research paper on historical context

• Source Criticism

What is historical context and why does it matter?

When you are analysing sources , it is important to remember that they were created at a time that is very different to our own.

As a result, they may describe things in very different ways. Source creators , particularly those of primary sources , will even say things that would be offensive today.

By examining the historical context, historians can gain a deeper understanding of the motivations and actions of people and groups in the past and can see how events and developments were shaped by the conditions and circumstances of the time. 

Additionally, understanding historical context can help to provide perspective and insight into the origins of current issues and trends.

What is 'historical context'?

Historical context is the awareness that the people who created sources were living at a time which may have held opinions and beliefs that are very different to what we consider ‘normal’.

Identifying historical context allows us to demonstrate historical empathy : to understand the different attitudes from the past without judging them.

For example:  

When reading an ancient Roman’s letter, they might say very derogatory things about slaves. Being aware of the historical context allows us to know that slavery was normal at the time and the things being said were not seen as ‘wrong’ to other Romans. Therefore, even though we do not condone slavery today, knowing the context allows us to appreciate the point of view of the primary source.  

Historical context is also being aware of the important events at the time that influenced the creation of the source.

Particular events often motivated people to create sources in a specific way.

The creator may have specifically mentioned certain people or events or used certain language because of an event which had recently occurred.

How do I determine a source’s context?

The first thing you need to know in order to contextualise a historical source is when the source was made .

Ensure that you are as precise as possible when identifying the date of creation : the century, decade, year, month and or day may help.

Secondly, once you know when it was created, you need to discover where it was created.

If a soldier wrote a letter in camp before battle, or a convict wrote a letter in a ship while in transit, or a newspaper printed a news report in a particular country town, can all become important to knowing the context of the source.

Thirdly, once you know when it was created, you need to discover what significant event occurred at that time.

Background research will be helpful in identifying this. Remember, you only care about events that directly influenced the creation of the source, not other events that occurred elsewhere in the world which are irrelevant.

Finally, carefully read the information in the source to identify specific language, ideas, and terminology that you need to learn more about in order to make sense of the source. Again, some background research might be required to understand any words with which you are unfamiliar.

John Smith’s letter to his parents was written on the 26th April, 1915: the day after the Gallipoli landings. This explains why he describes the Turkish defenders as “cruel murderers”. It is clear that he wrote this particular source to let his family know that he had survived the first day of battle.

The online newspaper article was written on the 13th February 2008, which was the same day as Kevin Rudd’s official apology speech to the indigenous peoples of Australia. This explains why the article focuses on the history of the Stolen Generations and mentions the “small ounce of relief of the thousands who will be present today”.

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How to Write a History Research Paper

In my last post, I shared some tips on how to conduct research in history and emphasized that researchers should keep in mind a source’s category (transcript, court document, speech, etc.). This post is something of a sequel to that, as I will share some thoughts on what often follows primary-source research: a history research paper. 

1. Background Reading   The first step to a history research paper is of course, background reading and research. In the context of a class assignment, “background reading” might simply be course readings or lectures, but for independent work, this step will likely involve some quality time on your own in the library. During the background reading phase of your project, keep an eye out for intriguing angles to approach your topic from and any trends that you see across sources (both primary and secondary).

2. T hemes and Context Recounting the simple facts about your topic alone will not make for a successful research paper. One must grasp both the details of events as well as the larger, thematic context of the time period in which they occurred. What’s the scholarly consensus about these themes? Does that consensus seem right to you, after having done primary and secondary research of your own?

3. Develop an Argument  Grappling with answers to the above questions will get you thinking about your emerging argument. For shorter papers, you might identify a gap in the scholarship or come up with an argumentative response to a class prompt rather quickly. Remember: as an undergraduate, you don’t have to come up with (to borrow Philosophy Professor Gideon Rosen’s phrase) ‘a blindingly original theory of everything.’ In other words, finding a nuanced thesis does not mean you have to disprove some famous scholar’s work in its entirety. But, if you’re having trouble defining your thesis, I encourage you not to worry; talk to your professor, preceptor, or, if appropriate, a friend. These people can listen to your ideas, and the simple act of talking about your paper can often go a long way in helping you realize what you want to write about.

4. Outline Your Argument  With a history paper specifically, one is often writing about a sequence of events and trying to tell a story about what happened. Roughly speaking, your thesis is your interpretation of these events, or your take on some aspect of them (i.e. the role of women in New Deal programs). Before opening up Word, I suggest writing down the stages of your argument. Then, outline or organize your notes to know what evidence you’ll use in each of these various stages. If you think your evidence is solid, then you’re probably ready to start writing—and you now have a solid roadmap to work from! But, if this step is proving difficult, you might want to gather more evidence or go back to the thesis drawing board and look for a better angle. I often find myself somewhere between these two extremes (being 100% ready to write or staring at a sparse outline), but that’s also helpful, because it gives me a better idea of where my argument needs strengthening.

5. Prepare Yourself   Once you have some sort of direction for the paper (i.e. a working thesis), you’re getting close to the fun part—the writing itself. Gather your laptop, your research materials/notes, and some snacks, and get ready to settle in to write your paper, following your argument outline. As mentioned in the photo caption, I suggest utilizing large library tables to spread out your notes. This way, you don’t have to constantly flip through binders, notebooks, and printed drafts.

In addition to this step by step approach, I’ll leave you with a few last general tips for approaching a history research paper. Overall, set reasonable goals for your project, and remember that a seemingly daunting task can be broken down into the above constituent phases. And, if nothing else, know that you’ll end up with a nice Word document full of aesthetically pleasing footnotes!

