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Understanding the Societal Impact of the Social Sciences and Humanities: Remarks on Roles, Challenges, and Expectations

Benedikt fecher.

1 Research Program Knowledge and Society, Alexander von Humboldt Institute for Internet and Society, Berlin, Germany

2 German Institute for Economic Research, Berlin, Germany

Freia Kuper

Nataliia sokolovska, alex fenton.

3 Research Area Research System and Science Dynamics, German Centre for Higher Education Research and Science Studies, Berlin, Germany

4 Department of Social Sciences, Humboldt University Berlin, Berlin, Germany

Stefan Hornbostel

Gert g. wagner.

5 Max Planck Institute for Human Development, Berlin, Germany

Hanna Hottenrott , Technical University of Munich, Germany

Associated Data

The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation.

Science is increasingly expected to help in solving complex societal problems in collaboration with societal stakeholders. However, it is often unclear under what conditions this can happen, i.e., what kind of challenges occur when science interacts with society and what kind of quality expectations prevail. This is particularly pertinent for Social Sciences and Humanities (SSH), which are part of the object they study and whose knowledge is always subject to provisionality. Here we discuss how SSH researchers can contribute to societal problems, what challenges might occur when they interact with societal stakeholders, and what quality expectations arise in these arrangements. We base our argumentation on the results of an online consultation among 125 experts in Germany (representatives from SSH, learned societies, stakeholders from different societal groups, and relevant intermediaries).

Introduction

Societal impact is an increasingly important evaluation paradigm in science governance. This trend can be seen in the implementation of large-scale impact agendas in various research and innovation systems over the past decade. Examples include the Research Excellence Framework in the United Kingdom, the Standard Evaluation Protocol in Netherlands, or the Excellence in Research framework in Australia ( van der Meulen and Rip, 2000 ; Geuna and Martin, 2003 ; Bornmann, 2013 ). Consequently, research is no longer assessed according to its scientific relevance alone but also according to the value it appears to generate for society. In Germany, where the present study was conducted, the societal impact of research is also at the top of the agenda of policymakers and research funders, although under a variety of terms. The German Ministry for Education and Research, for example, argues in a policy paper that a dialogue with society must become part of the logic of scientific reputation ( BMBF, 2019 ).

This gradual evolution of societal impact as an evaluation paradigm was preceded by a shift in the scholarly conception of the relationship between science and society, which can be summarized as a shift “from deficit to dialogue” ( Bucchi, 2008 ; Davies et al., 2009 ; Reincke et al., 2020 ). According to this view, science no longer provides knowledge to resolve a deficit but should develop “socially robust knowledge” together with societal stakeholders ( Nowotny et al., 2001 ). This shift in the conception of the science-society interface implies that societal impact requires interaction between scientific and societal stakeholders. As a result, evaluation frameworks increasingly focus on processes rather than outcomes, thus rely more heavily on narratives and on formative methods more than summative ones. An example of the latter is the SIAMPI approach, which focuses on ‘productive interactions’ between science and society ( Molas-Gallart and Tang, 2011 ; Spaapen and van Drooge, 2011 ).

The focus on societal impact in science governance and on interaction as a means to achieve this is particularly controversial for the social sciences and humanities (SSH), which we conceive of here as all research disciplines and subdisciplines that deal with social, societal, and cultural matters. On the one hand, from an internal scientific perspective, SSH disciplines investigate social life itself. This implies that subjects, investigators, and audiences tend to merge with one another and that value judgments might play a particularly important role ( Davies et al., 2008 ; Cassidy, 2014 ). As a result, when SSH researchers interact with societal stakeholders, questions of demarcation and boundary dissolution might arise ( Gieryn, 1983 ; Benneworth and Olmos-Peñuela, 2018 ). On the other hand, from an external perspective, evaluation exercises have rarely considered the particular epistemic conditions and specific utilization logics for SSH research ( Reale et al., 2018 ). Critics have noted the mismatch between indicators and SSH notions of quality, the lack of consideration for contributions that are critical rather than solution oriented, and the overly simple framing of societal impact as economic outputs, such as the number of patents or spin-offs ( Benneworth, 2015 ; Ochsner et al., 2017 ; Fecher and Hebing, 2021 ). Generally, established models for knowledge transfer do not do justice to the complexities of the diverse SSH disciplines and their many publics ( Davies et al., 2008 ).

Arguably, SSH research makes important societal contributions, but these are not well understood—at least not in the governance of science. We therefore recognize a need to better understand the societal impact of SSH disciplines in terms of a) the role they might play for societal challenges, b) the problems that might arise in interactive settings that involve SSH scholars and societal stakeholders, and c) the (possibly conflicting) quality expectations that are placed on their interaction. These objectives motivate our exploratory study, which consists of an online consultation with 125 experts (i.e., SSH researchers from different disciplines along with relevant societal stakeholders). Here, we report on the results of this consultation and reflect on the implications these might have for research evaluation.

Research Interest

The role of social sciences and humanities disciplines in response to societal problems.

There is some controversy about the role that SSH research can play in tackling societal problems: While some scholars argue that these fields should augment and emphasize their transformative potential ( Sörlin, 2018 ; Sigurðarson, 2020 ), others attribute a rather passive role to them, suggesting that they should create system knowledge (i.e., knowledge that increases understanding of a social issue) or orientation knowledge (i.e., knowledge that helps to determine possibilities for action) ( Becker, 2002 ; Jahn et al., 2012 ). One could furthermore argue that the public value of SSH research is not necessarily captured by their usefulness in solving problems but rather by their capacity to critically reflect on the problem itself and its potential solutions ( Olmos-Peñuela et al., 2015 ). In this regard, the societal impact of SSH research may also be counterintuitive if one expects clear-cut solutions to problems formulated in advance. Critics of an overly narrow conception of impact as research utilization have also pointed out how social science knowledge tends to be used in diverse ways, many of which are implicit ( Davies et al., 2008 ; Meagher et al., 2008 ; Stehr and Ruser, 2017 ). Weiss (1980) , for example, observes that expertise can “creep in” as conceptual knowledge that influences ideas and decisions. Compared to the natural and technical sciences, the impact of the SSH is thought to be more indirect and less visible. While utilization of SSH might be discreet, it can also be symbolic to the extent that it is used to justify political decisions that are already made ( Weiss, 1980 ; Albæk, 1995 ; Amara et al., 2004 ).

In summary, it is possible to identify quite different (often normative) perceptions of the societal role of SSH. Accordingly, the notion of socially relevant knowledge attributed to SSH disciplines varies: from more transformative and instrumental knowledge, to more indirect conceptual knowledge, to more counterintuitive critical knowledge. The different kinds of knowledge evoke quite different understandings of the role that the SSH should play in addressing societal challenges, which motivates our first research question (RQ1): What role is attributed to the SSH in addressing societal challenges?

Challenges for Collaborative Arrangements Involving the SSH and Societal Actors

In the sociology of science, the shift from deficit to dialogue is associated with concepts like “Mode 2,” “post-normal science,” or “triple helix” ( Funtowicz and Ravetz, 1992 ; Gibbons et al., 1994 ; Leydesdorff and Etzkowitz, 1998 ). These concepts all describe knowledge production as a mode of collaboration between scientific and societal stakeholders. According to a concept of transdisciplinarity, the main challenge for such collaborative arrangements is the integration of differences between actors on an epistemic, social-organizational, and communicative level ( Jahn et al., 2012 ). As already observed above, at the epistemic level, boundaries between subjects, investigators, and audiences have a tendency to become blurred in SSH research ( Davies et al., 2008 ; Cassidy, 2014 ). In collaborative arrangements that involve SSH researchers, questions of boundary work might therefore be of particular relevance ( Gieryn, 1983 ). Furthermore, within the diverse SSH disciplines, there is little consensus on research questions and suitable methods, which poses challenges to the robustness of findings ( Ochsner et al., 2017 ). Regarding the socio-organizational level, the structures that support societal exchange in universities are mostly centrally organized and focused on broad public communication ( Peters, 2013 ; Marcinkowski et al., 2014 ; Fecher and Hebing, 2021 ). Questions arise as to how adequate these might be for anticipating the complexities of science in general and of the SSH in particular. Furthermore, the focus on economic indicators as a means of measuring societal impact in the past might have led to structural discrimination against SSH disciplines in organizational efforts to promote societal engagement ( Benneworth and Olmos-Peñuela, 2018 ; Fecher and Hebing, 2021 ). Jacobson et al. (2004) suggest implementing an array of organizational measures that are believed to be more suitable for SSH disciplines, from increasing resources to fostering the skills of individual researchers. Regarding the communicative level, SSH researchers have frequently been accused of using overly specialized and obscure terms ( Alvesson et al., 2017 ; Healy, 2017 ). At the same time, because the social sciences—and to a lesser degree, the humanities—investigate social life, they must deal with the everyday observations and ad hoc assumptions of the individuals with whom they engage (cf. Cassidy, 2014 ).

Some researchers argue that a consensus on values is not the only necessary condition for facilitating cooperation between heterogeneous actors; more importantly the conditions and structures for cooperation must be created ( Star and Griesemer, 1989 ). For SSH disciplines, this might come with particular challenges that are not yet well understood. This motivates our second research question (RQ2): What hinders interaction between SSH researchers and societal stakeholders?

Quality Expectations Regarding the Interaction Process

If our aim is to grasp the collaborative settings of knowledge production, we will likely need to go beyond criteria that are either purely academic or targeted towards science communication through the media ( Secko et al., 2013 ; Rögener and Wormer, 2017 ). The term “socially robust,” meaning that knowledge should be scientifically robust and socially useful ( Nowotny et al., 2001 ), is now used frequently to describe quality in these settings. Rather than bridging a cognitive gap (as purely academic projects would do), these new modes of knowledge creation aim to bridge social gaps, i.e., they are geared towards potential users, political decision makers, and entrepreneurs ( Maasen and Lieven, 2006 ). The authors argue that in these settings, actors must develop social accountability procedures collaboratively. This undertaking produces social demands that differ from those made in disciplinary research because the researchers need to work outside the set of scientific norms that would otherwise guide their practice ( Merton, 1973 ; Mitroff, 1974 ). This creates new requirements vis-à-vis the outcome. These outcomes are not easily located on a disciplinary map but instead suit the context of application ( Gibbons et al., 1994 ). This will most likely be accompanied by processual requirements to bridge the above-mentioned gaps and to deal with the specific contexts that are addressed by these arrangements.

There are general preconceptions about how collaborative modes of knowledge production might consolidate the quality conceptions of all parties involved. Still, these often remain at an abstract level, which motivates our third research question (RQ3): What do scientific and societal stakeholders perceive as the conditions for good interaction?

Data and Methods

The study is exploratory in that it aims to better understand the societal impact of SSH disciplines by an empirical examination of the role ascribed to SSH research in addressing societal challenges, as well the quality expectations arising in collaborative processes involving SSH researchers. Our findings are based on an online consultation of SSH researchers, societal stakeholders, and intermediaries. We subsequently discussed the results of the consultation with SSH and science researchers in two workshops, where we further scrutinized their implications for assessing the societal impact of SSH.

The selection of participants in the consultation process was deliberate and targeted a) researchers from different SSH disciplines who had experience of knowledge transfer and b) societal stakeholders from politics, media, business, culture, civil society, and public administration who had experience in collaborating with SSH scholars. In order to ascertain that participants did indeed have experience of collaboration, we conducted preliminary interviews, researched specific collaboration projects, and, in the case of researchers, asked learned societies for nominations. The deliberate selection of participants was necessary in order to ensure that respondents could legitimately provide answers to the partly normative questions. Our final sample consists of 125 responses, of which 36 are SSH scholars, 71 societal stakeholders, and 18 intermediaries. Of the SSH scholars, four participants came from core humanities disciplines (philosophy, legal studies, history), four from economics, thirteen from other social sciences, and one each from pedagogy, linguistics, and design research. Twelve of the researchers did not indicate their disciplinary background. Further, our sample includes a group we describe as “intermediaries.” These are individuals that are involved in managing and enabling collaborations between SSH researchers, for example communications officers at universities or independent science communication consultants. We chose to include this group in the consultation because we assumed that they would be uniquely positioned to observe and thus reflect on the conditions of these interactions. Table 1 illustrates the final expert sample by group membership.

Sample of the online consultation by group membership.

The consultation consisted of an online survey that comprised both a close-ended section on sociodemographics and a set of mainly open-ended questions about individual experience in collaborative settings involving SSH researchers. Our analysis of the three research questions is based on five open questions in the survey ( Table 2 ). One of the questions refers to the Covid-19 pandemic ( Table 2 ; RQ1). We chose to include this because the pandemic is a complex societal challenge and is thus relevant to the subject of the study.

Research interest and survey questions.

We conducted a structuring content analysis in order to analyze the textual data. This technique corresponds to the inductive technique of qualitative content analysis ( Mayring, 2000 ) and takes into account Kuckartz’s structuring method by using an interpretative initial processing to then iteratively form consistent categories ( Kuckartz, 2014 ). Quotations in this paper are the authors’ translations from the original German responses into English.

We encouraged the experts to publish their names and responses because we consider them relevant for further research: 103 agreed to publish their responses, 68 agreed to publish their names and institutions, 27 to publish only the name of their institutions, and 30 wished to stay anonymous. The survey instrument, the anonymized MAXQDA file, as well as the full answers of those who granted permission, can be found on the project website.

This study had limitations regarding the selection of participants in the consultation: Despite every effort being made to recruit a diverse and relevant set of participants, the selection can hardly reflect the diversity of SSH researchers and its many specialized societal stakeholders. Further research is necessary to understand the manifestations of the generic categories presented here in different contexts.

From the survey responses, we first identify topics that SSH research is associated with and the role SSH research fulfills within society. Second, we present the challenges that are mentioned when SSH researchers and societal stakeholders interact. Third, we turn to quality expectations in this interaction. In each results section, we will report on the findings by referring to the number of codes ascribed to a category in brackets and use exemplary quotes where suitable.

Role of Social Sciences and Humanities Researchers

From the responses regarding the societal issues that SSH expertise is relevant for, we were able to identify 31 societal issues that span nearly every aspect of social and natural life, as well as technical innovation. Broadly, these can be assigned to the following categories: “politics” (45), “economy” (47), “culture” (6), “education” (26), “ecology” (56), “civil society” (131), “health” (34), and “technology” (42).

The answers likely relate to the respondents’ particular interests and expertise and do not represent those areas of real-world problems that the SSH contribute to. However, the issues show that the spectrum of topics ascribed to SSH disciplines goes far beyond narrow disciplinary couplings (e.g., educational research that deals with education or economics that deal with economic growth) and includes contemporary and frequently transformative topics, such as climate change, migration, or the current pandemic. The ubiquity of potential issues for SSH engagement is expressed in this quote from a journalist:

“Every topic has a societal component—from fundamental questions of democracy and politics to questions concerning nature and technology. Basically, each question that requires social action and regulation” (Media_ID103, 10).

While these issues provide some indication of the wide topical range for potential SSH engagement, the participants’ perception of the role of SSH research in addressing these societal issues might provide a more accurate picture of how that engagement might actually unfold. We coded the answers to the question of how participants assess the role of SSH research in solving societal problems accordingly. In total, we identified six distinct societal roles that are frequently referred to by the experts: explaining, reflecting, educating, signaling, foresight, and informing ( Table 3 ).

Societal functions of SSH knowledge.

We found indications that each of these six functions correspond to different types of knowledge. For example, the “explain” category relates to system knowledge needed to understand a social issue because it contains statements from participants that are geared towards contextualizing social issues without suggesting any concrete instructions for action. By the same token, the “educate” category contains knowledge used to build competence in a specific issue area. The category “foresee” relates to knowledge needed to determine possibilities for decision-making as it contains statements from participants that refer to future developments. For example, one person working in public administration describes SSH research as an “early warning system for problems that have not yet become apparent” (PublicAdmin_ID61, 9). According to this statement, SSH disciplines should assess the societal implications of social change. These include, as several respondents state, the implications of artificial intelligence on the future of work.

The “inform” category is closely linked to what is referred to as the instrumental use of SSH knowledge, i.e., it is used directly for decision-making. Both the “reflect” and the “signal” categories resonate with what might be considered critical knowledge. Statements in the “reflect” category do not refer to the provision of expertise for problem solving but to interpreting and analyzing the problem and the solution. The “signal” category includes statements that, according to the participants in the consultation, refer to issues that receive too little attention but are considered relevant to public discourse or policymaking. Accordingly, the role of SSH disciplines is to point to these problematic aspects and to act as a critical observer. In relation to the Covid-19 pandemic, for example, the participants mentioned that SSH researchers emphasized the psychological, social, and cultural consequences of pandemic control. Some experts believe SSH expertise is not given enough attention in current political strategies, others like this intermediary describe their influence as lagged but present:

“Whereas at the beginning it was mainly the virologists who were heard, in my opinion the social sciences have now made themselves heard in many respects and have pointed out numerous important aspects of economic and socio-political relevance. For example, the fact that the daycare centers and schools have not yet been closed again is not only due to the virological assessment that children are less likely to spread the virus, but also due to the indications of the problems for working parents and for the children whose educational disadvantages have been exacerbated” (Intermediary_ID110, 24).

