANU) X-ray Micro-CT Laboratory. Later, we (re)imaged the holotype (part A) and the paratype MV P231504 at the Adelaide Microscopy CT Facility (University of Adelaide) on a Skyscan1076 X-ray microtomography scanner using the following parameters: holotype, 74 kV; 135 μA; 0.5 mm aluminium (Al) filter; 360° rotation at 0.4° increments; frame averaging = 2; 2.4 second acquisition time; and paratype, 100 kV; 70 μA; 1.0 mm aluminium (Al) filter; 360° rotation at 0.4° increments; 3 frames/rotation; 4.1 second acquisition time. The resultant pixel size for the initial holotype scan was 150 μm, the paratype was 9 μm, and the holotype (part a) rescan was 17 μm. We reconstructed the resultant 16-bit depth TIFF images using the Skyscan NRecon software (Bruker microCT, Belgium), after which we completed 3-D segmentation and rendering using Mimics v.19.0 (biomedical.materialise.com/mimics; Materialise, Leuven, Belgium). Skull reconstruction was done in 3-matic (Materialise, Leuven, Belgium), and animations assembled using Adobe Premier Pro. Scan data and all resulting 3-D models (STLs) and animations are available via MorphoSource ( www.morphosource.org/projects/000485769?locale=en ), as well as the Github repository github.com/cjabradshaw/CoelacanthEvolution/ .

Phylogenetic analyses

To assess the phylogeny, we compiled three phylogenetic matrices for 82 coelacanth species and five onychodontiform outgroups containing 268 discrete, 14 meristic, and 40 continuous characters (see Supplementary Information for detailed description of all characters). Detailed description of the characters, states, scores and sources is provided in the supplementary information. We applied Bayesian (BEAST2) and maximum parsimony analyses (TNT) to create a newly proposed phylogeny. The discrete matrix is available on MorphoBank (Project 3471), the meristic and continuous characters are available at https://doi.org/10.5281/zenodo.8054092 .

Bayesian tip-dated analyses

We were performed Bayesian tip-dated analyses using BEAST 1.10.5 39 (BEAST2 currently cannot accommodate continuous traits with missing data). The data were explicitly gathered to satisfy the assumptions of tip dating, namely sampling all variable traits, including autapomorphies (see Supplementary Information). The most appropriate available tree prior was the birth-death serial-sampling model (BDSS 40 ); the alternative SABD tree prior is only available in BEAST2 41 . The optimal evolutionary histories that explain the discrete, meristic and continuous traits, as well as stratigraphic dates, were inferred using Markov-chain Monte Carlo (MCMC) approaches, as implemented in BEAST. The executable XML files, with annotations describing model, prior, MCMC run and logging settings, and R scripts, are available in Github https://github.com/cjabradshaw/CoelacanthEvolution . Four runs of all analyses were conducted, with run lengths and burnin confirmed as adequate for convergence using Tracer 42 ; the post-burnin samples of all 4 runs were then combined and summarised using post-processing BEAST modules LogCombiner and TreeAnnotator 43 as well as R scripts available in scripts/evolrate using libraries disparity 44 , phytools 45 , phylotate 46 and geoscale 47 .

Tip calibrations were employed using the full stratigraphic range (including uncertainty) for each species; taxa from the same deposit were constrained to co-vary in age by putting a tight (exponential) prior on their age variance ( cf   48 ). The maximum root age was unconstrained, but there was an exponential prior putting 95% of probability distribution between the oldest sampled fossil (412.15 Ma) and the oldest unequivocal sarcopterygians (418 Ma). Trees were rooted with five onychodontiform outgroup taxa.

Discrete morphological characters were analyzed using the Mkv-model which corrects for non-sampling of constant characters 49 . Multistate characters that formed clear morphoclines (characters 1, 2, 6, 8, 10, 15-16, 23, 26, 36, 53, 60, 74, 76, 97, 100, 110, 112, 135, 137, 208, 218, 224, 227, 240, and 258) were treated as ordered; others were treated as unordered. Among-character rate variation was modelled using the gamma parameter 50 . A state-partitioned model was employed, with substitution rates scaled by state number to correct for state ( = base) frequencies (see King et al. 51 ).