— Shanon FitzGerald, Social Sciences Correspondent

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"Historical Context" in Historical Context: Surface, Depth, and the Making of the Text

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Johannes Junge Ruhland , Victoria Zurita

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There is no interpretation without contextualisation. Few scholars would question this statement, not least because including information provided by the context (broadly construed) is pervasive in interpretations across theories as divergent as New Criticism and New Historicism. Whereas there can be no doubt as to the importance of ›context‹, some rather crucial issues concerning text and context have prompted disagreement, if they have been addressed at all. The term ›context‹ itself requires clarification since it is often used rather differently and with a meaning that remains vague. It is a matter of debate which contexts are relevant to interpretation. Various models of how text and context interact have been suggested in different theories of literature. Taken together, issues such as these constitute a fundamental problem of literary theory today.

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The Importance of Historic Context in Analysis and Interpretation

Print Collector/Getty Images

• M.Ed., Education Administration, University of Georgia
• B.A., History, Armstrong State University

Historical context is an important part of life and literature, and without it, memories, stories, and characters have less meaning. Historical context deals with the details that surround an occurrence. In more technical terms, historical context refers to the social, religious, economic, and political conditions that existed during a certain time and place. Basically, it's all the details of the time and place in which a situation occurs, and those details are what enable us to interpret and analyze works or events of the past, or even the future, rather than merely judge them by contemporary standards.

In literature, a strong understanding of the historical context behind a work's creation can give us a better understanding of and appreciation for the narrative . In analyzing historical events, context can help us understand what motivates people to behave as they did.

Put another way, context is what gives meaning to the details. It's important, however, that you don't confuse context with cause. Cause is the action that creates an outcome; context is the environment in which that action and outcome occur.

Words and Deeds

Whether dealing with fact or fiction, historical context is important when interpreting behavior and speech. Consider the following sentence which, devoid of context, sounds innocent enough:

"Sally hid her hands behind her back and crossed her fingers before she answered."

But imagine that this statement comes from a transcript of court documents in Salem, Massachusetts, in 1692 during the famed Salem Witch Trials . Religious fervor was at an extreme, and villagers were nearly obsessed with the devil and witchcraft. At that time, if a young woman were to tell a lie, it was fodder for hysteria and a violent reaction. A reader would assume that poor Sally was a candidate for the gallows.

Now, imagine you're reading a letter from a mother that contains this sentence:

"My daughter will be heading to California shortly after she marries."

How much information does this statement give us? Not much, until we consider when it was written. Should we discover that the letter was written in 1849, we will realize that one sentence can sometimes say a lot. A young woman heading for California in 1849 might be following her husband on a treacherous treasure-seeking expedition for the gold rush. This mother would probably be quite fearful for her child, and she would know that it would be a very long time before she'd see her daughter again, if ever.

Historical Context in Literature

No work of literature can be fully appreciated or understood without historical context. What may seem nonsensical or even offensive to contemporary sensibilities, might actually be interpreted in a completely different manner by considering the era it is from.

A good example is Mark Twain's " Adventures of Huckleberry Finn ," published in 1885. It is considered an enduring work of American literature and a biting social satire. But it is also criticized by modern critics for its casual use of a racial epithet to describe Huck's friend Jim, a freedom-seeking enslaved person. Such language is shocking and offensive to many readers today, but in the context of the day, it was​ the commonplace language for many.

Back in the mid-1880s, when attitudes toward newly liberated enslaved African Americans were often indifferent at best and hostile at worst, the casual use of such racial epithets wouldn't have been considered unusual. In fact, what is actually more surprising, given the historical context of when the novel was written, is Huck's treating Jim not as his inferior but as his equal—something rarely portrayed in the literature of the time.

Similarly, Mary Shelley's " Frankenstein"  cannot be fully appreciated by a reader who is unaware of the Romantic movement that took place in art and literature in the early 19th century. It was a time of rapid social and political upheaval in Europe when lives were transformed by the technological disruptions of the Industrial Age.

The Romantics captured the public's sense of isolation and fear that many experienced as a result of these social changes. "Frankenstein" becomes more than a good monster story, it becomes an allegory for how technology can destroy us.

Other Uses of Historical Context

Scholars and educators rely on historical context to analyze and interpret works of art, literature, music, dance, and poetry. Architects and builders rely on it when designing new structures and restoring existing buildings. Judges may use it to interpret the law, historians to understand the past. Any time critical analysis is required, you may need to consider historical context as well.

Without historical context, we are only seeing a piece of the scene and not fully understanding the influence of the time and place in which a situation occurred.

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A Literature Research Guide - Historical Context Research: Historical Background

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American Contexts

Colonial America 1607-1763

Early Republic 1783-1861

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Chaucer 1340's-1400.

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Author "in Context" sourcebooks   can identify key cultural and intellectual influences as well as the social, political, and historical context the author was working in.  These sourcebooks do not usually include primary sources, but they provide references and background information and may mention influential texts.  To find author sourcebooks, search the  library catalog  below using the author's name and  "in context" .    For example: Emily Dickinson in context

Article Databases:

• History Reference Source This link opens in a new window Subject: History History-related books, periodicals, documents, videos, biographies, photos, and maps; some full-text from 1917-current.
• US Major Dailies This link opens in a new window Subject: Business, Language, Literature, and Communication Contains full text of the New York Times (including the Book Review and Magazine), Wall Street Journal, The Chicago Tribune, LA Times, and the Washington Post.
• Humanities International Index This link opens in a new window Subjects: Art & Design, Music, Theatre Arts, Languages, Literature & Mass Communication Indexing (some full-text) of journal articles, books, reference works, poems, fiction, photographs, paintings and illustrations in the humanities from 1925 to present; constructs bibliography in five different citation styles.