The statements from politicians in our sample frequently referred to the “foresee” category, but other than that there were no striking quantitative variations in the distribution of codes.

With regard to the roles attributed to the SSH in solving societal problems, we identified different levels of activity, from a rather passive, contextualizing role (e.g., “explain”) to a more active, influencing role (e.g., “inform”). This leads us to conclude that the SSH provide a diverse range of problem-relevant kinds of knowledge for societal challenges. From a solution-focused point of view, SSH knowledge is partly counterintuitive because it does not necessarily aim to contribute to a solution but seeks to question the problem and its solution. Moreover, rather than producing knowledge that might itself stimulate change or even transformation, SSH disciplines are more frequently attributed the role of producing “cohesion knowledge,” that is, knowledge that helps anticipate change. In this regard, SSH research fulfils a moderating role in complex change processes by helping to establish and maintain social order, cohesion, and equality. In our view, the multiple roles attributed to SSH disciplines could amount to a moderating role that would involve taking into account the complexity of issue formation in change processes as well as attempts to tackle these. Therefore, SSH disciplines are in a position to consider overarching issues of social cohesion and equality. The capacity of SSH research to address questions of cohesion is strongly reflected in the frequency of references to issues: the terms equality or inequality are mentioned 79 times by the respondents, democracy is mentioned 32 times, and cohesion or similar terms are mentioned 28 times.

Interaction Challenges

In order to understand where difficulties arise in the interaction between SSH scholars and societal stakeholders, the participants were asked about the problems and challenges they experienced in previous interactions and—in order to assess organizational aspects—the role of universities in supporting science-society interactions. We identified four kinds of interaction challenges in the answers: 1) translational challenges that relate to different modes and logics of interaction, 2) institutional challenges that relate to the governance and organization of science, 3) epistemic challenges that relate to knowledge creation processes of SSH disciplines, and 4) uptake challenges that relate to the use of SSH expertise by different societal stakeholders. Table 4 presents these challenges and their subdimensions.

Interaction challenges.

Translational Challenges: Conflicting System Logics and Boundary Work

Translational challenges relate to different modes and logics of interaction between involved parties. The category comprises statements made by respondents that refer to semantic aspects and systemic differences between science and other social systems that hamper meaningful interaction. The statements in this category can be split into two categories: “language barriers” (27) and “conflicting system logics” (73).

Some participants perceive the language of SSH scholars to be complicated, as this journalist describes:

“As a journalist, it strikes me that social science researchers very often and unfortunately quite naturally use terms that are hardly used or understood by the general public” (Media_ID159, 13).

Differences, however, can be found in the assessment of language barriers. Some see the use of technical concepts as a necessity for describing social phenomena in a differentiated way, while others see it as unnecessarily complicated prose that is a hindrance to productive exchange. In general, references to language barriers are mostly made by participants working in the private sector or in the media.

A second challenge can be described as “conflicting system logics.” Statements in this category refer to three closely related aspects of incompatibility: 1) temporality of SSH research (i.e., SSH research takes time and cannot satisfy needs immediately), 2) conflicting notions of relevance (i.e., societal relevance of SSH is not based on immediate societal needs), and 3) self-referentiality of SSH research (i.e., SSH research refers to itself and not to what others consider social problems). The conflicting system logics resulting from these are well expressed in a quote from an SSH researcher, who on the one hand calls for SSH researchers to anticipate different societal contexts (here the media) but on the other hand reports that this can lead to conflicts among academic peers:

“Scholars should recognize that they move in a different system logic when they communicate with the media, for example. I experience a lot of criticism of the portrayal of science in the media, which I consider inappropriate. Of course, there is a decrease in length, but that is also completely okay.” (SSHscholar_ID138, 16–17)

In general, the participants often refer to different system logics, usually to explain why an exchange could not take place from their specific perspectives. In this quote, for example, a politician reports on the context of his decision making and the associated lack of time to deal with SSH research:

“Science is a different system than politics; there is a democracy proviso; being an elected official does not give me enough time to read or receive scientific literature.” (Politics_ID196, 17)

Different system logics explain the translational challenges between SSH researchers and members of other social subsystems, specifically with regards to language usage, the notions of relevance, and time and content-related use considerations. This explanation can be problematic when functional differentiation of social systems is used as a pretext for not engaging in interaction at all. It might be more fruitful to think of the interaction between societal stakeholders and scientists as one where boundaries between science and nonscience are contextually and continuously dissolved and redrawn.

Institutional Challenges: Mismatch Between Aspiration and Resources

Institutional challenges relate to the governance and organization of science. In this respect, we identified three types of challenges in the statements. These are “lack of resources” (19), “lack of organizational support” (19), and “lack of rewards” (20).

In most cases, references to lack of resources refer to limits concerning SSH researchers’ time and skills. One social scientist mentioned the need for training for research staff when explaining the latter:

“[We] are not trained to do this; we usually do basic research and teach basic science at universities—we need knowledge transfer” (SSHscholar_ID68, 15).

A second institutional challenge relates to the lack of organizational support. Respondents often refer to a decoupling of transfer infrastructures at universities and the researchers working there, or to necessary investment in transfer capacities at research organizations. The latter becomes clear in this statement made by a participant who works in public administration:

“In my opinion, scientific institutions should invest more in public relations—these positions are often sparsely staffed and funded [...]. The relevance of the job/intermediary function is recognized more and more, but this is (often) not yet reflected in the structures” (Intermediary_ID229, 13).

A third challenge in this category is the lack of rewards for societal engagement, which the participants link to the academic reputation and funding system. Another social scientist describes what she perceives as an undervaluation of engagement as follows:

“[There is a] lack of reputation for this activity as opposed to third-party funding and high-ranking publications. [Engagement] is only an “add on”” (SSHscholar_ID44, 13).

The notion of “engagement as an add-on” (i.e., not a main task) is mentioned frequently and especially by SSH scholars in the consultation. However, the participants discuss the matter of recognition with significant differentiation: One expert describes societal impact as an additional pathway for scholarly work, alongside scientific impact:

“Since publication excellence can hardly be mitigated, they could instead create funding lines that can only be used if the relevance to the SDGs is laid out clearly,” (SSHscholar_ID65, 28).

Lack of recognition for public engagement activities and a lack of resources to carry them out are not specific to SSH disciplines per se. However, they may be more pronounced here because knowledge transfer is even less rewarded and incentivized in a dominant framework focused on economic outcomes. If strengthening societal engagement is a science policy priority, the results here suggest that there is a perceived mismatch between this aspiration and the resources allocated to it.

Epistemic Challenges: The Illusion of Stable Social Sciences and Humanities Knowledge

The epistemic challenges category describes challenges that relate to the knowledge creation of SSH disciplines. It includes two subcategories, “ambiguous results” (23) and “conflicting paradigms” (9).

With respect to “ambiguous results,” statements often contain comparisons to the “hard” natural sciences, where results are perceived by some participants to be clear and unambiguous. In contrast, results from SSH disciplines are often described as vague. For example, for a respondent who works as a researcher and in the media, this is the main reason why results from the natural sciences are preferred:

“Questions and research designs are often too vague, the results too ambiguous. Therefore, journalists prefer communicating results from the natural sciences” (SSHscholar_ID142, 16).

The “conflicting paradigms” category contains statements that emphasize how different schools of thought within SSH disciplines result in different ways of understanding and assessing the same issue. A social scientist in the consultation interpreted the heterogeneity of SSH disciplines as an impediment to communication:

“Distinctive disciplinarity and families of methods in SSH disciplines prevent common problem-oriented communication” (SSHscholar_ID206, 22).

While the heterogeneity of SSH disciplines is often described as normal and indeed as an asset by the participants, some point to a problem, namely that this lack of consensus can also be perceived by the public as a lack of scientific rigor. This can lead to a loss of reputation and trust.

“One challenge is the question of how issues that are scientifically controversial can be presented to the public in such a way that the reputation of science does not suffer and, ideally, this heterogeneity can even be used productively” (SSHscholar_ID179, 13).

Of course, conflicting paradigms and ambiguous results are not purely SSH problems. However, they manifest in specific ways there. In general, SSH disciplines comprise very different approaches, research questions, and epistemological premises. Moreover, their results are often strongly dependent on context. These characteristics are echoed in our respondents’ view of the ambiguity of SSH results, which they describe as a challenge when interacting with societal stakeholders.

Uptake Challenges: Lacking Appreciation and Public Attention Dynamics

The category uptake challenges includes statements from participants that relate to the use of SSH expertise by societal stakeholders. We identified three types of uptake challenges. These are: “lacking public appreciation” (27), “public attention dynamics” (13), and the “risk of instrumentalization” (5).

Regarding “lacking appreciation,” SSH disciplines are, again, often contrasted with the natural sciences by participants. Many of them describe the natural sciences as having a comparatively higher public status, which becomes obvious in this statement from an SSH scholar:

“From my point of view, we offer many research topics that are of interest to a broader public, but we are not yet perceived and treated equally with the natural sciences” (Intermediary_ID229, 16)

This observation is backed up by a journalist who explains that while disciplines such as medicine, physics, or engineering are met with fascination, SSH disciplines are not:

“While the natural sciences and medicine are often met with widespread fascination for their subjects in society, this is often lacking in social science. Physics and technology are sexy, other disciplines are not” (Media_ID159, 16).

The “dynamics of public attention” subcategory subsumes statements that describe SSH research as being out of kilter with the public interest. In general, this refers to a perceived mismatch between the utilitarian perspective of societal stakeholders and the supply of knowledge that SSH disciplines can provide. Often, participants refer to the fast pace of social media, which SSH research cannot keep up with. Some participants even describe adverse effects when SSH researchers adapt their communication to the dynamics of publicity, which is made obvious in a quote from a humanities scholar, who explains how attention might trump relevance in public communication:

“Provocation is better “received” than factuality; “loud” colleagues are simply better seen and heard” (SSHscholar_ID67, 13).

The “risk of instrumentalization” category is rarely referenced. We list it nevertheless, because it is often mentioned in the literature and is distinct from the other listed challenges. The category subsumes statements that refer to the misuse of SSH expertise for political interests. For instance, a representative working in the economy and for an NGO states:

“Politicians must not misuse scientific findings for their own agendas and thereby partly discredit them” (Economy_ID96, 18).

Taken together, when SSH results are discussed by the public, they appear to not be appreciated in the same way as natural science results. Instead. they are made subject to attention dynamics and might be instrumentalized. This negative perception might be linked to the subtle nature and multiple ways in which SSH expertise reaches the public and political decision makers. If media attention factors determine whether SSH results are noted by the public, the scientific and societal relevance of SSH expertise might recede.

Quality Expectations

The third research question addresses quality expectations, i.e., conditions for a good exchange between societal stakeholders and SSH researchers. To this end, we asked the participants open questions about their expectations for a good exchange and about the specific conditions that might apply to SSH disciplines. From the answers, we are able to identify eight distinctive quality expectations that can be divided into three main categories. These are 1) process-related, b) outcome-related, and c) person-related quality expectations ( Table 5 ). Engagement with society, albeit an aspiration of many research organizations, seems to be difficult in current organizational structures according to our respondents.

Quality expectations.

Process-Related Quality Expectations

Process-related quality expectations refer to the interaction between SSH scholars and societal stakeholders and includes the codes “comprehensibility” (26), “pertinence” (13), “inclusivity” (26), and “form” (25).

“Comprehensibility” encompasses statements that refer to the mutual understanding between actors. Typically, these statements refer to comprehensible and clear communication of results on the part of SSH scholars and the adaptation to interlocutors. Accordingly, complex contents should be conveyed in such a way that those involved in the dialogue are able to follow and respond in an informed manner. The code “pertinence” refers to statements that suggest that knowledge should be used in a problem—and solution-oriented manner. This is illustrated by a statement made by a politician:

“For the policy sphere, I would like to see more focused exchanges that bring in key research findings” (Politics_ID237, 19).

“Inclusivity” refers to the actors involved in an interaction. We distinguished between two types of inclusivity. The first is selective inclusivity, which means that appointed experts who can contribute relevant and specific expertise should be involved. The second is universal inclusivity, which implies broader participation involving those who are possibly affected by the issue. Some participants point out that diverse expertise is needed to achieve viable results. Lastly, statements coded as “form” typically refer to the existence of an interaction format that is adequate for exchange and problem-solving.

It is impossible to meet all of these expectations of the interaction process. One SSH scholar puts it in these almost utopian terms:

“The goal should be to communicate complexity, reflexivity, and provisionality simply, clearly, understandably, and plausibly” (SSHscholar_ID205, 15).

It can be assumed that the more complex a problem is and the more diverse the parties involved in the interaction process, the more difficult it will be to arrive at some form of shared meaning. In this regard, there are expected tensions between inclusivity, pertinence, and comprehensibility, while formality might imply a strategy to meet these expectations in the best possible way.

Outcome-Related Quality Expectations

Outcome-related quality expectations refer to the results of an interaction process between SSH scholars and societal stakeholders. This category comprises the codes “transparency” (30) and “relevance” (31).

The code “transparency” indicates statements that refer to two kinds of transparency: 1) method transparency and 2) motivation transparency. In this article, we use method transparency to refer exclusively to SSH disciplines and signal the requirement of communicating uncertainties and clearly describing methods as necessary for good exchange. Motivation transparency refers to the communication of motivating factors (e.g., personal interest, dependencies, client expectations) and pertains to both SSH scholars and societal stakeholders. This is made obvious in a statement from a social science scholar:

“As part of society, scientists perceive and research socially relevant topics—politics should make the use of scientific research results transparent” (SSHscholar_ID68, 18).

“Relevance” includes statements that refer to the practical implications of the interaction process. We distinguished between individual and societal relevance. Individual relevance signifies the benefits for the individuals involved and is described by some as a motivating factor for partaking in the interaction process. Societal relevance is usually viewed in a differentiated way as referring either to benefits for individual citizens or benefits for specific groups and sectors of society. In some statements, such as the following made by a politician, societal relevance is framed as a return on societal investment in publicly financed research:

“Society makes a considerable contribution to the financial security and freedom of science, not least through public budgets. It can therefore expect science to take an interest in societal issues and to make its contribution to solving societal problems [...]” (Politics_ID234, 18).

However, achieving both transparency and relevance might be difficult, as this statement from an economics scholar shows:

“The greatest challenge in communicating social science research is often to openly acknowledge the uncertainty inherent in its findings while convincing people that they nevertheless contain important information” (SSHscholar_ID157, 16).

In this case, transparency is seen as a hindrance for relevance. Further tensions might arise when personal and societal relevance do not correspond, or when transparency (in the sense of replicability) cannot be achieved. There might also be a conflict between different quality expectations in the outcome of the interaction process.

Person-Related Quality Expectations

Person-related quality expectations refer to the individuals involved in the interaction process. They subsume the codes “empathy” (67) and “disinterestedness” (14).

“Empathy” indicates statements that refer to the mutual acknowledgement of all parties involved. Most statements in this category refer to acknowledging the position of the other parties involved in the interaction process. Typically, the social position of an individual comes with certain concessions, for example, journalists are granted reporting duties, politicians have decision-making power, and SSH scholars possess research autonomy. The reciprocal nature of the expectation of empathy is made clear in this quote from a journalist in the consultation:

“When researchers recognize that the media are their partners—in discourse, in presentation, in criticism. That means being available for media inquiries, discussing issues of relevance with a journalist, and sharing material. It also means tolerating exaggerations, even if one’s own business is differentiation” (Media_ID114, 16).

Some participants state that empathy should not be blind but informed. This is made obvious in a quote from a participant who works in public administration:

“It is important that the results of SSH disciplines can be properly assessed. Excessive claims in the social sciences, in the sense of objective truths, can easily produce disappointment and lead to a deviation, which in the worst cases can then leave the impression of arbitrariness of the decisions and actions under discussion” (PublicAdmin_ID167, 15).