Meristic characters were analyzed using a high-state ordered Mk-model. Essentially, meristic characters were treated as ordered multistate characters with very large numbers of states, the possible states being the minimum observed value, the maximum observed value, and all intervening whole numbers. Changes between any two states were constrained to pass through all intervening values (states). The large number of states for some characters required the use of unorthodox state labels, which are detailed in the Supplementary Information .

Continuous characters were log-transformed (to base 10) to reduce heteroscedasticity where relevant (highly right-skewed). The transformed data were then analysed using Brownian motion models implemented in BEAST 52 , with the average evolutionary rate (i.e., variance) for each continuous character estimated separately.

Rate variation across the tree was modelled using two different clock models; in the main analyses, rate variation was estimated separately for the discrete, meristic and continuous characters to test for concordance in patterns.

Uncorrelated lognormal (UCLN) relaxed clock

This clock model assumes rates vary independently across branches, with the values approximating a lognormal distribution with variance estimated from the data 53 . To achieve convergence, these analyses had to be performed using MC3 methods (4 chains, delta 0.08). The dated tree from this clock model is shown in Fig.  3 , along with the estimated rates of discrete, meristic and continuous characters across time (in Fig.  4 and Supplementary Fig.  5 ).

For testing correlates of evolutionary rates, where it was desirable to have a single rate value for all 3 types of traits, the UCLN relaxed clock analysis was repeated with discrete, meristic and continuous data modelled under a single (i.e., linked) clock.

Epoch clock

This clock model assumes rates vary independently across time slices, but rates in all branches within each time slice are the same 54 . Branches spanning multiple time slices are allocated multiple rates (i.e., the segment of branch within time slice a is allocated the rate for time slice a , etc.). Seven epochs were employed: Devonian (and earlier), Carboniferous, Permian, Triassic, Jurassic, Cretaceous, and Tertiary. The rates of evolution for discrete, meristic, and continuous characters across the seven epochs is shown in Supplementary Fig.  5 .

Parsimony analyses

Parsimony analyses used TNT 55 included the discrete, meristic and continuous characters (scaled to the same weight as binary characters), with outgroup and ordering assumptions as above. In order to remove negative log values (unreadable by TNT), all continuous characters had +2 added; the magnitude of the addition makes no difference under parsimony. Searches involved 1000 TBR replicates holding 100000 trees at each step. The strict consensus tree was calculated for all taxa, and with the three most unstable taxa pruned 56 (Supplementary Fig.  6 ). Clade support was calculated using 200 bootstrap replicates. The executable TNT files are in Github at https://doi.org/10.5281/zenodo.8054092 .

Boosted regression trees

We also built boosted-regression trees to test the relationship between rate of coelacanth evolution and five putative environmental drivers, namely subduction flux 57 , continental flooded area (combined with percentage of shallow seas) 58 , 59 , sea surface temperature 57 , dissolved O 2 60 atmospheric CO 2 61 (see Supplementary Information for data collection for these parameters) to account for potential nonlinearity in the relationships. We hypothesised that the rate of evolution would increase within relatively higher concentrations of dissolved O 2 given its suggested role in the evolution of animal life during the Phanerozoic 62 (but see Schachat 63 , 64 ). We further hypothesised that variation in atmospheric CO 2 might have influence coelacanth evolution given its role in modifying climate 65 and the flow of trophic energy through ecological networks 66 . We predicted that relatively higher sea surface temperatures would indicate higher rates of coelacanth evolution given the positive influence of temperature on poikilotherm metabolism 67 . Finally, we predicted that increasing subduction flux 57 , a measure of relative tectonic activity, would facilitate episodes of biogeographic differentiation and influence patterns of speciation 65 , 68 through the exploitation of novel niches, and that a higher percentage of shallow seas globally would provide more opportunity for evolution since most coelacanth species have been discovered mainly in marine and estuarine palaeoenvironments 9 , 69 , 70 .