Subjects: Biological Sciences, Art & Design, Business, Music, Theatre Arts Full-text peer-reviewed journal articles in the humanities and sciences from 1831-"moving wall" (generally 3 to 5 years). Note: most recent 3-5 years are not included. Articles which are not available in our subscription may be requested via InterLibrary Loan.

JSTOR has provided complimentary access during Covid to JSTOR Archives & Primary Source Collections until June 30, 2021.

• OmniFile Select This link opens in a new window Subject: Academic Journals for all subjects Some full-text to multidisciplinary journals and magazines from 1994-current.

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• UOW Library

Finding historical information

Starting your research, think about the broader historical context.

• Gather background information & identify your knowledge gaps
• Understand what "primary" & "secondary" sources mean
• Start with reading lists, references & footnotes
• Activity & self-assessment
• Searching collections
• Identifying historical evidence
• Finding biographies

What you can learn from this page:

• Establishing your topic within its broader historical context
• Understanding primary vs secondary sources
• Reading lists, reference lists and footnotes are helpful starting points

When you want to research a topic from the past, it's important to place that topic within its broader historical context.

Think about:

• related events
• political issues
• societal issues

This helps you recognise the significance of any historical sources you might find, and interpret the source's information.

Then identify what you already know about the subject and what you need to clarify. Lastly, make sure you understand what primary and secondary sources are, where to find them  and how these terms are relative to the time period, intended usage and subject discipline.

Gather background information & identify your knowledge gaps

Start by listing any key facts and helpful points that you already know (for example people, organisations or movements, dates, events, places or main issues).

As well as listing your starting points, you should list anything you're unsure of and that you need to confirm or clarify.

You may have lots of unanswered questions at this very early stage of your research and that's OK.

• Historical overviews in Trove This curated list shows you search tips and examples of the types of historical overviews and timelines you can find from websites and books to help you get started.

Understand what "primary" & "secondary" sources mean

Primary sources.

Primary sources are records of firsthand accounts (autobiographies, documentary history books, interviews in contemporary newspapers, government reports).

Primary sources provide us with a real sense of what was happening with a person, event or specific period in time.  

Secondary sources

Secondary sources are secondhand accounts which analyse and interpret past events using primary sources (books, textbooks, journal articles).

Secondary sources provide us with historical definitions and overviews; they are usually written at a much later time after the historical event or era and draw together a range of useful comments and other relevant information.  

Recognise your sources in the appropriate context

Sometimes it can be hard to decide if something may be a primary source or not. Sometimes a secondary source can also serve as a primary source, depending on the context in which you're viewing it and wanting to use it.

For example, a well known author writes a journal article discussing a particular historical event; their article would be considered a secondary source about that historical event. Years later a biographer is researching the life of that author; in this context that same journal article would serve as a primary source example of that author's written works.

Chances are, that you're familiar with a variety of primary and secondary sources and use them in everyday life. However, locating primary sources about an academic topic can sometimes be difficult.

Primary sources are first-hand accounts of an event and are created during the time that event took place. They can also be created retrospectively at a later date by a participant in those events. They are original documents and usually don't describe or analyse other documents. They can also be creative works.

Some examples of primary sources are:

• laws and court documents
• diaries, memoirs, autobiographies and letters
• works of art
• novels and plays
• original research and data
• historical newspapers

So how can primary sources be used for research?

They can be used as a focal point of a discussion about events. They can be used to back up claims or criticisms. They can be used as evidence for series and research, and they can be used to gain historical perspectives on the topic.

Secondary sources are written by scholars and observers after the fact and interpret or analyse primary sources or events. These sources are at least one step removed from what they are describing. Some examples of secondary sources are:

• encyclopedias
• essays and reviews
• magazines or journal articles which analyze events or ideas
• books which provide a summary of events or synthesize information for many primary sources

So how are secondary sources used?

They can be used to get background information and understand the scope of a topic. They can be used to see what others have discussed or get opinions. You can use them to learn how recent events affect or fit into the larger picture and they can help you understand the significance of events, data, works of literature and art.

Let's look at an example: a primary source for a paper about the placebo effect could be data from a medical trial which is published in an academic journal. Secondary sources for this topic could include books about medication, the placebo effect and health in general, or websites which define various anxiety disorders.

One thing to keep in mind is that a source's classification as either "primary" or "secondary" can change depending on the topic that you're studying. For example, if you are writing about how the news is being represented on the internet, a news site like CNN might be considered a primary source. If you're studying news on the internet, cnn.com represents the object that you're studying.

However, if you're writing about political elections and you find an article on cnn.com that analyses them, the article will be considered a secondary source, since, in this case, you're studying the elections, an article on cnn.com is one step removed from your topic.

Remember...

For an effective research paper, try to use both primary and secondary sources that are an original source of data, historical information or creative works, as well as secondary sources which summarize, analyse or comment on ideas or events.

Start with reading lists, references & footnotes

Check your subject reading lists for details of key primary and secondary sources your lecturers may expect you to read.

Check the footnotes and bibliographies of the books and articles you're reading for background information.

Activity & self-assessment

Where and how will you look for an historical overview or background information to help you better understand your broader topic area? You may like to practice your skills with our tutorial below.

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• Last Updated: Apr 15, 2024 3:41 PM
• URL: https://uow.libguides.com/finding-historical-information

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• Front Psychol

Putting Stress in Historical Context: Why It Is Important That Being Stressed Out Was Not a Way to Be a Person 2,000 Years Ago

Fabian hutmacher.