The code “disinterestedness” is used for statements that emphasize that actors should not pursue their own interests but act for the benefit of society. This is often combined with the expectation that personal opinions should be separated from facts and that the conversation should be devoid of emotions and self-promotional intentions. Responding to the question of what constitutes a good collaboration between science and society, one SSH scholar states:

“In my view, a good exchange is characterized above all by the fact that it is not primarily guided and inspired by the self-promotional intentions of individual scientists or scientific organizations” (SSHscholar_ID37, 16).

There are conflicts between disinterestedness and empathy, for instance when it comes to the proclaimed necessity of leaving emotions aside. In addition, there may be potential cross-category tensions between person—and outcome-related quality expectations, for instance in relation to disinterestedness and the individual relevance described above. The same holds true for informed empathy and inclusivity. Remarkably all participants, researchers as well as societal stakeholders from different fields, name the quality expectation empathy most frequently as a condition for exchange. Reflection on ones own position seems crucial for science-society-interactions.

In this article, we used an expert consultation to examine the societal impact of SSH disciplines, i.e., the role of SSH research in addressing societal issues, as well as the resulting challenges and quality expectations. The results shed light on the conundrum of addressing societal issues while being part of the subject matter.

Social Sciences and Humanities Knowledge as Cohesion Knowledge

The societal issues that SSH disciplines relate to are broad and transcend disciplinary couplings. The quasi ubiquity of SSH impact areas resonates with recent research findings (e.g., Bastow et al., 2014 ). The roles ascribed to SSH disciplines in addressing societal problems are likewise diverse and range from more instrumental tasks, such as informing a policy decision, to more contextualizing activities, such as explaining the social implications of a problem. The latter resonates with Stehr and Ruser’s (2017) description of social scientists as “meaning producers,” i.e., their knowledge does not focus on practical choices but on processes of meaning, which may give rise to decisions. In addition, we find evidence of a more counterintuitive role for SSH disciplines in addressing societal challenges, namely critiquing the definition of a problem and the envisaged solution. This finding resonates with Burchell (2009) who proposes that, from a societal perspective, the social sciences might best be interpreted as a “critical friend” (see also Davies et al., 2008 ). Participants in the consultation describe the relevance of this critical capacity, for instance, in discussing the social, cultural, and psychological implications of the Covid-19 pandemic, which some feel have not been sufficiently considered in policy decisions.

Along with these roles, we identified different types of knowledge that SSH disciplines can provide to help resolve societal challenges. These range from overview and system knowledge, as described by Becker (2002) , to instrumental knowledge ( Fähnrich and Lü ; Stehr and Ruser, 2017 ) like the kind that is used to inform political decision-making processes. This differentiation resonates with ( Weiss, 1980 ) who suggests that the contributions of SSH research to decision-making processes are much wider than a narrow idea of knowledge utilization suggests. Moreover, “critical knowledge,” i.e., knowledge that enables us to question societal decisions, appears to be an essential contribution of SSH disciplines to societal issues. This positions SSH researchers as a critical corrective in addition to its contextualizing and co-creating capacity. At a higher level of abstraction, we observe that SSH disciplines are rarely associated with “transformative knowledge” that causes change ( Becker, 2002 ) but instead with knowledge that helps us anticipate societal transformations and to deal with change (see also Sigurðarson, 2020 ). We refer to this kind of knowledge as “cohesion knowledge.”

Continuous Boundary Work

In the scholarly debate, dialogue between representatives from both science and society is understood as a condition for “socially robust” knowledge, i.e., knowledge that is both scientifically robust and socially useful ( Nowotny et al., 2001 ). Consequently, we conceptualize interaction as a prerequisite for societal impact (see also Spaapen and van Drooge, 2011 ). This motivated us to interrogate challenges in interactive and problem-oriented settings involving SSH disciplines. The challenges we identify can be categorized as translational, institutional, epistemic, and uptake challenges, and they thus correspond roughly to the framework suggested by Jahn et al. (2012) . While many of the challenges we identified point to contingent issues, some results stand out.

When it comes to translation, reducing linguistic complexity without being accused of triviality and commonplace hypotheses is a core challenge for SSH disciplines. Some of the societal stakeholders in the consultation describe SSH disciplines as self-referential and the language used as unnecessarily complicated at times. Bridging the “social gap” ( Maasen and Lieven 2006 ) between science and society thus means that SSH scholars must adapt their language (e.g., their use of terms), although at the risk of compromising their epistemic authority. A problem-oriented interaction with societal stakeholders, however, might contribute to increased “methodological efficiency” as a form of continuous external validation ( Woolgar, 2000 ). Regarding institutional challenges, we find initial evidence for a structural disadvantage of SSH disciplines. This might be explained with reference to the fact that the established entrepreneurial heuristic of societal impact carries little significance for SSH disciplines ( Benneworth and Olmos-Peñuela, 2018 ). Epistemic challenges mostly concern the heterogeneity of SSH disciplines and their approaches, intermittently conflicting paradigms, and the dynamic object of study, i.e., society as a moving target ( Dayé, 2014 ). It follows that SSH disciplines produce knowledge that is highly context-dependent, situated, and dynamic ( Gattone, 2012 ; Fähnrich and Lüthje, 2017 ). Hence, there are serious limitations regarding the extent to which objective, stable, and context-independent knowledge can be expected from SSH disciplines ( Davies et al., 2008 ). This finding is consistent with the self-conception of many SSH disciplines as critical, reflective, and contextual. When it comes to the uptake of SSH knowledge, the consulted representatives note how SSH expertise is not always fully appreciated and may explain to a certain extent the lack of appreciation for SSH research. For example, in the consultation, SSH research is often contrasted with natural science and technical disciplines, whose results are not only perceived as more stable but often as more exciting, too. This resonates with Knudsen (2017) , who found a deficit framing for the humanities in Danish print media. Cassidy (2014) explains this lack of appreciation with the close relationship of SSH disciplines to everyday life: “Unlike most natural sciences, where the specialist training, knowledge and equipment of scientists grants them largely uncontested expertise, social scientists’ expertise is often about matters of everyday experience and common-sense knowledge” (p. 190).

Taken together, these challenges suggest a twofold implication: The calls for more resources and recognition are on the one hand contingent issues that can give impulses to the governance of science. On the other hand, our results illustrate how the position of the SSH in society is a matter of ongoing negotiations. The identified challenges show how the SSH are caught up in boundary work in their interactions with extra-academic fields ( Gieryn, 1983 ). They speak of troubles of SSH researchers to claim their authority, which is linked to epistemic dynamics, that find expression in language usage, specific temporalities and context-specific results. How the SSH position themselves towards their moving target, the society, becomes even more of a challenge in collaborative formats.

Contextual Quality Configurations

Our empirical findings indicate a three-dimensional framework for ensuring quality in collaborative arrangements involving SSH researchers and societal stakeholders. The first is process-related and describes the expectations of the exchange itself. The second is person-related and describes the expectations towards the people involved. The third is outcome-oriented and includes the expectations of the outcome. In collaborative settings, there will most likely be contradictory expectations of what entitles persons to participate, how interacting partners should behave, and what constitutes relevant knowledge (see also Kropp and Wagner, 2010 ). This leads to conflicts between different expectations of quality that are difficult to avoid, for instance between disinterestedness and empathy, but also within categories, for instance, regarding different understandings of relevance (e.g., how can scientific demands for relevance be reconciled with demands for utility?). At times, the participants in the consultation offer solutions to these conflicts between quality expectations, for instance when they say that there are conditions for participation in the interaction such as having a basic understanding of the other interaction partner. This is in line with Bromme’s (2020) concept of “informed trust,” according to which it needs not only trust in public scientific statements but also knowledge on the system of science to make an informed judgement. Our findings add a nuance to this hypothesis by suggesting that informed trust must be reciprocal, i.e., researchers participating in a dialogue must also understand the societal stakeholders they engage with.

Generally, we can safely assume that the more diverse and complex the setting for a dialogue is, the more difficult it may be to document expertise and to establish transparency. If being affected by an issue legitimizes participation in a dialogue, then it may be more difficult to enforce pertinence as a premise. If expertise legitimizes participation, there is also a risk of exceeding the level of fact. It follows that there must be legitimate reasons for trade-offs between different quality expectations. These should depend on the aim of the interaction, the individuals involved, and the chosen interaction format. It follows that quality expectations in collaborative settings should not be understood universally, unilaterally, and statically. Instead, they should be considered within their specific context, reciprocally, and dynamically. Hence, we propose that quality itself must be an object of these interactions, i.e., there should ideally be deliberation about the appropriate quality configuration for the problem at hand. This could be particularly relevant for SSH disciplines, which, as discussed above, have to engage in continuous boundary work due to their position in society. The outline of a quality framework as proposed here can be a basis for deliberating on the quality of these arrangements. That said, for particularly established forms of interaction (e.g., scientific policy advice), there may already be recognized default settings from which it is possible to extrapolate.

Our results show, that the societal impact of SSH disciplines can be counterintuitive and precisely not aimed at solving a problem. Instead, they often seek to challenge both the problem and its solution. Nor does SSH research necessarily strive for transformation but instead seeks an understanding and a moderation of social change. Therefore, the impact of the SSH is often discreet, indirect, and conceptual. Thus, the quality of the societal impact of SSH disciplines can only be understood in relation to their specific context, in the sense that it is person-, problem-, and time-dependent and must take into account different field logics as it takes place in a “space between fields” ( Williams, 2020 ). For these reasons, a rigid, purely quantitative assessment of societal impact of SSH disciplines should generally be avoided, especially with regard to how assessment shapes and stabilizes underlying values ( Espeland and Sauder, 2007 ; Williams, 2020 ).

Our results provide some arguments for so-called formative evaluations of the societal impact of SSH disciplines. Formative evaluations focus on the process (e.g., an interaction, a program, or a project) while the activities are ongoing. They are geared towards learning and goal adjustment. The SIAMPI approach ( Spaapen and van Drooge, 2011 ) as well as the Agora model ( Frederiksen et al., 2003 ; Barré, 2010 ) or Public Value Mapping ( Bozeman and Sarewitz, 2011 ) are promising examples of such formative assessment concepts. Using the concept of “productive interactions,” the SIAMPI approach focuses on the individual’s contributions to an interaction rather than reactively assessing its outputs. With its emphasis on productivity however, it cannot capture the counterintuitive contributions outlined above, which do not focus on the solution to a problem but instead question the problem.

Nonetheless, this at times counterintuitive impact of SSH disciplines may not be suitable for evaluation at all. Instead, it might imply that additional measures such as capacity building are needed to support the interaction between science and society ( Sigurðarson, 2020 ). The integration of science communication, and with it the reflection on boundaries, must become an integral part of science education. This is underlined by the trend towards public legitimation of research funds and a new social contract for science not as hasty obedience to a political desire but as a basis for an informed discussion of perspectives and implications. In that sense, it seems reasonable to reflect on and gain a more nuanced understanding of the societal impact of SSH disciplines within research communities and learned societies.

Data Availability Statement

Author contributions.

All authors certify that they have participated sufficiently in the work to take public responsibility for the content, including participation in the concept, design, analysis, writing, or revision of the manuscript. BF supervised, carried out the analysis, editing and data collection together with FK. All authors discussed the results and contributed to the final manuscript.

This study was carried out with funding from the German Federal Ministry of Education and Research (under grant numbers 01PW18008A and 01PW18008B BMBF).