We also accounted for potential phylogenetic non-independence and temporal autocorrelation by resampling the dataset 1000 times using the following procedure: ( i ) we constructed a temporal vector of ages by Gaussian-resampling the mean and standard deviation of the intervals between fossil appearance periods (based on the first and last appearances) using one-third of the calculated standard deviation and removing the negative intervals; ( ii ) for each resampled temporal sequence, we determined which species appeared within the sequence points (again, based on first and last appearances), ( iii ) for each of the species within the resampled sequence, we resampled a random uniform value for each putative environmental driver between its maximum and minimum, and ( iv ) we transformed, centred, and scaled the extracted environmental values using the scale function in R. For each of these 1000 resampled datasets, we ran a boosted regression tree emulator to predict the rate of coelacanth evolution (scaled, centred, log 10 -transformed itself to produce a Gaussian-like distribution) from the scaled environmental variables using a learning rate = 0.0003, tolerance = 0.00005, error family = Gaussian, bag fraction = 0.75, tree complexity = 2, and maximum number of trees = 1,000,000 in the function gbm.step from the dismo R library 71 . For each of the 1000 iterations, we retained the coefficient of variation as a measure of goodness of fit, the relative influence of each environmental variable, and the predicted relationship between scaled rate of evolution and each scaled environmental variable, from which we estimated 95% confidence limits using the quantile function in R. However, we also applied a kappa ( κ ) limitation to the resampled selections to limit the influence of outliers 72 , where we retained only the resampled mean ranks within κσ of the overall average mean ( κ  = 2). We then recalculated the average and standard deviation of the mean rank, with the process repeated five times. All data and R code necessary to run this procedure are available at Github https://doi.org/10.5281/zenodo.8054092 .

Disparity analyses

We evaluated coelacanth morphological disparity using two approaches. ( i ) We used a matrix of discrete characters (268 characters for 82 coelacanth species excluding outgroups) to explore morphological disparity based on Gower’s coefficient 73 . We plotted the morphospaces for taxa in seven time-bins: Devonian, Carboniferous, Permian, Triassic, Jurassic, Cretaceous, and extant. The first two axes of the principal coordinates analysis explained 42.01% and 11.30% of the variation, respectively (Fig.  6A ). ( ii ) We did 2-D geometric morphometric analyses of body shape, lower jaw, and cheek region for taxa that included the relevant information. We digitized 2-D landmarks with tpsDig2 v.2.32 74 on reconstructions of coelacanths previously verified and corrected when needed. We did three separate analyses to optimize both the number of landmarks and species in each analysis. We digitized 14 2-D landmarks on 35 species to describe the lateral body outline and relative positions of the fins, 17 2-D landmarks on 34 species to capture the shape of the cheek, and seven 2-D landmarks on 38 species to describe the shape of the lower jaw (see Supplementary Information Table  2 .1 for a detailed description of the landmarks). We rotated, scaled, and translated landmark coordinates with a Procrustes superimposition using the function gpagen in the R package geomorph v.4.0.1 75 . We constructed morphospaces based on the two first axes of the principal component analyses. ( iii ) We calculated Procrustes variance for each time-bin using the function morphol.disparity in the package geomorph. All data and R code necessary to repeat disparity analyses are available at Github https://doi.org/10.5281/zenodo.8054092 .

Reporting summary

Further information on research design is available in the  Nature Portfolio Reporting Summary linked to this article.

Data availability

The CT data generated in this study have been deposited in the Morphosource database at www.morphosource.org/projects/000485769?locale=en . The phylogenetic matrix for discrete character data are available from MorphoBank (Project 3471): morphobank.org/permalink/P3471. All other data used in this study are available from the GitHub repository at https://doi.org/10.5281/zenodo.8054092 .