1 Department of Psychology, University of Regensburg, Regensburg, Germany

2 Human-Computer-Media Institute, University of Würzburg, Würzburg, Germany

It was not until the middle of the twentieth century that scientists and Western societies began to label the combination of physiological and psychological responses that people display when things are getting too much and out of balance as “stress.” However, stress is commonly understood as a universal mechanism that exists across times and cultures. In a certain sense, this universality claim is correct: the physiological and endocrinological mechanisms underlying the stress response are not a modern invention of our body. In another sense, the universality claim is potentially problematic: stress has become, but has not always been, a way to be a person. That is, the social practices, in which the physiological and endocrinological stress mechanisms are embedded, are not the same across times and cultures. Crucially, these social practices are not a negligible by-product, but form an essential part of the way stress is commonly understood and experienced. Against this background, one may still decide to use the word “stress” when speaking about other times and cultures. Nevertheless, one should at least be cautious when doing so for three reasons. First, using the word “stress” when referring to societies different from our own may create the impression of a similarity between then and now, which does not actually exist. Second, it may blind us to the nature of the differences between times and cultures. Third, it naturalizes a contemporary scientific concept, which is more adequately viewed as the result of complex social, historical, and societal processes. Putting the stress concept in historical context and acknowledging that its use emerged in a specific historical environment enables us to take a step back and to think about the ways that stress shapes our lives. In other words, viewing stress as a culture-bound concept can give us the possibility to reflect upon our modern societies, in which the concept emerged.

Introduction

It is hard to determine precisely when the history of the stress concept begins (for an overview, see e.g., Kugelmann, 1992 ; Doublet, 2000 ; Cooper and Dewe, 2004 ; Jackson, 2013 ). Predecessors like George M. Beard’s “neurasthenia” or Walter B. Cannon’s idea of “homeostasis” can be traced back to the end of the nineteenth and beginning of the twentieth century ( Beard, 1869 ; Cannon, 1929 ). Note, that the “godfather of stress,” Hans Selye, did not use the term stress in his first publication about the general adaptation syndrome (GAS; Selye, 1936 ). Although the GAS is generally considered the starting point for the development of his stress theory, it was not before the 1950s that stress was regularly adopted as a scientific term. As Kugelmann (1992 , p. 54) put it: “Before the war [i.e., the Second World War], no one spoke of stress; after it, increasingly, everyone did.” However, what is stress believed to be, after all?

This question is not easy to answer as stress is not a narrow term with a fixed meaning: “Stress is a term that causes psychologists headaches. There is a great deal of controversy over what the term means” ( Martin et al., 2013 , p. 682). Hans Selye, for instance, changed his definition of stress several times ( Viner, 1999 ; Jackson, 2013 ). More generally speaking, stress is either seen as an aversive stimulus we are exposed to, as the response we show in reaction to this stimulus or as an interactional process , assuming that it is the “lack of fit between the environment and a person” ( Mulhall, 1996 , p. 459) that makes certain situations stressful. Apart from that, the concept of stress connects research findings from genetics, biology, medicine, and psychology and relates them not only to the individual but also to institutional and societal structures. Thus, stress seems to be a very broad, notoriously fuzzy, and versatile, a “protean concept” ( Becker, 2013 , p. 2) – a concept that is able to “incorporate a wide range of themes” ( Pollock, 1988 , p. 387). Put differently, the way that the stress concept is defined and investigated depends on the specific approach and the interests of the individual researcher.

However, this overall impression does not help to answer the question as to whether there is at least some consensus about what stress actually is. What might help is to look at various introductory books to psychology and to see how stress is defined there. Such an approach does not necessarily reveal the “truth” about stress. As textbooks provide a condensed summary of the current academic discourse, they can nevertheless give us a good impression of the way stress is commonly understood in contemporary psychology (see e.g., Smyth, 2004 , for an elaboration of how stress as a concept emerged in psychology textbooks). Interestingly, the definitions used in the textbooks seem to share three crucial features.

First, all of them roughly describe stress as the notion that things are getting too much and out of balance . People are stressed out because of “specific events or chronic pressures that place demands on a person or threaten the person’s well-being” ( Schacter et al., 2014 , p. 550; for similar descriptions, see Eysenck, 2009 , p. 87; Martin et al., 2013 , p. 682; Ciccarelli and White, 2018 , p. 462). Stress “is the pattern of response an organism makes to stimulus events that disturb its equilibrium and tax or exceed its ability to cope” ( Gerrig, 2013 , p. 333). In other words, “[s]tress occurs when aspects of the environment overwhelm people. That is, people feel stressed when too much is expected of them, or when events seem scary or worrisome” ( Gazzaniga and Heatherton, 2003 , p. 336).

Second, the individual’s response to stress is viewed as a complex pattern, which “is made up of a diverse combination of reactions taking place on several levels, including physiological, behavioral, emotional, and cognitive” ( Gerrig, 2013 , p. 333; similar descriptions can be found in Gazzaniga and Heatherton, 2003 , p. 334; Eysenck, 2009 , p. 87; Schacter et al., 2014 , p. 550; Ciccarelli and White, 2018 , p. 462). As Martin et al. (2013 , p. 682) puts it: “In general terms, stress is a pattern of physiological, behavioural, emotional, and cognitive responses to real or imagined stimuli that are perceived as preventing a goal or endangering or otherwise threatening well-being.” Expressed differently, the inseparable combination of physiological and psychological factors is what constitutes stress.

Third, stress is believed to be “a common component of everyday emotional life” ( Gazzaniga and Heatherton, 2003 , p. 334) as “[e]very organism faces challenges from its external environment and from its personal needs” ( Gerrig, 2013 , p. 332), ranging from major life events, such as a natural catastrophe or the death of a close family member to daily hassles, which are all those “personal events that affect the comfortable pattern of our lives and little annoyances that bug us day after day” ( Schacter et al., 2014 , p. 550). Expressed more philosophically: “Life is really about change. Every day, each person faces some kind of challenge, big or small” ( Ciccarelli and White, 2018 , p. 462). From the perspective of evolutionary psychology, one might add the following: “Stress is not a direct product of cultural evolution but is a product of natural selection. It is a behavioural adaptation that helped our ancestors to fight or to flee from wild animals and enemies” ( Eysenck, 2009 , p. 87; Martin et al., 2013 , p. 682). Thus, stress appears as a universal mechanism , which is not restricted to certain times and cultures.