Conflict of Interest

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

• Albæk E. (1995). Between Knowledge and Power: Utilization of Social Science in Public Policy Making . Policy Sci 28 , 79–100. 10.1007/BF01000821 [ CrossRef ] [ Google Scholar ]
• Alvesson M., Gabriel Y., Paulsen R. (2017). Return to Meaning: A Social Science with Something to Say . First edition. Oxford: Oxford University Press. 10.1093/oso/9780198787099.001.0001 [ CrossRef ] [ Google Scholar ]
• Amara N., Ouimet M., Landry R. (2004). New Evidence on Instrumental, Conceptual, and Symbolic Utilization of University Research in Government Agencies . Sci. Commun. 26 , 75–106. 10.1177/1075547004267491 [ CrossRef ] [ Google Scholar ]
• Barré R. (2010). Towards Socially Robust S&T Indicators: Indicators as Debatable Devices, Enabling Collective Learning . Res. Eval. 19 , 227–231. 10.3152/095820210X512069 [ CrossRef ] [ Google Scholar ]
• Bastow S., Dunleavy P., Tinkler J. (2014). The Impact of the Social Sciences: How Academics and Their Research Make a Difference. Los Angeles; London; New Delhi; Singapore . Washington, D.C: SAGE. 10.4135/9781473921511 [ CrossRef ] [ Google Scholar ]
• Becker E. (2002). Transformations of Social and Ecological Issues into Transdisciplinary Research . Knowl. Sustain. Dev. Insight Encycl. Life Support. Syst. 3 , 949–963. [ Google Scholar ]
• Benneworth P., Olmos-Peñuela J. (2018). Reflecting on the Tensions of Research Utilization: Understanding the Coupling of Academic and User Knowledge . Sci. Public Pol. 45 , 764–774. 10.1093/scipol/scy021 [ CrossRef ] [ Google Scholar ]
• Benneworth P. (2015). Tracing How Arts and Humanities Research Translates, Circulates and Consolidates in society. How Have Scholars Been Reacting to Diverse Impact and Public Value agendas?How Have Scholars Been Reacting to Diverse Impact and Public Value Agendas? Arts Humanities Higher Edu. 14 , 45–60. 10.1177/1474022214533888 [ CrossRef ] [ Google Scholar ]
• BMBF (2019). Grundsatzpapier des Bundesministeriums für Bildung und Forschung zur Wissenschaftskommunikation . Berlin: Federal Ministry of Education and Research. [ Google Scholar ]
• Bornmann L. (2013). What Is Societal Impact of Research and How Can it Be Assessed? a Literature Survey . J. Am. Soc. Inf. Sci. Tec 64 , 217–233. 10.1002/asi.22803 [ CrossRef ] [ Google Scholar ]
• Bozeman B., Sarewitz D. (2011). Public Value Mapping and Science Policy Evaluation . Minerva 49 , 1–23. 10.1007/s11024-011-9161-7 [ CrossRef ] [ Google Scholar ]
• Bromme R. (2020). “ Informiertes Vertrauen: Eine psychologische Perspektive auf Vertrauen in Wissenschaft ,” in Wissenschaftsreflexion . Editors Jungert M., Frewer A., Mayr E. (Brill | mentis; ), 105–134. 10.30965/9783957437372_006 [ CrossRef ] [ Google Scholar ]
• Bucchi M. (2008). “ Of Deficits, Deviations and Dialogues. Theories of Public Communication of Science ,” in Handbook of Public Communication of Science and Technology . Editors Bucchi M., Trench B. (London; New York: Routledge; ), 57–76. Available at: http://site.ebrary.com/id/10236333 (Accessed April 13, 2021). [ Google Scholar ]
• Burchell K. (2009). A Helping Hand or a Servant Discipline? Sci. Technol. Innov. Stud. 5 , 49–61. 10.17877/DE290R-970 [ CrossRef ] [ Google Scholar ]
• Cassidy A. (2014). “ Communicating the Social Sciences: a Specific Challenge? ,” in In Routledge Handbook of Public Communication of Science and Technology . Editors Bucchi M., Trench B. (London; New York: Routledge, Taylor & Francis Group; ), 186–197. [ Google Scholar ]
• Davies H., Nutley S., Walter I. (2008). Why 'knowledge Transfer' Is Misconceived for Applied Social Research . J. Health Serv. Res. Pol. 13 , 188–190. 10.1258/jhsrp.2008.008055 [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Davies S., McCallie E., Simonsson E., Lehr J. L., Duensing S. (2009). Discussing Dialogue: Perspectives on the Value of Science Dialogue Events that Do Not Inform Policy . Public Underst. Sci. 18 , 338–353. 10.1177/0963662507079760 [ CrossRef ] [ Google Scholar ]
• Dayé C. (2014). Visions of a Field . Sci. Technol. Hum. Values 39 , 877–891. 10.1177/0162243914538323 [ CrossRef ] [ Google Scholar ]
• Espeland W. N., Sauder M. (2007). Rankings and Reactivity: How Public Measures Recreate Social Worlds . Am. J. Sociolo. 113 , 1–40. 10.1086/517897 [ CrossRef ] [ Google Scholar ]
• Fähnrich B., Lüthje C. (2017). Roles of Social Scientists in Crisis Media Reporting: The Case of the German Populist Radical Right Movement PEGIDA . Sci. Commun. 39 , 415–442. 10.1177/1075547017715472 [ CrossRef ] [ Google Scholar ]
• Fecher B., Hebing M. (2021). How Do Researchers Achieve Societal Impact? Results of an Empirical Survey Among Researchers in Germany . Berlin: SSOAR; Available at: https://www.ssoar.info/ssoar/handle/document/71327 . [ Google Scholar ]
• Frederiksen L. F., Hansson F., Wenneberg S. B. (2003). The Agora and the Role of Research Evaluation . Evaluation 9 , 149–172. 10.1177/1356389003009002003 [ CrossRef ] [ Google Scholar ]
• Funtowicz S. O., Ravetz R. (1992). “ Three Types of Risk Assessment and the Emergence of post-normal Science ,” in Social Theories of Risk (Praeger; ), 251–274. [ Google Scholar ]
• Gattone C. F. (2012). The Social Scientist as Public Intellectual in an Age of Mass Media . Int. J. Polit. Cult. Soc. 25 , 175–186. 10.1007/s10767-012-9128-1 [ CrossRef ] [ Google Scholar ]
• Geuna A., Martin B. R. (2003). University Research Evaluation and Funding: An International Comparison . Minerva 41 , 277–304. 10.1023/B:MINE.0000005155.70870.bd [ CrossRef ] [ Google Scholar ]
• Gibbons M., Limoges C., Nowotny H., Schartzmann S., Scott P. B., Trow M. (1994). in The New Production of Knowledge. The Dynamics of Science and Research in Contemporary Societies. London (Thousand Oaks, Calif: SAGE Publications; ). 10.4135/9781446221853 [ CrossRef ] [ Google Scholar ]
• Gieryn T. F. (1983). Boundary-Work and the Demarcation of Science from Non-science: Strains and Interests in Professional Ideologies of Scientists . Am. Sociological Rev. 48 , 781. 10.2307/2095325 [ CrossRef ] [ Google Scholar ]
• Healy K. (2017). Fuck Nuance . Sociological Theor. 35 , 118–127. 10.1177/0735275117709046 [ CrossRef ] [ Google Scholar ]
• Jacobson N., Butterill D., Goering P. (2004). Organizational Factors that Influence University-Based Researchers' Engagement in Knowledge Transfer Activities . Sci. Commun. 25 , 246–259. 10.1177/1075547003262038 [ CrossRef ] [ Google Scholar ]
• Jahn T., Bergmann M., Keil F. (2012). Transdisciplinarity: Between Mainstreaming and Marginalization . Ecol. Econ. 79 , 1–10. 10.1016/j.ecolecon.2012.04.017 [ CrossRef ] [ Google Scholar ]
• Knudsen S. (2017). Thinking inside the Frame: A Framing Analysis of the Humanities in Danish Print News media . Public Underst. Sci. 26 , 908–924. 10.1177/0963662517693452 [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Kropp C., Wagner J. (2010). Knowledge on Stage: Scientific Policy Advice . Sci. Technol. Hum. Values 35 , 812–838. 10.1177/0162243909357912 [ CrossRef ] [ Google Scholar ]
• Kuckartz U. (2014). Qualitative Text Analysis: A Guide to Methods, Practice & Using Software . Los Angeles: SAGE Publications. [ Google Scholar ]
• Leydesdorff L., Etzkowitz H. (1998). The Triple Helix as a Model for Innovation Studies . Sci. Public Pol. 25 , 195–203. 10.1093/spp/25.3.195 [ CrossRef ] [ Google Scholar ]
• Maasen S., Lieven O. (2006). Transdisciplinarity: a New Mode of Governing Science? Sci. Public Pol. 33 , 399–410. 10.3152/147154306781778803 [ CrossRef ] [ Google Scholar ]
• Marcinkowski F., Kohring M., Fürst S., Friedrichsmeier A. (2014). Organizational Influence on Scientists' Efforts to Go Public . Sci. Commun. 36 , 56–80. 10.1177/1075547013494022 [ CrossRef ] [ Google Scholar ]
• Mayring P. (2000). Qualitative Content Analysis . Forum Qual. Sozialforschung Forum Qual. Soc. Res. 1; Available at: http://www.qualitative-research.net/index.php/fqs/article/view/1089 . (Accessed August 20, 2015). [ Google Scholar ]
• Meagher L., Lyall C., Nutley S. (2008). Flows of Knowledge, Expertise and Influence: a Method for Assessing Policy and Practice Impacts from Social Science Research . Res. Eval. 17 , 163–173. 10.3152/095820208X331720 [ CrossRef ] [ Google Scholar ]
• Merton R. K. (1973). “ The Normative Structure of Science ,” in The Sociology of Science: Theoretical and Empirical Incvestigations (Chicago: Univ. of Chicago Pr; ), 267–278. [ Google Scholar ]
• Mitroff I. I. (1974). Norms and Counter-norms in a Select Group of the Apollo Moon Scientists: A Case Study of the Ambivalence of Scientists . Am. Sociological Rev. 39 , 579. 10.2307/2094423 [ CrossRef ] [ Google Scholar ]
• Molas-Gallart J., Tang P. (2011). Tracing “productive Interactions” to Identify Social Impacts: an Example from the Social Sciences . Res. Eval. 20 , 219–226. 10.3152/095820211X12941371876706 [ CrossRef ] [ Google Scholar ]
• Nowotny H., Scott P. B., Gibbons M. (Editors) (2001). Re-Thinking Science. Knowledge and the Public in an Age of Uncertainty . London: Sage Publications. [ Google Scholar ]
• Ochsner M., Hug S., Galleron I. (2017). The Future of Research Assessment in the Humanities: Bottom-Up Assessment Procedures . Palgrave Commun. 3 , 17020. 10.1057/palcomms.2017.20 [ CrossRef ] [ Google Scholar ]
• Olmos-Peñuela J., Benneworth P., Castro-Martínez E. (2015). Are Sciences Essential and Humanities Elective? Disentangling Competing Claims for Humanities' Research Public Value . Arts Humanities Higher Edu. 14 , 61–78. 10.1177/1474022214534081 [ CrossRef ] [ Google Scholar ]
• Peters H. P. (2013). Gap between Science and media Revisited: Scientists as Public Communicators . Proc. Natl. Acad. Sci. 110 , 14102–14109. 10.1073/pnas.1212745110 [ PMC free article ] [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Reale E., Avramov D., Canhial K., Donovan C., Flecha R., Holm P., et al. (2018). A Review of Literature on Evaluating the Scientific, Social and Political Impact of Social Sciences and Humanities Research . Res. Eval. 27 , 298–308. 10.1093/reseval/rvx025 [ CrossRef ] [ Google Scholar ]
• Reincke C. M., Bredenoord A. L., van Mil M. H. (2020). From Deficit to Dialogue in Science Communication . EMBO Rep. 21 , E51278. 10.15252/embr.202051278 [ PMC free article ] [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Rögener W., Wormer H. (2017). Defining Criteria for Good Environmental Journalism and Testing Their Applicability: An Environmental News Review as a First Step to More Evidence Based Environmental Science Reporting . Public Underst. Sci. 26 , 418–433. 10.1177/0963662515597195 [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Secko D. M., Amend E., Friday T. (2013). Four Models of Science Journalism . Journalism Pract. 7 , 62–80. 10.1080/17512786.2012.691351 [ CrossRef ] [ Google Scholar ]
• Sigurðarson E. S. (2020). Capacities, Capabilities, and the Societal Impact of the Humanities . Res. Eval. 29 , 71–76. 10.1093/reseval/rvz031 [ CrossRef ] [ Google Scholar ]
• Sörlin S. (2018). Humanities of Transformation: From Crisis and Critique towards the Emerging Integrative Humanities . Res. Eval. 27 , 287–297. 10.1093/reseval/rvx030 [ CrossRef ] [ Google Scholar ]
• Spaapen J., van Drooge L. (2011). Introducing “Productive Interactions” in Social Impact Assessment . Res. Eval. 20 , 211–218. 10.3152/095820211X12941371876742 [ CrossRef ] [ Google Scholar ]
• Star S. L., Griesemer J. R. (1989). Institutional Ecology, `Translations' and Boundary Objects: Amateurs and Professionals in Berkeley’s Museum of Vertebrate Zoology, 1907-39 . Soc. Stud. Sci. 19 , 387–420. 10.1177/030631289019003001 [ CrossRef ] [ Google Scholar ]
• Stehr N., Ruser A. (2017). Social Scientists as Technicians, Advisors and Meaning Producers . Innovation: Eur. J. Soc. Sci. Res. 30 , 24–35. 10.1080/13511610.2016.1207505 [ CrossRef ] [ Google Scholar ]
• van der Meulen B., Rip A. (2000). Evaluation of Societal Quality of Public Sector Research in the Netherlands . Res. Eval. 9 , 11–25. 10.3152/147154400781777449 [ CrossRef ] [ Google Scholar ]
• Weiss C. H. (1980). Knowledge Creep and Decision Accretion . Knowledge 1 , 381–404. 10.1177/107554708000100303 [ CrossRef ] [ Google Scholar ]
• Williams K. (2020). Playing the fields: Theorizing Research Impact and its Assessment . Res. Eval. 29 , 191–202. 10.1093/reseval/rvaa001 [ CrossRef ] [ Google Scholar ]
• Woolgar S. (2000). Social Basis of Interactive Social Science . Sci. Pub. Pol. 27 , 165–173. 10.3152/147154300781782039 [ CrossRef ] [ Google Scholar ]

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What can influence the quality of international collaborative publications: a case study of humanities and social sciences international collaboration in china’s double first-class project universities.

1. Introduction

2. literature review, 3. research design and data acquisition, 3.1. research hypothesis, 3.2. data samples, 3.3. model design, 4. empirical analysis, 4.1. descriptive analysis, 4.2. variable correlation and multicollinearity test, 4.3. analysis of the impact of international research collaboration papers based on the level of discipline standardization, 5. discussion and conclusions, author contributions, institutional review board statement, informed consent statement, data availability statement, conflicts of interest.

• Abramo, Giovanni, Ciriaco Andrea D’Angeloa, and Marco Solazzia. 2011a. Are researchers that collaborate more at the international level top performers? an investigation on the italian university system. Journal of Informetrics 5: 204–13. [ Google Scholar ] [ CrossRef ] [ Green Version ]
• Abramo, Giovanni, Ciriaco Andrea D’Angeloa, and Marco Solazzia. 2011b. The relationship between scientists’ research performance and the degree of internationalization of their research. Scientometrics 86: 629–43. [ Google Scholar ] [ CrossRef ]
• Adams, James D., Grant C. Black, J. Roger Clemmons, and Paula E. Stephan. 2005. Scientific Teams and Institution Collaborations: Evidence from U.S. Universities, 1981–1999 . Rochester: Social Science Electronic Publishing. [ Google Scholar ]
• Adams, Jonathan, Karen Gurney, and Stuart Marshall. 2007. Patterns of International Collaboration for the UK and Leading Partners. Available online: https://www.semanticscholar.org/paper/Patterns-of-International-Collaboration-for-the-UK-Adams-Gurney/44c3adfa0a6670c3dcd979e1bed18ed93632acb6 (accessed on 1 February 2021).
• Avkiran, Necmi Kemal. 1997. Scientific collaboration in finance does not lead to better quality research. Scientometrics 39: 173–84. [ Google Scholar ] [ CrossRef ]
• Barjak, Franz, and Simon Robinson. 2008. International collaboration, mobility and team diversity in the life sciences: Impact on research performance. Social Geography 3: 23–26. [ Google Scholar ] [ CrossRef ]
• Bordons, Maria, Isabel Gomez, M. Teresa Fernandez, M. Angeles Zulueta, and Aida Mendez. 1996. Local, Domestic and International Scientific Collaboration in Biomedical Research. Scientometrics 37: 279–95. [ Google Scholar ] [ CrossRef ]
• Bordons, María, Borja González-Albo, Javier Aparicio, and Luz Moreno. 2015. The influence of R&D intensity of countries on the impact of international collaborative research: Evidence from Spain. Scientometrics 102: 1–16. [ Google Scholar ]
• Carayol, Nicolas, and Mireille Matt. 2004. The exploitation of complementarities in scientific production process at the laboratory level. Technovation 24: 455–65. [ Google Scholar ] [ CrossRef ]
• Chang, Han-Wen, and Mu-Hsuan Huang. 2016. The effects of research resources on international collaboration in the astronomy community. Journal of the Association for Information Science and Technology 67: 2489–510. [ Google Scholar ] [ CrossRef ]
• Chinchilla-Rodríguez, Zaida, Cassidy R. Sugimoto, and Vincent Larivière. 2019. Follow the leader: On the relationship between leadership and scholarly impact in international collaborations. PLoS ONE 14: e0218309. [ Google Scholar ] [ CrossRef ] [ Green Version ]
• Chinchilla-Rodríguez, Zaida, Maria Benavent-Pérez, and Félix de Moya-Anegón. 2012. International collaboration in Medical Research in Latin America and the Caribbean (2003–2007). Journal of the American Society for Information Science and Technology 63: 2223–38. [ Google Scholar ] [ CrossRef ] [ Green Version ]
• De Dreu, Carsten K. W., and Michael Alun West. 2001. Minority Dissent and Team Innovation: The Importance of Participation in Decision Making. Journal of Applied Psychology 86: 1191–201. [ Google Scholar ] [ CrossRef ] [ PubMed ]
• Gazni, Ali, and Fereshteh Didegah. 2011. Investigating different types of research collaboration and citation impact: A case study of Harvard University’s publications. Scientometrics 87: 251–65. [ Google Scholar ] [ CrossRef ]
• Glänzel, Wolfgang, and András P. Schubert. 2001. Double effort = Double impact? A critical view at international co-authorship in chemistry. Scientometrics 50: 199–214. [ Google Scholar ] [ CrossRef ]
• Glänzel, Wolfgang, and Cornelius de Lange. 2002. A distributional approach to multinationality measures of international scientific collaboration. Scientometrics 54: 75–89. [ Google Scholar ] [ CrossRef ]
• Guerrero Bote, Vicente P., Carlos Olmeda-Gómez, and Félix de Moya-Anegón. 2013. Quantifying the benefits of international scientific collaboration. Journal of the American Society for Information Science & Technology 64: 392–404. [ Google Scholar ]
• Guo, Shesen, Ganzhou Zhang, and Yufei Guo. 2015. Social Network Analysis of 50 Years of International Collaboration in the Research of Educational Technology. Journal of Educational Computing Research . [ Google Scholar ] [ CrossRef ]
• He, Tianwei. 2009. Scientometric Indications of Chinese SCI Papers with International. Bulletin of National Natural Science Foundation of China 23: 93–97. [ Google Scholar ]
• Hsiehchen, David, Magdalena Espinoza, and Antony Hsieh. 2018. Evolution of collaboration and optimization of impact: Self-organization in multinational research. Scientometric 117: 391–407. [ Google Scholar ] [ CrossRef ]
• Jeong, Seongkyoon, Jae Young Choi, and Jaeyun Kim. 2011. The determinants of research collaboration modes: Exploring the effects of research and researcher characteristics on co-authorship. Scientometrics 89: 967–83. [ Google Scholar ] [ CrossRef ]
• Katz, J. Sylvan, and Ben R. Martin. 1997. What is research collaboration? Research Policy 26: 1–18. [ Google Scholar ] [ CrossRef ]
• Khor, Khiam Aik, and Ligen Yu. 2016. Influence of international co-authorship on the research citation impact of young universities. Scientometrics 107: 1095–110. [ Google Scholar ] [ CrossRef ] [ Green Version ]
• Kwiek, Marek. 2020. Internationalists and locals: International research collaboration in a resource-poor system. Scientometrics 124: 57–105. [ Google Scholar ] [ CrossRef ]
• Kyvik, Svein, and Ingvild Reymert. 2017. Research collaboration in groups and networks: Differences across academic fields. Scientometrics 113: 951–67. [ Google Scholar ] [ CrossRef ] [ PubMed ]
• Lancho-Barrantes, Bárbara S., Vicente P. Guerrero-Bote, and Felix de Moya-Anegon. 2013. Citation increments between collaborating countries. Scientometrics 94: 817–31. [ Google Scholar ]
• Leydesdorff, Loet, Lutz Bornmann, and Caroline S. Wagner. 2017. The relative influences of government funding and international collaboration on citation impact. Journal of the Association for Information Science and Technology 70: 198–201. [ Google Scholar ] [ CrossRef ] [ PubMed ] [ Green Version ]
• Merton, Robert K. 1968. The Matthew Effect in Science, The reward and communication systems of science are considered. Science 159: 56–63. [ Google Scholar ] [ CrossRef ]
• Narin, Francis, Kimberly A. Stevens, and Edith S. Whitlow. 1991. Scientific co-operation in Europe and the citation of multinationally authored papers. Scientometrics 21: 313–23. [ Google Scholar ] [ CrossRef ]
• Nguyen, Tuan V., Thao P. Ho-Le, and Ut V. Le. 2017. International collaboration in scientific research in Vietnam: An analysis of patterns and impact. Scientometrics 110: 1035–51. [ Google Scholar ] [ CrossRef ]
• Parker, Jan. 2007. Priorities for the future of Humanities in Europe: What can humanities contribute? Social Sciences Abroad 4: 98–100. [ Google Scholar ]
• Payumo, Jane, Taurean Sutton, Derek Brown, Dan Nordquist, Marc Evans, Danna Moore, and Prema Arasu. 2017. Input-output analysis of international research collaborations: A case study of five US universities. Scientometrics: An International Journal for All Quantitative Aspects of the Science of Science Policy 111: 1657–71. [ Google Scholar ] [ CrossRef ]
• Prakasan, E. R., Lalit Mohan, Priya Girap, Ganesh Surwase, B. S. Kademani, and K. Bhanumurthy. 2014. Scientometric facts on international collaborative Indian publications. Current Science 106: 166–69. [ Google Scholar ]
• Price, D., J. G. Sone, and Z. F. Dai. 1982. Small Science and Big Science . Singapore: World Science Publishing. [ Google Scholar ]
• Puuska, Hanna-Mari, Reetta Muhonen, and Yrjö Leino. 2014. International and domestic co-publishing and their citation impact in different disciplines. Scientometrics 98: 823–39. [ Google Scholar ] [ CrossRef ]
• Qiu, J. P., and Q. Zeng. 2013. Can international cooperation improve the influence of scientific research—Taking computer science as an example. Information Studies: Theory & Application 36: 1–5. [ Google Scholar ]
• Quan, Wei, Philippe Mongeon, Maxime Sainte-Marie, Rongying Zhao, and Vincent Larivière. 2019. On the development of China’s leadership in international collaborations. Scientometrics 120: 707–21. [ Google Scholar ] [ CrossRef ]
• Roosa, Leimu, and Koricheva Julia. 2005. Does scientific collaboration increase the impact of ecological articles? Bioence 5: 438–43. [ Google Scholar ]
• Suárez-Balseiro, Carlos, Carlos García-Zorita, and Elías Sanz-Casado. 2009. Multi-authorship and its impact on the visibility of research from Puerto Rico. Information Processing & Management 45: 469–76. [ Google Scholar ]
• Sud, Pardeep, and Mike Thelwall. 2016. Not all international collaboration is beneficial: The Mendeley readership and citation impact of biochemical research collaboration. Journal of the Association for Information Science and Technology 67: 1849–57. [ Google Scholar ] [ CrossRef ] [ Green Version ]
• Van Raan, Anthony. 1998. The influence of international collaboration on the impact of research results. Scientometrics 42: 423–28. [ Google Scholar ] [ CrossRef ]
• Wagner, Caroline S., Travis A. Whetsell, and Satyam Mukherjee. 2019. International research collaboration: Novelty, conventionality, and atypicality in knowledge recombination. Research Policy 48: 1260–70. [ Google Scholar ] [ CrossRef ]
• Wood, John, James Walter, and Kerry Carrington. 2007. The importance of social science to government. Social Sciences Abroad 4: 97–98. [ Google Scholar ]
• Yao, Jia Wen, Tie-Wu Jia, and Xiao-Nong Zhou. 2013. Assessing the correlation between international collaboration and academic influence in parasitic diseases: A case study of National Institute of Parasitic Diseases, Chinese Center for Disease Control and Prevention. Chinese Journal of Schistosomiasis Control 25: 367–74. [ Google Scholar ]
• Ye, W. P., W. Y. Liang, and Y. M. Hu. 2017. How far is C9 University from the world first class University. Education Research 38: 53–66. [ Google Scholar ]