Code availability

All code and data are available via https://doi.org/10.5281/zenodo.8054092

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Acknowledgements

We acknowledge the Gooniyandi people and other landholders on which the Gogo fish sites are located. Members of the 2008 field team are thanked for their contribution. Tim Senden, Mike Turner (Australian National University, Australia), and Ruth Williams (Adelaide Microscopy, Australia) are thanked for performing the CT scans. Michael Siversson and Helen Ryan (Western Australian Museum) are thanked for arranging specimen access. Jenjira Prombansung, Clara Comeau, Chantal Rodrigue, and Laurent Houle (UQAR, Canada) helped with illustrations. Richard Flament and Laurianne Richard assisted with compiling coelacanth diversity data. Wen Wen provided high resolution images of specimens for scoring characters. Andrew Wendruff and Mark V.H. Wilson for the permission to use information on unpublished Whiteia coelacanths. Florian Witzmann (Museum für Naturkunde, Germany) is thanked for access to Euporosteus eifeliensis and cast material of Diplocercides kayseri . Fieldwork was funded by the Australian Research Council, with grant DP 0772138 (JAL). This work was supported by the Australian Research Council DP 220100825 (JAL, KT, AMC), DP 200103398 (JAL, AMC), DP 110101127 (JAL, KT) and DP 0772138 (JAL). Other fundings sources include Honorary Visiting Scholar at Flinders University 2019, 2023 to (RC), Visiting professor at Mahasarakham University (2023 to RC), and Natural Sciences and Engineering Research Council of Canada RGPIN−2019-06133 (RC), NERC (Natural Environment Research Council) Standard Grant NE/P013090/1 (HD), and QEII Fellowship (KT).

Author information

These authors contributed equally: Alice M. Clement, Richard Cloutier, John A. Long.

Authors and Affiliations

College of Science and Engineering, Flinders University, Adelaide, 5042, Australia

Alice M. Clement, Richard Cloutier, Michael S. Y. Lee & John A. Long

Département de Biologie, Chimie et Géographie, Université du Québec à Rimouski, Rimouski, G5L 3A1, Canada

Richard Cloutier & Olivia Vanhaesebroucke

Excellence Center in Evolution of Life, Basin Studies and Applied Paleontology,, Palaeontological Research and Education Centre, Mahasarakham University, Maha Sarakham, 44150, Thailand

Richard Cloutier

Earth Sciences Section, South Australian Museum, North Terrace, Adelaide, 5000, Australia

Michael S. Y. Lee

Max Planck Institute for Evolutionary Anthropology, Deutscher Platz 6, 04103, Leipzig, Germany

Benedict King

Global Ecology | Partuyarta Ngadluku Wardli Kuu, College of Science and Engineering, Flinders University, Adelaide, 5001, Australia

Corey J. A. Bradshaw

University of Bristol, School of Earth Sciences, Bristol, UK

School of Molecular and Life Sciences, Faculty of Science and Engineering, Curtin University, Perth, 6845, Australia

Kate Trinajstic

Earth and Planetary Sciences, Western Australian Museum, 49 Kew Street, Welshpool, 6106, Australia

Kate Trinajstic & John A. Long

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Contributions

Conceived project: A.M.C., R.C., K.T., J.A.L. Fieldwork: A.M.C., K.T., J.A.L. Specimen preparation & photography: A.M.C., K.T., J.A.L. Specimen interpretation: A.M.C., R.C., H.D., J.A.L. CT –scanning, segmentation & visualisation: A.M.C. Matrix construction: A.M.C., R.C., J.A.L. Character scoring: A.M.C., R.C., H.D., B.K., J.A.L., O.V. Analyses: R.C., M.S.Y.L., B.K., O.V., C.J.A.B. Figures: A.M.C., R.C., M.S.Y.L., B.K., J.A.L., O.V., C.J.A.B. Writing – original draft: A.M.C., R.C., J.A.L. Writing – review & editing: A.M.C., R.C., M.S.Y.L., H.D., B.K., K.T., J.A.L., O.V., C.J.A.B.

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Clement, A.M., Cloutier, R., Lee, M.S.Y. et al. A Late Devonian coelacanth reconfigures actinistian phylogeny, disparity, and evolutionary dynamics. Nat Commun 15 , 7529 (2024). https://doi.org/10.1038/s41467-024-51238-4

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