If stress indeed is a universal mechanism consisting of a combination of physiological and psychological responses that people show when things are getting too much and out of balance, one could ask how stress levels have developed over the course of time and whether people living in our modern era are more stressed out than they used to be in pre-industrial societies. The first section (“The Stress of Life”) addresses this question by sketching out different lines of reasoning. However, the second section (“Being Stressed Out as a Way to Be a Person”) attempts to explain why comparing the hardships of the past and the present in order to conclude whether ancient or contemporary lives are more stressful is potentially problematic. Building on the framework suggested by Hacking (2007) , I argue that being stressed out has become, but has not always been, a way to be a person. If this is the case, the assumption that stress is a universal mechanism seems questionable. Stress may be universal in the sense that people from all times and cultures (at least sometimes) have the experience that things are getting too much and out of balance. However, the way that people deal with this experience, that is, the way that people connect physiological and psychological responses, differs across times and cultures, making the stress concept highly context-dependent. This distinction is elaborated in the third section (“Stress as a Universal Mechanism?”). The final section of the paper (“The Importance of Putting Stress into Context”) discusses three reasons why we should be cautious when using the term “stress” in order to analyze the past. In short, the concept of stress can only be properly understood when put in historical context. In addition, such a contextualization may also help us to understand the functioning of our present-day societies.

The Stress of Life

Assuming that stress is a universal mechanism, that is, that stress exists across times and cultures, asking how stress levels vary across times and cultures is a sound question – and it in fact is a question posed by various authors. The answers that these authors give differ fundamentally and can be sorted into two groups: those that point to processes of acceleration and flexibilization in modern societies and those that point to the hardships and uncontrollable risks that existed in pre-industrial times. While the first group holds that modern life leads to increased stress levels, the second group believes that life was unimaginably harder in pre-modern societies. Let us consider these two types of answers.

For those who believe that being stressed out is deeply intertwined with the way our modern societies work (e.g., Sennett, 1998 , 2006 ; Rosa, 2010 , 2013 ), ours is an age of stress. It is argued that “[m]odern industrialized society sets a rapid, hectic pace for living. People often have too many demands placed on their time, are worried about uncertain futures, and have little time for family and fun” ( Gerrig, 2013 , p. 332). Hence, stress is regarded as the result “of living in the fast lane” ( Jackson, 2013 , p. 15), as an inescapable consequence of our lifestyle “with its multiple demands, little time for relaxation, and pressure to achieve” ( Donnelly and Long, 2003 , p. 398). In line with that, “the body’s responses to stress are [sometimes] regarded as being entirely appropriate, but inadequate to meet the intolerably high and relentless demands imposed by modern living conditions” ( Pollock, 1988 , p. 388). Expressed in more dramatic words this would mean, that the “[c]ultural progress, having outpaced biological evolution, invalidates some of the wisdom of the body” ( Kugelmann, 1992 , p. 34). In pre-industrial societies, people did not work in offices in which they were supposed to prepare a presentation for the next meeting while simultaneously helping their colleagues, answering mails, picking up the phone, talking to their boss who has just entered the room, and ignoring the radio which is playing in the background. Back then, people did not have a family with both spouses working full-time, being expected to be deeply in love with each other and being caring parents for their children, managing the household, keeping in touch with their friends, and living in peace with the neighbors who always complain about the kids being too noisy. Back then, people did not live in a world in which they were bombarded with information, making it tremendously difficult if not impossible to distinguish the important things from all the white noise. In short, it is the pace and the demands of our hectic, modern life that “stress us out.”

Although this claim seems to reflect a common belief, it does not remain unquestioned. Pollock (1988) writes, for instance, that “it is hard to see on what grounds we could be justified in assuming that the populations of non-industrial societies carry a lighter burden […]. These communities have their own fair share of morbidity and mortality, though these differ from our own” (p. 388; see also Jackson, 2014 ). Admittedly, the reply might go on, there were no smartphones, tablets, and computers back then, no newspapers and no television, no cars and no airplanes to make us feel rushed and overwhelmed. On the other hand, these technologies have diversified and enriched our lives to an incredible extent. Following this logic, the complexity of our modern societies is not a sign of decadence, but of security, wealth, happiness, and improved health. In line with that, Eysenck (2009 , p. 87) argues as follows:

It is probably true that more people than ever report being stressed. However, it isn’t clear that most people are more stressed than used to be the case. Our ancestors had to contend with major epidemics, poor life expectancy, poverty, and an almost complete absence of holidays. Taking all that into account, my hunch is that stress levels nowadays are much the same as in the past.

In fact, one may take an even more radical stance regarding this question: compared to the daily struggle to survive in the face of crop failures, famines, epidemic diseases, and natural disasters, one might say, our modern complaints about multiple demands and the increased pace of life are almost ridiculous. If anything, life was not easier but unimaginably harder in the past. If anything, people back then were far more stressed out than we are today.

So who is correct: those who claim that modern life leads to increased stress levels or those who claim that life was unimaginably harder in pre-modern, pre-industrial societies? As I shall argue in the following, it is almost impossible to answer the question satisfactorily. In contrast to what the cited authors seem to believe and in contrast to what contemporary psychology textbooks claim, it is far from clear that – or at least: in what sense – stress is a universal mechanism. Elaborating on this idea is the topic of the next section.