Share and Cite

Cheng, Z.; Lu, X.; Xiong, X.; Wang, C. What Can Influence the Quality of International Collaborative Publications: A Case Study of Humanities and Social Sciences International Collaboration in China’s Double First-Class Project Universities. Soc. Sci. 2021 , 10 , 109. https://doi.org/10.3390/socsci10030109

Cheng Z, Lu X, Xiong X, Wang C. What Can Influence the Quality of International Collaborative Publications: A Case Study of Humanities and Social Sciences International Collaboration in China’s Double First-Class Project Universities. Social Sciences . 2021; 10(3):109. https://doi.org/10.3390/socsci10030109

Cheng, Zhe, Xingfu Lu, Xiong Xiong, and Chuanyi Wang. 2021. "What Can Influence the Quality of International Collaborative Publications: A Case Study of Humanities and Social Sciences International Collaboration in China’s Double First-Class Project Universities" Social Sciences 10, no. 3: 109. https://doi.org/10.3390/socsci10030109

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Home » Humanities Research – Types, Methods and Examples

Humanities Research – Types, Methods and Examples

Table of Contents

Humanities Research

Definition:

Humanities research is a systematic and critical investigation of human culture, values, beliefs, and practices, including the study of literature, philosophy, history, art, languages, religion, and other aspects of human experience.

Types of Humanities Research

Types of Humanities Research are as follows:

Historical Research

This type of research involves studying the past to understand how societies and cultures have evolved over time. Historical research may involve examining primary sources such as documents, artifacts, and other cultural products, as well as secondary sources such as scholarly articles and books.

Cultural Studies

This type of research involves examining the cultural expressions and practices of a particular society or community. Cultural studies may involve analyzing literature, art, music, film, and other forms of cultural production to understand their social and cultural significance.

Linguistics Research

This type of research involves studying language and its role in shaping cultural and social practices. Linguistics research may involve analyzing the structure and use of language, as well as its historical development and cultural variations.

Anthropological Research

This type of research involves studying human cultures and societies from a comparative and cross-cultural perspective. Anthropological research may involve ethnographic fieldwork, participant observation, interviews, and other qualitative research methods.

Philosophy Research

This type of research involves examining fundamental questions about the nature of reality, knowledge, morality, and other philosophical concepts. Philosophy research may involve analyzing philosophical texts, conducting thought experiments, and engaging in philosophical discourse.

Art History Research

This type of research involves studying the history and significance of art and visual culture. Art history research may involve analyzing the formal and aesthetic qualities of art, as well as its historical context and cultural significance.

Literary Studies Research

This type of research involves analyzing literature and other forms of written expression. Literary studies research may involve examining the formal and structural qualities of literature, as well as its historical and cultural context.

Digital Humanities Research

This type of research involves using digital technologies to study and analyze cultural artifacts and practices. Digital humanities research may involve analyzing large datasets, creating digital archives, and using computational methods to study cultural phenomena.

Data Collection Methods

Data Collection Methods in Humanities Research are as follows:

• Interviews : This method involves conducting face-to-face, phone or virtual interviews with individuals who are knowledgeable about the research topic. Interviews may be structured, semi-structured, or unstructured, depending on the research questions and objectives. Interviews are often used in qualitative research to gain in-depth insights and perspectives.
• Surveys : This method involves distributing questionnaires or surveys to a sample of individuals or groups. Surveys may be conducted in person, through the mail, or online. Surveys are often used in quantitative research to collect data on attitudes, behaviors, and other characteristics of a population.
• Observations : This method involves observing and recording behavior or events in a natural or controlled setting. Observations may be structured or unstructured, and may involve the use of audio or video recording equipment. Observations are often used in qualitative research to collect data on social practices and behaviors.
• Archival Research: This method involves collecting data from historical documents, artifacts, and other cultural products. Archival research may involve accessing physical archives or online databases. Archival research is often used in historical and cultural studies to study the past.
• Case Studies : This method involves examining a single case or a small number of cases in depth. Case studies may involve collecting data through interviews, observations, and archival research. Case studies are often used in cultural studies, anthropology, and sociology to understand specific social or cultural phenomena.
• Focus Groups : This method involves bringing together a small group of individuals to discuss a particular topic or issue. Focus groups may be conducted in person or online, and are often used in qualitative research to gain insights into social and cultural practices and attitudes.
• Participatory Action Research : This method involves engaging with individuals or communities in the research process, with the goal of promoting social change or addressing a specific social problem. Participatory action research may involve conducting focus groups, interviews, or surveys, as well as involving participants in data analysis and interpretation.

Data Analysis Methods

Some common data analysis methods used in humanities research:

• Content Analysis : This method involves analyzing the content of texts or cultural artifacts to identify patterns, themes, and meanings. Content analysis is often used in literary studies, media studies, and cultural studies to analyze the meanings and representations conveyed in cultural products.
• Discourse Analysis: This method involves analyzing the use of language and discourse to understand social and cultural practices and identities. Discourse analysis may involve analyzing the structure, meaning, and power dynamics of language and discourse in different social contexts.
• Narrative Analysis: This method involves analyzing the structure, content, and meaning of narratives in different cultural contexts. Narrative analysis may involve analyzing the themes, symbols, and narrative devices used in literary texts or other cultural products.
• Ethnographic Analysis : This method involves analyzing ethnographic data collected through participant observation, interviews, and other qualitative methods. Ethnographic analysis may involve identifying patterns and themes in the data, as well as interpreting the meaning and significance of social and cultural practices.
• Statistical Analysis: This method involves using statistical methods to analyze quantitative data collected through surveys or other quantitative methods. Statistical analysis may involve using descriptive statistics to describe the characteristics of the data, or inferential statistics to test hypotheses and make inferences about a population.
• Network Analysis: This method involves analyzing the structure and dynamics of social networks to understand social and cultural practices and relationships. Network analysis may involve analyzing patterns of social interaction, communication, and influence.
• Visual Analysis : This method involves analyzing visual data, such as images, photographs, and art, to understand their cultural and social significance. Visual analysis may involve analyzing the formal and aesthetic qualities of visual products, as well as their historical and cultural context.

Examples of Humanities Research

Some Examples of Humanities Research are as follows:

• Literary research on diversity and representation: Scholars of literature are exploring the representation of different groups in literature and how those representations have changed over time. They are also studying how literature can promote empathy and understanding across different cultures and communities.
• Philosophical research on ethics and technology: Philosophers are examining the ethical implications of emerging technologies, such as artificial intelligence and biotechnology. They are asking questions about what it means to be human in a world where technology is becoming increasingly advanced.
• Anthropological research on cultural identity: Anthropologists are studying the ways in which culture shapes individual and collective identities. They are exploring how cultural practices and beliefs can shape social and political systems, as well as how individuals and communities resist or adapt to dominant cultural norms.
• Linguistic research on language and communication: Linguists are studying the ways in which language use and communication can impact social and political power dynamics. They are exploring how language can reinforce or challenge social hierarchies and how language use can reflect cultural values and norms.

How to Conduct Humanities Research

Conducting humanities research involves a number of steps, including:

• Define your research question or topic : Identify a question or topic that you want to explore in-depth. This can be a broad or narrow topic, depending on the scope of your research project.
• Conduct a literature review: Before beginning your research, read extensively on your topic. This will help you understand the existing scholarship and identify gaps in the literature that your research can address.
• Develop a research methodology: Determine the methods you will use to collect and analyze data, such as interviews, surveys, archival research, or textual analysis. Your methodology should be appropriate to your research question and topic.
• Collect data: Collect data using the methods you have chosen. This may involve conducting interviews, surveys, or archival research, or analyzing primary or secondary sources.
• Analyze data: Once you have collected data, analyze it using appropriate methods. This may involve coding, categorizing, or comparing data, or interpreting texts or other sources.
• Draw conclusions: Based on your analysis, draw conclusions about your research question or topic. These conclusions should be supported by your data and should contribute to existing scholarship.
• Communicate your findings : Communicate your findings through writing, presentations, or other forms of dissemination. Your work should be clearly written and accessible to a broad audience.

Applications of Humanities Research

Humanities research has many practical applications in various fields, including:

• Policy-making: Humanities research can inform policy-making by providing insights into social, cultural, and historical contexts. It can help policymakers understand the impact of policies on communities and identify potential unintended consequences.
• Education: Humanities research can inform curriculum development and pedagogy. It can provide insights into how to teach critical thinking, cross-cultural understanding, and communication skills.
• Cultural heritage preservation: Humanities research can help to preserve cultural heritage by documenting and analyzing cultural practices, traditions, and artifacts. It can also help to promote cultural tourism and support local economies.
• Business and industry: Humanities research can provide insights into consumer behavior, cultural preferences, and historical trends that can inform marketing, branding, and product design.
• Healthcare : Humanities research can contribute to the development of patient-centered healthcare by exploring the impact of social and cultural factors on health and illness. It can also help to promote cross-cultural understanding and empathy in healthcare settings.
• Social justice: Humanities research can contribute to social justice by providing insights into the experiences of marginalized communities, documenting historical injustices, and promoting cross-cultural understanding.

Purpose of Humanities Research

The purpose of humanities research is to deepen our understanding of human experience, culture, and history. Humanities research aims to explore the human condition and to provide insights into the diversity of human perspectives, values, and beliefs.

Humanities research can contribute to knowledge in various fields, including history, literature, philosophy, anthropology, and more. It can help us to understand how societies and cultures have evolved over time, how they have been shaped by various factors, and how they continue to change.

Humanities research also aims to promote critical thinking and creativity. It encourages us to question assumptions, to challenge dominant narratives, and to seek out new perspectives. Humanities research can help us to develop empathy and understanding for different cultures and communities, and to appreciate the richness and complexity of human experience.

Overall, the purpose of humanities research is to contribute to a deeper understanding of ourselves, our communities, and our world. It helps us to grapple with fundamental questions about the human experience and to develop the skills and insights needed to address the challenges of the future.

When to use Humanities Research

Humanities research can be used in various contexts where a deeper understanding of human experience, culture, and history is required. Here are some examples of when humanities research may be appropriate:

• Exploring social and cultural phenomena: Humanities research can be used to explore social and cultural phenomena such as art, literature, religion, and politics. It can help to understand how these phenomena have evolved over time and how they relate to broader social, cultural, and historical contexts.
• Understanding historical events: Humanities research can be used to understand historical events such as wars, revolutions, and social movements. It can provide insights into the motivations, experiences, and perspectives of the people involved, and help to contextualize these events within broader historical trends.
• Promoting cultural understanding : Humanities research can be used to promote cross-cultural understanding and to challenge stereotypes and biases. It can provide insights into the diversity of human experiences, values, and beliefs, and help to build empathy and mutual respect across different cultures and communities.
• Informing policy-making: Humanities research can be used to inform policy-making by providing insights into social, cultural, and historical contexts. It can help policymakers understand the impact of policies on communities and identify potential unintended consequences.
• Promoting innovation and creativity : Humanities research can be used to promote innovation and creativity in various fields. It can help to generate new ideas, perspectives, and approaches to complex problems, and to challenge conventional thinking and assumptions.

Characteristics of Humanities Research

Some of the key characteristics of humanities research:

• Focus on human experience: Humanities research focuses on the study of human experience, culture, and history. It aims to understand the human condition, explore human values and beliefs, and analyze the ways in which societies and cultures have evolved over time.
• Interpretive approach: Humanities research takes an interpretive approach to data analysis. It seeks to understand the meaning behind texts, artifacts, and cultural practices, and to explore the multiple perspectives and contexts that shape human experience.
• Contextualization : Humanities research emphasizes the importance of contextualization. It seeks to understand how social, cultural, and historical factors shape human experience, and to place individual phenomena within broader cultural and historical contexts.
• Subjectivity : Humanities research recognizes the subjective nature of human experience. It acknowledges that human values, beliefs, and experiences are shaped by individual perspectives, and that these perspectives can vary across cultures, communities, and time periods.
• Narrative analysis : Humanities research often uses narrative analysis to explore the stories, myths, and cultural narratives that shape human experience. It seeks to understand how these narratives are constructed, how they evolve over time, and how they influence individual and collective identity.
• Multi-disciplinary: Humanities research is often interdisciplinary, drawing on a range of disciplines such as history, literature, philosophy, anthropology, and more. It seeks to bring together different perspectives and approaches to understand complex human phenomena.

Advantages of Humanities Research

Some of the key advantages of humanities research:

• Promotes critical thinking: Humanities research encourages critical thinking by challenging assumptions and exploring different perspectives. It requires researchers to analyze and interpret complex texts, artifacts, and cultural practices, and to make connections between different phenomena.
• Enhances cultural understanding : Humanities research promotes cross-cultural understanding by exploring the diversity of human experiences, values, and beliefs. It helps to challenge stereotypes and biases and to build empathy and mutual respect across different cultures and communities.
• Builds historical awareness: Humanities research helps us to understand the historical context of current events and social issues. It provides insights into how societies and cultures have evolved over time and how they have been shaped by various factors, and helps us to contextualize current social, political, and cultural trends.
• Contributes to public discourse: Humanities research contributes to public discourse by providing insights into complex social, cultural, and historical phenomena. It helps to inform public policy and public debate by providing evidence-based analysis and insights into social issues and problems.
• Promotes creativity and innovation: Humanities research promotes creativity and innovation by challenging conventional thinking and assumptions. It encourages researchers to generate new ideas and perspectives and to explore alternative ways of understanding and addressing complex problems.
• Builds communication skills: Humanities research requires strong communication skills, including the ability to analyze and interpret complex texts, artifacts, and cultural practices, and to communicate findings and insights in a clear and compelling way.

Limitations of Humanities Research

Some of the key limitations of humanities research:

• Subjectivity: Humanities research relies heavily on interpretation and analysis, which are inherently subjective. Researchers bring their own perspectives, biases, and values to the analysis, which can affect the conclusions they draw.
• Lack of generalizability : Humanities research often focuses on specific texts, artifacts, or cultural practices, which can limit the generalizability of findings to other contexts. It is difficult to make broad generalizations based on limited samples, which can be a challenge when trying to draw broader conclusions.
• Limited quantitative data : Humanities research often relies on qualitative data, such as texts, images, and cultural practices, which can be difficult to quantify. This can make it difficult to conduct statistical analyses or to draw quantitative conclusions.
• Limited replicability: Humanities research often involves in-depth analysis of specific texts, artifacts, or cultural practices, which can make it difficult to replicate studies. This can make it challenging to test the validity of findings or to compare results across studies.
• Limited funding: Humanities research may not always receive the same level of funding as other types of research. This can make it challenging for researchers to conduct large-scale studies or to have access to the same resources as other researchers in different fields.
• Limited impact : Humanities research may not always have the same level of impact as research in other fields, particularly in terms of policy and practical applications. This can make it challenging for researchers to demonstrate the relevance and impact of their work.

About the author

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Researcher, Academic Writer, Web developer

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William Gibbons, Leading Music Scholar, Joins RPI as Dean of Humanities, Arts, and Social Sciences

July 29, 2024

William Gibbons, Ph.D. will join Rensselaer Polytechnic Institute (RPI) as the new Dean of the School of Humanities, Arts, and Social Sciences (HASS) on August 1. 

A leading music scholar, Gibbons’ wide-ranging research explores the intersections of the arts, humanities, and technology in contemporary culture, especially in video games. He will help strengthen RPI’s unique, holistic approach to learning and discovery that foregrounds the human and social context of scientific and technological progress. 

Prior to joining RPI, Gibbons served as Dean of The Crane School of Music at SUNY Potsdam, one of the oldest and largest schools of music in the Northeast. At Crane, Gibbons directed the creation and revision of innovative new curricula, developed partnerships with industry leaders, and successfully acted as lead fundraiser for the school.

“We look forward to welcoming Will Gibbons to RPI,” said RPI Provost Rebecca Doerge, Ph.D. “The convergence of social sciences, the arts, technology, and the humanities in HASS creates a community of leaders and creators who uplift society. Will is joining us at an exciting time as we continue to celebrate RPI’s Bicentennial with some thrilling events in the months ahead.” 

“I am thrilled at this opportunity to join the team at HASS,” said Gibbons. “The humanities, arts, and social sciences are disciplines that explore essential questions — about who we are as individuals and groups, how we think and feel, what we value, and how our creative activity can improve the lives of those around us. Seeking answers to these questions is profoundly relevant to all of us, and I look forward to working with my colleagues to continue RPI’s incredible legacy of innovation, research, interdisciplinary, and creativity in these fields.”

In addition to dozens of books, articles, and chapters, Gibbons also co-edited the recent  Oxford Handbook of Video Game Music and Sound  (Oxford, 2024) as well as the essay collections  Music in Video Games  (Routledge, 2014) and  Music in the Role-Playing Game  (Routledge, 2020). His book  Unlimited Replays: Video Games and Classical Music  (Oxford, 2018) explores the relationship between games and the arts from the early arcade to the contemporary concert hall. 

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Before SUNY Potsdam, Gibbons served as Associate Dean of the College of Fine Arts at Texas Christian University, where he oversaw undergraduate and graduate programs in art, dance, design, fashion, music, and theater, and directed an interdisciplinary program in arts leadership and entrepreneurship. 

Gibbons holds a Ph.D. and M.A. in musicology from the University of North Carolina at Chapel Hill, as well as a B.A. in Music from Emory & Henry College.

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• Published: 13 July 2024

A global perspective on social stratification in science

• Aliakbar Akbaritabar   ORCID: orcid.org/0000-0003-3828-1533 1 ,
• Andrés Felipe Castro Torres 1 , 2 &
• Vincent Larivière 3  

Humanities and Social Sciences Communications volume  11 , Article number:  914 ( 2024 ) Cite this article

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To study stratification among scientists, we reconstruct the career-long trajectories of 8.2 million scientists worldwide using 12 bibliometric measures of productivity, geographical mobility, collaboration, and research impact. While most previous studies examined these variables in isolation, we study their relationships using Multiple Correspondence and Cluster Analysis. We group authors according to their bibliometric performance and academic age across six macro fields of science, and analyze co-authorship networks and detect collaboration communities of different sizes. We found a stratified structure in terms of academic age and bibliometric classes, with a small top class and large middle and bottom classes in all collaboration communities. Results are robust to community detection algorithms used and do not depend on authors’ gender. These results imply that increased productivity, impact, and collaboration are driven by a relatively small group that accounts for a large share of academic outputs, i.e., the top class. Mobility indicators are the only exception with bottom classes contributing similar or larger shares. We also show that those at the top succeed by collaborating with various authors from other classes and age groups. Nevertheless, they are benefiting disproportionately from these collaborations which may have implications for persisting stratification in academia.

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Introduction.

Science is a social enterprise with inequality among its agents (Chompalov et al. 2002 ; Kozlowski et al. 2022 ; Shrum et al. 2001 , 2007 ). Factors underpinning social stratification include differences within and between countries in institutional capacity and resources available for research (Castro Torres and Alburez-Gutierrez 2022 ), and inequalities among scholars according to gender (Akbaritabar and Squazzoni, 2020 ; Larivière et al. 2013 ), race and ethnicity (Kozlowski et al. 2022 ), migration status (Sanliturk et al. 2023 ; X. Zhao et al. 2023 ), and social class differences in opportunities to access higher education and research (Bourdieu and Passeron, 1979 ; Burris 2004 ; Clauset et al. 2015 ). Such overrepresentation of specific demographics in privileged positions within scientific systems are indicators of stratification (Alper 1993 ; Hofstra et al. 2022 ; Marini and Meschitti 2018 ). Differences in scholars’ strategies in the search for prestige can also influence inequalities in science (Leahey and Cain 2013 ). The durability of stratification depends, among other things, on taken-for-granted ideas about the necessity and benefits of hierarchical order—for example in terms of seniority, impact, or recognition. These taken-for-granted ideas also exist in the broader sphere of social and economic affairs. The belief that a market-oriented organization of the economy without state intervention is optimal legitimizes the existence of socioeconomic inequalities within and between societies (Mazzucato 2018 ; Pikkety 2019 ), which in turn contributes to sustaining social stratification among nations and individuals (Therborn 2013 ). In all likelihood, Science as a subfield of these broader social and economic relations, works analogously. Scientific research also is an inherently competitive endeavor, in which individual-based reputational incentives can undermine the motivation to collaborate (Müller 2012 ; Penman and Goldson 2015 ; van den Besselaar et al. 2012 ).

Inequalities in science are often justified by beliefs regarding the meritocratic nature of science and of academic success and the inherent value of truth. Several indicators, such as the number of publications and citations, help fuel these beliefs. While those are increasingly challenged by scholars from different perspectives (Sugimoto and Larivière 2018 ; Wilsdon et al. 2015 ), bibliometric measures remain used extensively. Moreover, in the context of assesment, those are mostly used in isolation and their interrelations are ignored.

This paper provides an assessment of stratification across fields of science based on a multivariate analysis of large-scale bibliometric information from 1996 to 2021 and highlights the interrelationships between bibliometric indicators. We argue that these interrelations provide a structural measure of inequalities in the scientific community beyond single variables gaps such as authors’ differences in the number of publications or citations. Because measuring inequalities is only a first step in understanding their potential underlying mechanisms, we make a dataset with country-level measures of scientific stratification publicly available for future research (Akbaritabar and Castro Torres 2024 ).

Existing inequalities in science

Data on scholars’ collaboration, geographical mobility, productivity, and citations suggest that academia is growing in absolute numbers and expanding geographically. There are more coauthored papers in recent years compared to earlier decades (Abramo et al. 2009 ; Melkers and Kiopa 2010 ; Wuchty et al. 2007 ), and more scholars experienced geographical mobility today than in the past (Sanliturk et al. 2023 ; Sugimoto et al. 2017 ; X. Zhao et al. 2023 ). Likewise, studies have shown that the number of scholarly publications has increased and that digitization has made searching and citing easier (Kozlowski et al. 2024 ; Lozano et al. 2012 ). Greater productivity and increased citation capacities enhanced academic works’ visibility and potential impact (Liu et al. 2018 ; Sinatra et al. 2016 ). Some of these analyses have pointed out that these rising trends are accompanied by an increased concentration of academic-success indicators among relatively few scholars (Ioannidis et al. 2018 ) or that increased collaboration and rate of productivity per individual has not increased (Fanelli and Larivière 2016 ).

According to the 28+ million publications indexed by Scopus (1996–2021), 33% of scholars have contributed to only one research paper throughout their careers, and the median number of authors per paper is two. This suggests that a few highly productive researchers may drive rising trends in scholars’ productivity reported in the literature (Fox and Nikivincze 2021 ; Ioannidis et al. 2018 ). Likewise, according to Scopus data, approximately 27.2% of the publications have only one author, and more than 75% are authored by scholars from one country, i.e., strictly national publications. Likewise, most authors (87.5%) have been affiliated with a single country throughout their careers, and 73.5% to a single sub-national region, that therefore experienced little geographical mobility (Akbaritabar et al. 2023 ; Sanliturk et al. 2023 ; X. Zhao et al. 2023 ). Similarly, 36.8% of authors have been actively publishing over only one year. These low shares call for a global investigation into whether claims of increased mobility, collaboration, productivity and impact are widespread phenomena, or remain concentrated among a small group of scholars. Bibliometric research has also shown that academic citations display a skewed distribution where only a very small share of publications, journals, and authors receive disproportionately high citations which has increased recently (Nielsen and Andersen 2021 ). These studies suggest that bibliometric indicators for academic-success are concentrated on a few countries, institutions, and authors.

In light of this evidence, the growth of scientific activities and its geographical expansion require a critical examination of their consequences for inequalities and global stratification. In fact, we know less about the interrelatedness of these trends than we know about them in isolation. Therefore, understanding inequalities in science requires a multidimensional approach. There might be positive or negative correlations, feedback effects, and synergistic connections among bibliometric measures of academic success including individual and collaborative productivity, national and international mobility, and research visibility as measured by citations.

For instance, more collaborations could lead to more citations, which in turn may translate into greater productivity and more opportunities for geographical mobility; greater mobility may expand scholars’ networks, enhancing their potential pool of collaborators. Conversely, mobility and changes of affiliation could also reflect negative conditions such as precarious research contracts and lack of opportunities for a life-long or long-term career. Further, multiple instances of mobility can destabilize one’s network of collaborations (Z. Zhao et al. 2020 ). The absence or lack of success in any of these realms may negatively affect performance in the others, as well as positive outcomes in any of these realms may boost success in others i.e., Matthew effect (Merton 1968 ). Social stratification in science will likely emerge from the confluence of successful (and unsuccessful) academic paths in these interrelated realms: productivity, collaboration, geographical mobility, and citations.

Materials and methods

We use 28.5 million articles and review publications indexed in Elsevier’s Scopus between 1996 and 2021. A proper disambiguation of author names is crucial for analysis such as ours that reconstructs publication trajectories over one’s career. Scopus identification numbers (Baas et al. 2020 ) are one of the few reliable options available (Aman 2018 ) and were used here to assign papers to authors and to identify groups of authors who publish together in the global network of co-authorship. We limit these publications to all of those written by the authors having identification numbers in Scopus and declared as “disambiguated” by Elsevier which has a 98.3% precision and a 90.6% recall (Baas et al. 2020 ). In addition to the evaluations by Elsevier (Baas et al. 2020 ), others have previously shown that Scopus author identification numbers are reliable in comparison to other sources (Aman 2018 ). We further disambiguate the academic affiliation of authors in this set of publications using the Research Organization Registry’s (ROR) Application Programming Interface (API) and geocode organizations’ addresses to subnational units (Akbaritabar 2021 ). This reduces our coverage of publications down from 33 to 28.5 million publications by 8.2 million disambiguated authors.

Author level variables and career-long measurement

To categorize scientists into specific groups and identify stratification processes, we reviewed the literature and selected the 12 most-widely used academic performance indicators. The list of indicators is as comprehensive as possible given existing data and it avoids, as much as possible, redundancy across measures. Together, these indicators provide a robust measure of individual-level academic performance. These are the most widely used measures in previous studies which have implemented them mostly in isolation without considering their interrelation.

While our analytical sample includes 8.2 million authors with at least one publication in the Scopus database, we excluded 41,278 authors (0.5%) because their publications have missing metadata. The list below provides each bibliometric indicator’s name and category: productivity, collaboration, mobility, and visibility. These indicators are computed at the author level and comprise all individual publications indexed by Scopus between 1996 and 2021; covering authors’ careers from one up to 25 years.

The number of coauthored papers, Num. coauthored pubs . ( collaboration/internationalization )

The average number of coauthors per paper in career, Avg. collaborations (as a measure for collaboration/internationalization )

The number of internationally coauthored publications, Num. intl. pubs ( collaboration/internationalization )

The number of nationally coauthored publications, Num. national pubs . ( collaboration/internationalization )

The number of international changes in academic affiliation, Num. intl. moves ( mobility )

The number of national changes in academic affiliation, Num nat. moves ( mobility )

The number of affiliated organizations, Num. organizations ( mobility )

The total number of citations, Total citations ( impact/visibility )

The average number of citations per paper in career, Avg. citations ( impact/visibility )

The fractional count of publications, Fractional pubs . ( productivity )

The number of publications, Total publications ( productivity )

The number of first-author publications, First author publications ( productivity )

To favor comparability among scholars, we standardize most indicators by authors’ academic age (age hereafter), measured as the years since their first publication in our database. However, the average number of coauthors per paper and the average number of citations per paper are not normalized by career age but, rather, the number of papers an author publishes throughout their career. Our goal with these two average measures, used in combination with the other 9 variables, is to further identify the effect of outliers in one’s career, such as highly cited papers or highly collaborative ones. To account for differences across disciplines in publication practices, we categorized researchers separately for each of the six macro fields of science according to the OECD classification by using the field where highest share of their publications appeared: Agricultural Sciences, Natural Sciences, Humanities, Medical and Health Sciences, Engineering and Technology, and Social Sciences.

By default, scholars with only one publication display lower variability across these 12 indicators compared to other groups. Because they published only one article, other measures such as national and international mobility, and the number of organizations are bound to zero and one, respectively. The number of citations, co-authors, and fractional count of papers are also limited to the information of the only published paper. Similarly, scholars who have publications in only one year in our data have lower bounds in these indicators. This limited heterogeneity reduces the influence of this group in our analysis despite their relatively high shares, ranging from 31% in the Natural Sciences to 47% in Engineering and Technology. In the Supplementary information (SI), we show separate figures for scholars with only one year of publication activity (Fig. S3 presents the share of one-year old authors). Instead of excluding this group from the analysis, as the usual practice in the literature, we decided for categorizing them under a specific age group to study the specificities of this understudied group.

Bibliometric variables are extremely skewed and the usual practice in the literature is to exclude outliers. As an example, publications with the highest number of authors are sometimes excluded (Nogrady 2023 ; Singh Chawla 2019 ). Here, to better capture non-linear relations across these indicators, and to reduce the influence of outliers, while keeping them in the analysis, all the indicators were categorized into the maximum possible number of categories ensuring relative frequencies of at least 2% in all categories. This categorization method maintains the essential characteristics of the continuous variables while mitigating the impact of outliers on correlation measures. This is achieved by grouping outliers into the lower- and bottom-end categories. This approach to variable coding is beneficial in the context of highly-skewed variables with heavy tails (see Fig. S2 ), as it allows us to: (i) include extreme values in the analysis, (ii) capture potential non-linear relationships among variables, (iii) preserve the distributional characteristics of each indicator, and (iv) avoids potential biases in correlational analyses due to outlier observations. The resulting number of categories across variables ranges from three for the number of international changes in academic affiliation in Agricultural Sciences (i.e., 95% of authors do not experience international mobility) to ten for the total number of citations in the Natural Sciences and Medical and Health Sciences (i.e., the 10th, 20th, …, 100th percentiles).