Being Stressed Out as a way to be a Person

Hacking (2007) has noted that a “scientific classification may bring into being a new kind of person, conceived of and experienced as a way to be a person” (p. 285). He named this process making up people and added a second term, the so-called looping effect , referring “to the way in which a classification may interact with the people classified” (p. 286). Hacking considers neither the development of a scientific theory nor the process of making up people to be arbitrary. He solely points out that using a system of classification never remains without consequences. When classifying people, we most likely also create institutions , which are responsible for classifying and dealing with the classified. Furthermore, we start to produce and to spread knowledge about the people we have made up, not to forget that there will be trained experts in the field as well. Finally, the possibility of being categorized enables people who have been categorized to act and behave differently. This might then, in turn, change the way the system of classification works. As MacIntyre (1985 , p. 898) has put it in a similar context, the impact of theories on human thinking and behavior is twofold: “it provides new models for self-knowledge and a partially new self for us to have knowledge of.”

In his paper, Hacking is mainly concerned with autism and multiple personality disorder, that is, with quite stable social categories and identities (for applications to other psychological phenomena, see, e.g., Thompson, 2017 ; Strle and Markič, 2018 ). In comparison to these phenomena, stress appears to be a rather temporary psychological state. For instance, it is perfectly sound to say that one was not stressed out yesterday but that one is stressed out today. In contrast, one would normally not claim that one is a person with autism today but not tomorrow. Thus, one may ask whether Hacking’s framework can be transferred to analyzing the concept of stress. I believe that the answer is positive. First, one may point to the fact that many people are not only stressed out every now and then but also experience stress regularly if not chronically. For those people at least, the state of being stressed out seems permanent rather than merely transient. Second, even if one were convinced that being stressed out reflects a temporary psychological state and not a stable identity, one would have to keep in mind that the concept of stress is a well-established social category that one can easily refer to if necessary. In other words, while the psychological state of the individual may be variable, the existence of the category itself is not. The concept of stress is deeply rooted in our present-day Western societies and can be used to describe one’s feelings, thoughts, and experiences. Just consider how stress shapes our daily lives:

People use a stressful day at work as an excuse not to tell their children their bedtime story or as an explanation why they are always fighting with their partner. They participate in stress management seminars in order to learn relaxation techniques and coping strategies, ask their doctors to put them on sick leave, and talk to their psychotherapists. Stress is also used to state the discomfort with current societal and economic developments ( Hutmacher, 2019 , p. 181).

Moreover, we can frequent institutions, which are specialized in treating the stressed, make an appointment with experts in the field who have the necessary knowledge to help us out, and we can use the term “stress” to denote what bothers us. Most importantly, others understand our complaints. Everyone knows what it feels like to be stressed out. Thus, stress “keeps consultants busy, researchers productive, exercise instructors jumping, and ordinary citizens experimenting with an increasingly complex array of diets, life-styles and technological stress-reducing gadgets” ( Kugelmann, 1992 , p. 21; see also Becker, 2013 ). For us, being stressed out is a way to be a person.

However, what about other times and cultures? Consider for this purpose the following two statements (adapted from Hacking, 2007 , p. 299):

• There were no stressed people in 500 BC; there are many stressed people in 2021.
• To be stressed out was not a way to be a person in 500 BC, people did not experience themselves in this way, they did not interact with their friends, their families, their employers, their counselors, in this way; but in 2021 this is a way to be a person, to experience oneself, to live in society.

In line with Hacking (2007) , I argue that B is true whereas A can be either true or false depending on how we read it. A is false in the sense mentioned above: no matter when and where people lived, they always had to carry their burdens – in 1900 as well as in 2021 or 500 BC. However, if A is seen as a brief version of B, it is true. B reflects the idea that a scientific concepts such as stress cannot be understood properly without taking into account the historical and societal circumstances in which its development and use is embedded.

In other words, the stress concept cannot be described adequately without referring to the social practices it is involved in. This means that a “stressed subject is different from one without such a qualifier: she or he can be treated or behave differently” ( Bicknell and Liefooghe, 2006 , p. 381). In 500 BC, people could not use a stressful day at work as an excuse not to tell their children their bedtime story or as an explanation why they are always fighting with their partner. They did not participate in stress management seminars in order to learn relaxation techniques and coping strategies. They did not ask their doctors to put them on sick leave, and they did not talk to their psychotherapists.

Stress as a Universal Mechanism?

Where does this leave the idea that stress is a universal mechanism ? Based on the framework provided by Hacking (2007) , the answer seems straightforward: being stressed out has become, but has not always been, a way to be a person. Put another way, “stress” as a social practice is a deeply culture-bound product of our modern Western societies and not a universal mechanism . However, one could try to defend the notion that stress indeed is a universal mechanism by pointing to the fact that the physiological and endocrinological mechanisms constituting the stress response are not a modern invention of our body. This counterargument deserves serious consideration.

Simply put, if we experience a situation in which “things are getting too much and out of balance,” our body shows a wide range of hard-wired responses. For instance, driven by an activation of the sympathetic nervous system, blood pressure, heart rate, and glucose levels increase, while reproductive and digestive functions are reduced (for an introductory overview, see, e.g., Karemaker, 2017 ). In addition, the hypothalamic-pituitary-adrenocortical axis (HPA-axis), a neuroendocrine system, which has already been investigated by Hans Selye, is activated and releases as cascade of hormones (for an overview, see, e.g., Tsigos and Chrousos, 2002 ; Charmandari et al., 2005 ; Smith and Vale, 2006 ). Moreover, prolonged chronic stress has been associated with various diseases such as depression and cardiovascular disease (e.g., Cohen et al., 2007 , 2016 ) as well as dysregulations of the immune system (e.g., Morey et al., 2015 ). Against this background, it seems tempting to dismiss the social practices, in which these physiological and endocrinological stress mechanisms are embedded, as a negligible by-product and to conclude that stress essentially indeed is a universal mechanism.