A multidimensional measure of social stratification within scientific communities

We run a Multiple Correspondence Analysis (Le Roux and Rouanet 2004 ) on the 12 categorized indicators for each macro field of science. Based on the Singular Value Decomposition of the matrix representing the 12 indicators, MCA yields individual-level numerical variables termed factorial axes. These factorial axes summarize the 12 indicators according to their multivariate correlations and relative importance. Due to the high number of categories of the 12 variables, our field-specific MCAs yield more than 50 factorial axes, most of which have very little informational value. We focus on the first three axes because their associated eigenvalues are significantly larger than the others, and therefore capture the most salient differences among scholars’ bibliometric performances (see Fig. S4 ).

Despite our age standardization, the first factorial axis of all MCAs came out as strongly correlated with scholars’ age and indicators of productivity, visibility, and collaboration. This result is partially due to the specificities of the one-year old group (e.g., reduced heterogeneity and very distinct profiles compared to older scholars), but also underscores the cumulative aspect of academic achievements with age. There is a clear age gradient in the first factorial axis for all age groups, not only the one year old, indicating that the incremental improvements in academic productivity, visibility, and collaboration grow as individuals progress in seniority.

Considering the significance of age in our study, and with the aim of improving comparability, we performed cluster analyses independently for six age groups: One-year-old, two to five, six to nine, 10 to 14, 15 to 20, and 21 to 25. Hence, we conducted 36 hierarchical clustering analyses (six macro fields of science multiplied by six age groups) based on the Ward method followed by a cluster consolidation via the K-means algorithms. Neighboring solutions with five, six, seven, and eight clusters were assessed using the ratio of between to total variance. These assessments led us to focus on a six-cluster solution (see SI). We term these clustering bibliometric classes and we use positional words to label them: bottom , low , mid-low , mid-high , high , and top . The marginal distribution of scholars across bibliometric classes measures the social stratification of science in each field. The differences between bibliometric classes in academic performance indicators capture the extent of hierarchies. We visualize these differences using factorial axes where distance implies differences and proximity implies similarity.

Network analysis of intra- and inter-class collaboration

To investigate whether members of identified bibliometric classes collaborate “within” their own class or with members of other classes and age groups, we construct global bipartite networks of co-authorship among the 8.2 million authors, identify its largest connected (giant) component and detect communities of densely collaborating scientists. In other words, we group authors into scientific communities according to their degrees of proximity in collaboration networks. Scholars that coauthor papers are maximally close, whereas authors without any coauthor in common are maximal distal. To identify communities, we use the Constant Potts Model (CPM) (Reichardt and Bornholdt 2004 ) and its extension to bipartite networks (Akbaritabar 2021 ; Akbaritabar and Barbato 2021 ; Traag et al. 2011 ) with a varying range of 18 resolution parameters. For robustness checks, we use three additional community detection algorithms from NetworKit (default algorithm, parallel Louvain, and parallel Label Propagation) and cross-check the identified communities. Additionally, we projected the bipartite network to a one-mode one, despite criticisms on such a projection and information loss it brings (Akbaritabar 2021 ; Akbaritabar and Barbato 2021 ), to use Leiden algorithm and results were robust and our storyline did not change (see SI).

We examine authors’ distribution across bibliometric classes within these identified scientific communities. For this analysis, we pooled all academic-age groups and compared the distribution of authors within each scientific community according to their academic age and bibliometric class. A side-by-side comparison of the bibliometric classes and academic-age distributions within scientific communities and entropy measures for these two distributions allows for assessing the nature and strength of stratification across scientific communities. Figure S1 presents the steps described above.

We represent social stratification in science and bibliometric classes using the first two MCA axes. We interpret these axes according to the variables’ percentage contribution to the variance, as displayed in Fig. 1 . A vertical line is drawn at the mean percentage contribution, i.e., 8.3%. Markers at the right of this vertical line indicate variables with above-average contributions to the axes’ variance. Different markers are used for each macro field of science.

The panels correspond to the first three factorial axes. The X-axis shows the variables' contribution to the axes' inertia. Markers' colors and shapes distinguish the OECD macro field of sciences. The vertical dashed line indicates the average percentage point contribution (100%/12 = 8%).

The variables that contribute the most to the first factorial axis are total publications, number of organizations, number of coauthored publications, average collaborations, and first-authored publications. Field differences are evident in the contribution of these variables to the first axis. For instance, in the Humanities (filled square), “Num. coauthored pubs.” and “Avg. collaborations” have a much lower contribution than “First author publications”, which can be explained by the fact that they are generally a non-collaborative field. The reverse is observed for the Social Sciences (filled diamond), where coauthored papers have a higher contribution to the first axis than first-author publications.

The first factorial axis correlates positively with academic age. This is a somewhat unexpected result given that we use indicators standardized by age. In all macro fields of science, there is an age-gradient in the first axis, and the mean coordinate of first and last age-groups are more than one standard deviation apart. There is no age gradient in any of the other axes. Therefore, when considering total publications, the number of organizations, coauthored publications, average collaborations, and first-author publications per year of age, senior scholars surpass their junior counterparts. In other words, the positive correlation between academic age and the first axis suggests that academic success accumulates with age, leading to progressively greater marginal gains. Thus, we labeled the first MCA axis as “Academic age, number of organizations, and individual productivity” despite the fact that age has not been used as an input in the MCA. A large coordinate in this axis represents older academic age, a relatively high number of organizations, and an above-average number of publications, as first-author in collaborations.

The variables that contribute the most to the second factorial axis are total, fractional (for some fields), and coauthored publications. In addition, the total number of citations and the number of national publications also contribute significantly to the second axis. We labeled the second axis as: “Total productivity, visibility, and collaborations.” Finally, the variables that contribute the most to the third factorial axis are first-authored publications, total publications, fractional publications, number of coauthored publications, and average collaborations. There is a large variety among fields of science in variables’ contributions to the third axis, yet, productivity and collaboration measures excel for their large contributions, particularly for the Humanities.

Hence, the organization of scholars according to their bibliometric indicators revolves around two main dimensions: “academic age, number of organizations, and individual productivity” on the one side, and “total productivity, visibility, and collaborations,” on the other. Scholars’ productivity is distinctly comprised in both dimensions. In the first dimension, productivity goes along with age and first-author publication. In the second dimension, productivity is less dependent on age and is associated with collaborations and citations. Interestingly, none of the mobility measures contribute significantly to the first three MCA axes that could stem from the very small share of mobile authors (about 8% in international and 12% in national moves).

Figure 2 displays authors’ distribution by fields of science according to the above-described main dimensions and the bibliometric classes detected via cluster analysis. Existing differences in academic practices (e.g., publication, collaboration, mobility, and citation) across fields of science require axes’ scales be free and prevent scaled comparisons across them. Authors with identical bibliometric measures are grouped and represented as circles to reduce overplotting. Circles’ size is proportional to the number of authors with identical bibliometric profiles. Although we conduct the analysis for all ages and find similar results across those (gray background circles), Fig. 2 highlights the bibliometric stratification of 15 to 20 year old scholars. The top group comprises the most successful authors based on combining our 12 bibliometric measures. The bottom-left includes those at the bottom of academic achievement indicators’ distributions.

Multiple Correspondence Analysis (MCA) results using the 12 most widely used bibliometric variables allowed identifying six classes of scientists from Bottom, Low, Middle low, Middle high, High, to Top. In all six fields of science and five-year career groups from a minimum of 1 to a maximum of 25 years of publication career indexed in Scopus, we see the same stratified structure appearing. A minority of the top class is identified which consists of less or about 10% (in most fields) of the most successful scientists indicated with dark red colors in the figure. See figures in Supplementary Information (SI) for other academic age groups and disaggregated analysis based on gender of authors to males and females which did not show a change in the reported trends.

The clustering of authors according to their academic achievement is a measure of existing inequalities in these fields of science. Despite disciplinary differences in size and scientific practices, the commonalities in the stratification of authors are notable. In all six fields of science, the top class comprises a minority whose share ranges from a minimum of 6% in Humanities to a maximum of 19% in Natural Sciences. The bottom class ranges from a minimum of 22% in Natural Sciences to a maximum of 32% in Engineering and Technology. On the contrary, the middle- and bottom classes unanimously position towards the bottom left quadrant, meaning they are always worse off in terms of 12 bibliometric measures investigated here.

This structure replicates among other academic-age groups (refer to figures in SI) with the exception of the one-year old. Scholars’ bibliometric stratification is most pronounced within the oldest age group (i.e., 21-to-25 years old) with bibliometric classes comprising more similar shares compared to bibliometric classes among 15-to-20-year-old scholars (refer to Fig. S10 ). This greater uniformity in the size of bibliometric classes indicates a possible cumulative effect of bibliometric performance over time. The 21-to-25 years old group represents scholars who have been actively publishing in Scopus-indexed journals for over 20 years. Thus, they are likely committed to the principles of scientific production, or at least, to the norms governing publication systems, including their penalties and rewards.

In contrast, a strong pyramidal structure (i.e., very small shares at the top classes) appears among scholars with shorter durations in the publishing system, such as those aged one year or two to five years. This strong pyramidal pattern may stem from their limited exposure to publication systems, hindering the establishment of distinct patterns. Consequently, the correlations, feedback mechanisms, and synergistic effects among bibliometric indicators are yet to manifest fully among these younger scholars.

This multivariate approach to academic performance and bibliometric classes challenges the so-called 20/80 rule, showing that it does not apply to all cases. To illustrate this point, Fig. 3 compares the bottom and top classes’ contribution to the total output in 10 metrics among 15 to 20-year-old scholars. The vertical axes represent the outcome share coming from each class, and the numbers at the top indicate class’ sizes. For example, the bottom class in Agricultural Sciences comprises 28% of the authors in our sample. These scholars contribute less than 5% of the total international publications. The scholars who are in the top class, 18%, instead, contribute more than 55%.

A multivariate approach to academic performance shows that the assumption that 80% of outputs are produced by the top 20% contributors (the so-called 20/80 rule) does not hold for bibliometric variables. The top classes in all macro fields of science account for less than 80% of the total outputs across 10 indicators. Bottom classes’ contributions are meager highlighting the extreme heterogeneity across academic careers. Both, top and bottom classes display similar contributions to geographical and institutional mobility.

Figure 3 shows that bottom classes comprise one fourth of authors in all macro fields and contribute less than 5% of the total in seven out of 10 indicators. The three exceptions are the number of organizations, and national and international moves which are measures of mobility. In fact, the share contribution of the bottom classes to these three outcomes is similar to that of the top class, except in the Humanities where bottom class scholars contribute much larger shares. These similarities indicate that mobility, both geographical and institutional, is associated with both success and failure in bibliometric performance. This is coherent with the literature highlighting positive and negative implications for mobility such as higher impact and less stable network of collaborations (Sugimoto et al. 2017 ; Z. Zhao et al. 2020 ).

In contrast, the top classes, between 6% and 19% of authors, lead the contributions to international publications in all macro fields of science. However, even in the Natural Sciences, where their share contribution is the highest, they are far from contributing 80%, meaning that the 20/80 rule does not hold under a multivariate approach to academic performance. The top classes also excel by their contribution to national publications, Coauthored papers, and total citations. Share contributions to other outcomes by the top class are generally lower, particularly for outcomes that imply some mobility or change of institutional affiliation as highlighted above. Figure S5 in the SI displays the shared contribution of all classes for the 10 outcomes.

Another aspect of these bibliometric classes is whether authors from different classes belong to the same research communities identified in the co-authorship network. Figure 4 shows the distribution of authors according to bibliometric classes (Panel A) and academic age groups (Panel B) across 19,970 scientific communities with at least 20 authors (99% of authors and 42.7% of communities). These communities are identified from the collaboration networks measured through co-authorship of publications (see more information in methods section). In panels A and B, scientific communities are represented by horizontal lines sorted from largest (on the top) to smallest and the deciles of the community-size distribution are indicated in the vertical axis. According to these panels, bibliometric-based stratification is similar to stratification based on age, suggesting that collaboration networks comprise authors of all ages and from all bibliometric classes. This similarity of bibliometric-class and academic age compositions is confirmed by Panel C, which displays the empirical density of the community-level entropy of authors’ distribution by bibliometric classes and age groups. We display results for three community detection scenarios out of 18 that were assessed, to maintain the figure’s clarity (see further robustness results including evaluation of authors’ country of affiliation and gender in SI). The fact that all density curves are strongly skewed towards high entropy values (max entropy = 1) confirms our visual assessment of Panels A and B and suggests our results are robust to different community detection scenarios and algorithms.

To investigate the trends shown in Fig. 2 further and control the collaboration structure among the classes, we turned to co-authorship networks of the studied 28 million publications. Networks of collaboration in terms of co-authoring scientific publications among 8.2 million authors worldwide allowed us to identify communities of collaboration. We used the Constant Potts Model (CPM) and its extension for bipartite networks with a varying range of 18 thresholds for the resolution parameter to detect communities. In all these detected communities (only 3 shown in the figure to preserve clarity), we investigated the class ( A ) and age ( B ) composition of members. Independent from the threshold used, all these communities have a heterogeneous composition of classes and age groups and analysis of entropies of this stratification ( C ) indicates an inter-class and inter-age collaboration structure among the most and least prolific, collaborative/internationalized, and mobile scientists. SI includes figures with further robustness analysis using three other community detection algorithms, one-mode projection of the network and results using Leiden (Traag et al. 2019 ) algorithm, and also disaggregated analysis based on gender of authors to males and females which did not show a change in the reported trends.

This paper provided a quantitative assessment of the global inequalities in science using bibliometric data across fields of science and research communities. Our results show that a stratified system in terms of bibliometric performance exists in all macro fields of science, and it is as strong as fields’ stratification by academic age. As scholars age (i.e., progress to more senior academic career stages) and maintain consistent participation in publication systems, their positioning within the bibliometric-based academic hierarchy becomes clearer. This clarity evolves potentially due to increased exposure and experience in publishing, highlighting the role of time and continued scholarly activity in shaping bibliometric classes. In addition, we evaluated collaboration ties among classes and whether specific age groups dominate it. We provide the aggregated data to enable future research on the causes and consequences of this stratification (Akbaritabar and Castro Torres 2024 ).

Our multivariate assessment of bibliometric classes is grounded in the assumption that scholars’ prestige within their respective fields does not rely solely on a single indicator, such as the number of citations or publications. Instead, we assume that scholars’ standing and prestige is based on their performance across multiple indicators. Consequently, the top class includes authors who may not necessarily rank at the highest levels in every individual indicator but possess the most favorable overall academic profiles. Similarly, the middle and lower classes encompass authors with varying degrees of less favorable academic profiles. This conceptualization of academic performance introduces nuances to the conventional 20/80 rule, demonstrating that it does not necessarily apply universally. It emphasizes that individual contributions to a particular output are more intricate than the notion that the top 20% contribute 80% of the outcome. We found that top classes, defined multidimensionally, contribute less than 80% in most of the cases. Bottom classes’ contributions are minimal suggesting the existence of very distinct academic careers. While the causes and implications of these disparities are yet to be examined, we speculate that differential access to resources and additional labor (Zhang et al. 2022 ) that could be higher among the top class and be perpetuated through additional funding and new resources allocated to them in performance-based funding schemes (Akbaritabar et al. 2021 ; Zacharewicz et al. 2019 ) could drive the persisting trends. The positive age pattern of bibliometric stratification suggest that these are no unlikely speculations. Greater exposure to publication systems and continued publishing activities likely serve as reinforcing mechanisms, contributing to the observed patterns of bibliometric stratification advancement over academic age.

Science is transmitted from established scholars to new generations through a mentorship relationship that affects mentees’ future success (Ke et al. 2022 ; Liénard et al. 2018 ; Ma et al. 2020 ). Such supervisor-supervisee relationships inherently have an age component. Hence, we expect that a share of observed scientific collaborations will be among junior and senior scholars. Nevertheless, our results show that the proportion of scholars who exit the system after only one paper amounts to 25% or more of the members of identified communities, which cannot be solely representing the age structure of academia and could be driven by the performance measures described and the hierarchical structure inherent in them that drives a high proportion to exit the system. We emphasize that not all graduate students continue the career paths in research leading to continued publication activity. Nonetheless, the probability of having higher impact and citations in the science system is disproportionately distributed and highly stratified (Nielsen and Andersen 2021 ).

Our study has a descriptive nature, despite the comprehensive inclusion of all most widely used bibliometric variables, their relationships, while considering academic age differences and fields of science. With the current descriptive setup, it is not possible to evaluate if the observed quantitative stratification signals inequality in access to resources such as research assistants and junior collaborators (Zhang et al. 2022 ). We do not know much about the type of contracts or positions these studied researchers hold; we only know their academic age. Similarly, the prestige of these academic institutions is not covered in our analysis, as well as the national policies that might affect the resources one accesses. These differences in resources and environment affect the type of research one can do and could lead to a different position on observational data i.e., bibliometric indicators. While our study sheds light on the stratifications because of its elaborated and comprehensive use of all relevant bibliometric variables, we did not have a causal setup and cannot evaluate the underlying causes leading to the reported stratifications and presented arguments on potential causes are based on our speculations.

Bibliometric indicators are widely used in national research assessment exercises (Akbaritabar et al. 2021 ; Zacharewicz et al. 2019 ) to determine who should be hired and promoted and whose research should be funded (Sugimoto and Larivière 2018 ). Based on our analysis, which was possible by adopting a global, multivariate, and multi-method framework to debunk the widely-spread myths about increased productivity, collaboration, internationalization, mobility, and impact among scientists, we call for a further elaborated investigation of these trends. We propose considering academic age, career cohorts and composition of a multitude of bibliometric variables instead of solely relying on one-indicator explanations which might be appealing to attract policy-makers’ attention, but might be detrimental to our understanding of the science system, its social structure, and its inherent stratification and intersectional inequalities (Kozlowski et al. 2022 ).

Data availability

All data to replicate presented results are publicly accessible under: Aliakbar Akbaritabar, & Castro Torres, A. F. (2024). Replication data for: A global perspective on social stratification in science (1.0). Zenodo. https://doi.org/10.5281/zenodo.12527944 .

Abramo G, D’Angelo CA, Di Costa F (2009) Research collaboration and productivity: Is there correlation? High Educ 57(2):155–171. https://doi.org/10.1007/s10734-008-9139-z

Article   Google Scholar  

Akbaritabar A (2021) A quantitative view of the structure of institutional scientific collaborations using the example of Berlin. Quant Sci Stud 2(2):753–777. https://doi.org/10.1162/qss_a_00131

Akbaritabar A, Barbato G (2021) An internationalised Europe and regionally focused Americas: A network analysis of higher education studies. Eur J Educ 56(2):219–234. https://doi.org/10.1111/ejed.12446

Akbaritabar A, Bravo G, & Squazzoni F (2021) The impact of a national research assessment on the publications of sociologists in Italy. Sci. Public Policy. scab013. https://doi.org/10.1093/scipol/scab013

Akbaritabar A, & Castro Torres AF (2024) akbaritabar/A-global-perspective-on-social-stratification-in-science: 1.0 (1.0) [Computer software]. Zenodo. https://doi.org/10.5281/zenodo.12527944

Akbaritabar A, & Squazzoni F (2020) Gender Patterns of Publication in Top Sociological Journals. Sci, Technol, Hum Values. https://doi.org/10.1177/0162243920941588

Akbaritabar A, Theile T, & Zagheni E (2023) Global flows and rates of international migration of scholars. MPIDR Working Paper , 018 . https://doi.org/10.4054/MPIDR-WP-2023-018

Akbaritabar A, & Castro Torres, AF (2024) Replication data for: A global perspective on social stratification in science (1.0). Zenodo. https://doi.org/10.5281/zenodo.12527944

Alper J (1993) The Pipeline Is Leaking Women All the Way Along. Science 260(5106):409–411. https://doi.org/10.1126/science.260.5106.409

Article   ADS   CAS   PubMed   Google Scholar  

Aman V (2018) Does the Scopus author ID suffice to track scientific international mobility? A case study based on Leibniz laureates. Scientometrics 117(2):705–720. https://doi.org/10.1007/s11192-018-2895-3

Baas J, Schotten M, Plume A, Côté G, Karimi R (2020) Scopus as a curated, high-quality bibliometric data source for academic research in quantitative science studies. Quant Sci Stud 1(1):377–386. https://doi.org/10.1162/qss_a_00019

Bourdieu P, & Passeron JC (1979) The Inheritors: French Students and Their Relation to Culture . University of Chicago Press

Burris V (2004) The Academic Caste System: Prestige Hierarchies in PhD Exchange Networks. Am Sociol Rev 69(2):239–264. https://doi.org/10.1177/000312240406900205

Castro Torres AF, Alburez-Gutierrez D (2022) North and South: Naming practices and the hidden dimension of global disparities in knowledge production. Proc Natl Acad Sci 119(10):e2119373119. https://doi.org/10.1073/pnas.2119373119

Article   CAS   PubMed   PubMed Central   Google Scholar  

Chompalov I, Genuth J, Shrum W (2002) The organization of scientific collaborations. Res Policy 31(5):749–767

Clauset A, Arbesman S, Larremore DB (2015) Systematic inequality and hierarchy in faculty hiring networks. Sci Adv 1(1):e1400005. https://doi.org/10.1126/sciadv.1400005

Article   ADS   PubMed   PubMed Central   Google Scholar  

Fanelli D, Larivière V (2016) Researchers’ Individual Publication Rate Has Not Increased in a Century. PLOS ONE 11(3):e0149504. https://doi.org/10.1371/journal.pone.0149504

Fox MF, Nikivincze I (2021) Being highly prolific in academic science: Characteristics of individuals and their departments. High Educ 81(6):1237–1255. https://doi.org/10.1007/s10734-020-00609-z

Hofstra B, McFarland DA, Smith S, Jurgens D (2022) Diversifying the Professoriate. Socius 8:23780231221085118. https://doi.org/10.1177/23780231221085118

Ioannidis JPA, Klavans R, Boyack KW (2018) Thousands of scientists publish a paper every five days. Nature 561(7722):167–169. https://doi.org/10.1038/d41586-018-06185-8

Ke Q, Liang L, Ding Y, David SV, Acuna DE (2022) A dataset of mentorship in bioscience with semantic and demographic estimations. Sci Data 9(1):1. https://doi.org/10.1038/s41597-022-01578-x

Article   CAS   Google Scholar  

Kozlowski D, Andersen JP, Larivière V (2024) The decrease in uncited articles and its effect on the concentration of citations. J Assoc Inf Sci Technol 75(2):188–197. https://doi.org/10.1002/asi.24852

Kozlowski D, Larivière V, Sugimoto CR, & Monroe-White T (2022) Intersectional inequalities in science. Proc Natl Acad Sci. 119(2). https://doi.org/10.1073/pnas.2113067119

Larivière V, Ni C, Gingras Y, Cronin B, Sugimoto CR (2013) Bibliometrics: Global gender disparities in science. Nature 504(7479):211–213. https://doi.org/10.1038/504211a

Article   PubMed   Google Scholar  

Le Roux B, & Rouanet H (2004) Geometric Data Analysis: From correspondence analysis to structured data analysis . Dordrecht

Leahey E, Cain CL (2013) Straight from the source: Accounting for scientific success. Soc Stud Sci 43(6):927–951. https://doi.org/10.1177/0306312713484820

Liénard JF, Achakulvisut T, Acuna DE, & David SV (2018) Intellectual synthesis in mentorship determines success in academic careers. Nat. Commun. 9(1), Article 1. https://doi.org/10.1038/s41467-018-07034-y

Liu L, Wang Y, Sinatra R, Giles CL, Song C, Wang D (2018) Hot streaks in artistic, cultural, and scientific careers. Nature 559(7714):7714. https://doi.org/10.1038/s41586-018-0315-8

Lozano GA, Larivière V, Gingras Y (2012) The weakening relationship between the impact factor and papers’ citations in the digital age. J Am Soc Inf Sci Technol 63(11):2140–2145. https://doi.org/10.1002/asi.22731

Ma Y, Mukherjee S, & Uzzi B (2020) Mentorship and protégé success in STEM fields. Proc Natl Acad Sci. https://doi.org/10.1073/pnas.1915516117

Marini G, Meschitti V (2018) The trench warfare of gender discrimination: Evidence from academic promotions to full professor in Italy. Scientometrics 115(2):989–1006. https://doi.org/10.1007/s11192-018-2696-8

Mazzucato M (2018) The entrepreneurial state: Debunking public vs. private sector myths . Penguin Books

Melkers J, Kiopa A (2010) The Social Capital of Global Ties in Science: The Added Value of International Collaboration: The Social Capital of Global Ties in Science. Rev Policy Res 27(4):389–414. https://doi.org/10.1111/j.1541-1338.2010.00448.x

Merton RK (1968) The Matthew Effect in Science. Science 159(3810):56–63. https://doi.org/10.1126/science.159.3810.56

Müller R (2012) Collaborating in Life Science Research Groups: The Question of Authorship. High Educ Policy 25(3):289–311. https://doi.org/10.1057/hep.2012.11

Nielsen MW & Andersen JP (2021) Global citation inequality is on the rise. Proc Natl Acad Sci. 118(7). https://doi.org/10.1073/pnas.2012208118

Nogrady B (2023) Hyperauthorship: The publishing challenges for ‘big team’ science. Nature 615(7950):175–177. https://doi.org/10.1038/d41586-023-00575-3

Penman D, Goldson S (2015) Competition to collaboration: Changing the dynamics of science. J R Soc N. Z 45(2):118–121. https://doi.org/10.1080/03036758.2015.1011172

Pikkety T (2019) Capital et idéologie (1st ed.). Seuil

Reichardt J, Bornholdt S (2004) Detecting fuzzy community structures in complex networks with a Potts model. Phys Rev Lett 93(21):218701. https://doi.org/10.1103/PhysRevLett.93.218701

Sanliturk E, Zagheni E, Dańko MJ, Theile T, Akbaritabar A (2023) Global patterns of migration of scholars with economic development. Proc Natl Acad Sci 120(4):e2217937120. https://doi.org/10.1073/pnas.2217937120

Shrum W, Chompalov I, Genuth J (2001) Trust, Conflict and Performance in Scientific Collaborations. Soc Stud Sci 31(5):681–730. https://doi.org/10.1177/030631201031005002

Shrum W, Genuth J, Carlson WB, Chompalov I, & Bijker WE (2007) Structures of Scientific Collaboration . MIT Press

Sinatra R, Wang D, Deville P, Song C, Barabasi A-L(2016) Quantifying the evolution of individual scientific impact. Science 354(6312):aaf5239. https://doi.org/10.1126/science.aaf5239

Article   CAS   PubMed   Google Scholar  

Singh Chawla D (2019) Hyperauthorship: Global projects spark surge in thousand-author papers. Nature. https://doi.org/10.1038/d41586-019-03862-0

Sugimoto CR, & Larivière V (2018) Measuring Research: What Everyone Needs to Know . Oxford University Press

Sugimoto CR, Robinson-Garcia N, Murray DS, Yegros-Yegros A, Costas R, Larivière V (2017) Scientists have most impact when they’re free to move. Nature 550(7674):29–31. https://doi.org/10.1038/550029a

Therborn G (2013) The killing fields of inequality . Polity

Traag VA, Van Dooren P, Nesterov Y (2011) Narrow scope for resolution-limit-free community detection. Phys Rev E 84(1):016114. https://doi.org/10.1103/PhysRevE.84.016114

Article   ADS   CAS   Google Scholar  

Traag VA, Waltman L, & van Eck NJ (2019) From Louvain to Leiden: Guaranteeing well-connected communities. Sci Rep 9(1), 5233. https://doi.org/10.1038/s41598-019-41695-z

van den Besselaar P, Hemlin S, van der Weijden I (2012) Collaboration and Competition in Research. High Educ Policy 25(3):263–266. https://doi.org/10.1057/hep.2012.16

Wilsdon J, Allen L, Belfiore E, Campbell P, Curry S, Hill S, Jones R, Kain R, Kerridge S, Thelwall M, Tinkler J, Viney I, Wouters P, Hill J, & Johnson B (2015) The Metric Tide: Report of the Independent Review of the Role of Metrics in Research Assessment and Management . https://doi.org/10.13140/RG.2.1.4929.1363

Wuchty S, Jones BF, Uzzi B (2007) The Increasing Dominance of Teams in Production of Knowledge. Science 316(5827):1036–1039. https://doi.org/10.1126/science.1136099

Zacharewicz T, Lepori B, Reale E, Jonkers K (2019) Performance-based research funding in EU Member States—A comparative assessment. Sci Public Policy 46(1):105–115. https://doi.org/10.1093/scipol/scy041

Zhang S, Wapman KH, Larremore DB, Clauset A (2022) Labor advantages drive the greater productivity of faculty at elite universities. Sci Adv 8(46):eabq7056. https://doi.org/10.1126/sciadv.abq7056

Zhao X, Akbaritabar A, Kashyap R, Zagheni E (2023) A gender perspective on the global migration of scholars. Proc Natl Acad Sci 120(10):e2214664120. https://doi.org/10.1073/pnas.2214664120

Zhao Z, Bu Y, & Li J (2020) Does the mobility of scientists disrupt their collaboration stability? J. Info Sci. 016555152094874. https://doi.org/10.1177/0165551520948744

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Acknowledgements

We thank Cassidy R. Sugimoto for helpful comments on an earlier version of this manuscript. This study has received access to the bibliometric data through the project “Kompetenznetzwerk Bibliometrie” and we acknowledge their funder Bundesministerium für Bildung und Forschung (grant number 16WIK2101A). AFCT received support from the Catalonian Goverment (grant number 2021 BP 00027). Open Access funding enabled and organized by Projekt DEAL.

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AA: Conceptualization, Methodology, Software, Validation, Data Curation, Formal analysis, Investigation, Writing - Original Draft, Writing - Review & Editing, Visualization. AFCT: Conceptualization, Methodology, Software, Validation, Formal analysis, Investigation, Writing - Original Draft, Writing - Review & Editing, Visualization. VL: Conceptualization, Writing - Original Draft, Writing - Review & Editing.

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Akbaritabar, A., Castro Torres, A.F. & Larivière, V. A global perspective on social stratification in science. Humanit Soc Sci Commun 11 , 914 (2024). https://doi.org/10.1057/s41599-024-03402-w

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Southern Humanities Conference, 2025

The Southern Humanities Conference, 2025

Call for Papers

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The Southern Humanities Conference offers an opportunity for scholars, artists, writers, musicians, performers, and humanists of all kinds to share their knowledge, research, work, and experiences in an interdisciplinary, welcoming, and engaging intellectual space.

For 2025 our conference theme will be “Real, Artificial, and Superficial.”  Human relationships in the twenty-first century are often marked by moments of genuine honesty and vulnerability as people seek ‘real’ connection as opposed to something ‘superficial.’  This desire to parse things real, artificial, and superficial—and to see the interstices between them—are central to experiences in the humanities, and perhaps, to the human experience.  In addition, researchers of all types seek to recover or expose reality in the world and submit it to a critical and evaluative process.  Yet, many recognize that subjective research can only reveal reality in partial, fragmentary, or illusory ways.  As Albert Einstein noted, “Reality is merely an illusion, albeit a very persistent one.”  Sorting through theoretical and practical discussions of the real and the artificial is central to many of the assumptions that undergird contemporary research and critical theory in the postmodern world.  And yet, the interplay between reality, the artificial and the superficial can be exceptionally productive for the creativity of writers, artists, dancers, and musicians.  Furthermore, one of the most important recent technological developments is artificial intelligence, where generative engines have raised questions about the nature of information and communication, as well as about how educators and researchers might engage with the artificial.  In fact, what are the boundaries between the artificial and the real? How intelligent is the artificial? And how superficial or real is artificial intelligence?  Jean Baudrilliard, whose key ideas included “simulation” and the “hyperreal” quipped, “The sad thing about artificial intelligence is that it lacks artifice and therefore intelligence.”  The alchemy between real, artificial, and superficial will serve as the prompt for our collective conversation, and offers us a platform for appraising the world around us.

The Southern Humanities Conference invites proposals for papers on any aspect of the theme “Real, Artificial, Superficial” broadly conceived.  Our conference themes are meant to be inspiring and prompt reflection, not limiting.  The topic is interdisciplinary and invites proposals from all areas of study, as well as creative pieces including but not limited to performance, music, art, and literature. Customary paper and full panel proposals are invited, as are ones for creative presentation formats like roundtables, workshops, and demonstrations. Moreover, the Southern Humanities Conference welcomes proposals from teachers and professionals outside the academy, as well as from scholars in the early stages of their academic careers.  Please note that the name of our organization simply reflects its having been founded in the U.S. South; no presenter is expected to present anything “southern,” though southern topics are also welcomed. Conference attendees come from all over the United States, Canada, and overseas.

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