From my point of view, this conclusion would be too simplistic. The idea that it means something for us as human beings to be stressed out, that is, that being stressed out is a way of understanding ourselves, is based on the assumption that stress is not only a physiological, but also a psychological construct. Put differently, the way stress is commonly understood is based on the idea that the psychological responses to stress and the social practices involved in coping with stress are more than a negligible by-product. However, one may ask, would it not be possible to change this definition and to reconceptualize stress as a purely physiological and endocrinological mechanism? Such an approach would run into practical and theoretical problems. Successfully enforcing such a redefinition of the stress concept seems practically impossible, as the way stress is understood in the public as well as in the scientific discourse, it is far more than a purely physical condition. As described above, conceptualizing stress as the inseparable combination of physiological and psychological factors is deeply rooted in our present-day societies. So even if a researcher decided to apply the term stress to physiological or endocrinological mechanisms only, the researcher would constantly run at risk of being misinterpreted, as the researcher’s definition of stress would conflict with the way the concept is commonly applied.

However, there is an even more fundamental theoretical argument: stress does not exist as a purely biological state in humans – and it never can. This claim can be illustrated using an analogy about “good parenting” proposed by Thompson (2017 , p. 55):

Being a good parent consists in a host of emotional and cognitive skills and putting those skills into play in action. The skills and the behaviors based on them clearly depend on the brain – and improving them changes the brain – but they are not private mental states and do not exist inside the brain. Although it is possible that unique patterns of brain activity correlate with being a good parent in a given context, appealing to their presence would not explain what it is to be a good parent. Parenting does not exist inside the brain; it exists in the social world of human life. Furthermore, what counts as good parenting depends on the social context and the culture. So parenting simply is not visible at the level of the brain. To bring it into view, we need a wider perspective, one that takes in the context of the whole person as well as the social and cultural environment.

The same applies to stress: stress clearly depends on certain innate biological mechanisms, but it is not a private mental state and it does not exist inside the brain. Stress is unthinkable without the manner in which we relate to our body’s reactions, the way we frame, interpret, guide, and organize them (see Kugelmann, 1992 , p. 2). This also means that the social practices, in which the physiological and endocrinological stress mechanisms are embedded, form an essential part of the way stress is commonly understood. As discussed above, however, the manner in which we do relate to our body’s reactions as well as the manner in which we integrate these reactions into our scientific and societal discourse is not hard-wired: It is the result of complex social, historical, and societal processes. The fact that being stressed out has become a way to be a person simply means that our contemporary (Western) societies have developed a rule-governed, intersubjectively understandable, and institutionalized way of relating humans’ thoughts and behavior to a certain kind of bodily experience.

So is stress a universal mechanism? Yes and no. Yes, because the physiological and endocrinological mechanisms underlying the stress response are the same across times and cultures; and no, because the social practices in which these physiological and endocrinological mechanisms are embedded, have changed over time: being stressed out has become, but as not always been, a way to be a person. As the social practices surrounding the biological basis are not a negligible by-product of stress, but form an important part of the way stress is commonly understood, using the term “stress” when speaking about other times and cultures may be problematic. In other words, using the term “stress” is likely to create associations about institutions and experts, about the creation of knowledge and research programs, and about ways of interacting with others, which cannot be transferred directly to societies different from our own. Before discussing the potential consequences of this conclusion, I want to illustrate the point that I have tried to make by taking a closer look at two archeological studies.

The mummified body of the Iceman (also called “Ötzi”) who lived about 5,300 years ago was discovered in September 1991 in South Tyrol. Since then, his body has been analyzed in order to learn as much as possible about the circumstances of his life and death (see e.g., Seidler et al., 1992 ; Handt et al., 1994 ; Capasso, 1998 ; Macko et al., 1999 ). Although the mummy had lost all nails post mortem, as has been observed in other ancient mummies as well, one fingernail was found during the archeological excavation. The study by Capasso (1994) is concerned with analyzing this fingernail. In the abstract, the author writes:

[T]he presence of three sets of Beau’s lines have [ sic ] allowed us to determine the seriousness, time of onset, and duration of three periods of intense stress that the subject underwent during the last months of his life […]. […] [T]hey occurred four, three, and two months before death. The final episode was the most serious, and the systemic upheaval it produced lasted at least two weeks ( Capasso, 1994 , p. 123).

So what are Beau’s lines? First described by Beau (1846) from whom their name is derived, Beau’s lines are the expression “of temporary suffering on the part of the cells that produce onycokeratin. This suffering results in a more or less marked reduction in the growth of the nail, whose thickness is also reduced during the period of stress” ( Capasso, 1994 , pp. 127–128). As discussed in the literature, Beau’s lines can be caused by both localized pathologies and systemic causes. As “only fairly serious systemic diseases are capable of producing the degree of suffering of the nail matrix necessary to produce a reduction in the growth rate of the nail that can be observed macroscopically” ( Capasso, 1994 , p. 128) and as the Beau’s lines on the Iceman’s fingernail are very distinct, systemic causes seem to be most likely. Among others, possible systemic causes for the development of Beau’s lines in adults are zinc deficiencies ( Weismann, 1977 ), parathyroidal disease ( Lang, 1981 ), and serious events during which a person’s life was under serious threat ( Beaven and Brooks, 1984 ). No matter what kind of systemic cause may have led to the formation of the Beau’s lines on the Iceman’s fingernail, they seem to be, as Capasso argues, “the result of generic forms of stress” (p. 129).

Is this conclusion correct? First, it is important to note that I do not want to cast doubt on the scientific worth of the cited study. Gaining new insights in the living conditions of the Iceman using the latest instruments and techniques of analysis sounds promising and has indeed yielded impressive results. Second, using the term “stress” in this context may be potentially misleading. Given the results of the discussed study and the findings of other researchers, it seems safe to assume that the last weeks and months in the life of the Iceman were full of deprivation. Nevertheless, the collected evidence does not tell us anything about the subjective experiences the Iceman had during this last period of his life. We do not know anything about his thoughts or feelings. We do not know how he as an individual related to the symptoms he experienced. We do not know how he reacted to the diseases he may have been afflicted with. He may or may have not viewed them as a punishment by gods or spirits. He may have suffered from them, but he may also have accepted them as a burden he had to carry. We simply do not know the answer to these kinds of psychological questions and there is no way of finding out. However, what we do know is that in the times of the Iceman, there was no health care system comparable to ours. As mentioned above, there were no psychotherapists, no stress-management seminars teaching coping strategies, and no doctors putting exhausted individuals on sick leave. Most certainly, the Iceman had his own strategies on how to deal with fear and despair, misfortune and disease, and most certainly these strategies were not the strategies we use today. The Iceman did not talk about stressors and coping in the sense that we do today. Simply put, being stressed out was not a way to be a person for the Iceman. He neither experienced himself nor interacted with his contemporaries in this way.

Taken together, using the term “stress” in the context of the Iceman is potentially misleading as it suggests a knowledge about the subjective experience of the Iceman, which we do not have, and as it creates the impression of a similarity between his time and our time, which does not necessarily exist. Of course, one could defend the use of the word “stress” in the context of the Iceman by claiming that one was referring to the underlying physiological and endocrinological mechanisms, which we share with the Iceman. In a certain sense, this defense is perfectly sound. Nevertheless, the defense is also incomplete as it discards the social practices surrounding the biological basis of stress too quickly. That does not necessarily imply that we should stop using the word “stress” when speaking about other times and cultures, but it does imply that we should use the word with caution. At least, we should be aware of the fact that there are fundamental differences between then and now , which are not captured by the umbrella term “stress.”

Archeological Hair From Peru

Similar lessons can be learned from another archeological study, conducted by Webb et al. (2010) who tried to assess “systemic stress” of long-deceased individuals. In order to do so, the authors “selected hair samples from ten individuals from five different archaeological sites in Peru, and analyzed them in segments to determine cortisol levels” (p. 807). The bodies of the investigated individuals were between 500 and 1,500 years old. The authors hypothesized that the “[a]nalysis of cortical levels in archaeological hair should enable assessment of stress during a short, but critical, period of an individual’s life” (p. 807). Indeed, the hair samples of all individuals “showed measurable levels of cortisol” (p. 809). Thus, “individual experiences of stress can be reconstructed for the period of time represented by each hair sample” (p. 807). Furthermore, “[t]he segmental data suggest that stress in the months and years represented by our hair samples is highly variable among individuals, and it is likely that the causes of that stress are also diverse” (p. 811).

Again, my reservation is not about the idea of trying to understand more about the life of deceased individuals about whose lifestyle and living conditions we have no source except from their mortal remains; my reservation is not about the data itself, but about the way they are presented . The cortisol found in the hair of the 10 investigated individuals may in fact represent their bodies’ reaction to the demands of their environment. In this context, the observation that their “[c]ortisol levels are somewhat high compared to modern healthy individuals […] [and that] this is not entirely unexpected because these individuals were approaching death and some may have been chronically ill” (p. 810) sounds reasonable, too. My point is simply that we have no idea how people dealt with these struggles and difficulties in the societies or communities they belonged to. Thus, using the term “stress” to denote what the individuals were bothered with can be seen as a simplification. In the lack of better options, we may still decide to do it. However, we should at least be aware what we are doing.

Discussion: the Importance of Putting Stress Into Context

As the first section of the present paper has illustrated, contemporary psychology commonly views stress as a universal mechanism consisting of a combination of physiological and psychological responses that people show when things are getting too much and out of balance. In a certain sense, this universality claim is correct: The physiological and endocrinological mechanisms underlying the stress response are not a modern invention of our body, but have remained the same across time and cultures. In another sense, the universality claim is potentially problematic: neither for the Iceman nor for the 10 individuals, who died in South America between 500 and 1,500 years ago, “being stressed out” was a way to be a person. The use of the stress concept is in fact restricted to certain times and cultures. More specifically, the social practices in which the physiological and endocrinological stress mechanisms are embedded have changed over time. Hence, using the term “stress” when referring to the burdens people from different times and cultures had to carry can be seen as an oversimplification. However, one may still decide to use the term “stress” when referring to other times and cultures for pragmatic reasons . While the terms that the communities under investigation have used to describe their burdens may be unknown or at least foreign to us, “stress” is a commonly understood concept. Hence, one could argue that using “stress” as an umbrella term that helps our understanding of the sorrows and worries of the past as well as connects us to cultures and civilizations that have long since disappeared. While I see the merits of such a pragmatic approach, the last section of the present paper is dedicated to exploring why I believe that we should be cautious when using the stress concept to understand the past. In my opinion, there are at least three reasons, some of which I have already briefly mentioned above. First, using the term “stress” when referring to past times and cultures is potentially problematic, because it may create the impression of a similarity between then and now , which does not actually exist. Second, it may blind us to the nature of the differences between times and cultures. Third, it naturalizes a contemporary scientific concept, which is more adequately viewed as the result of complex social, historical, and societal processes. These three reasons shall be discussed in more detail.

Culture shapes our lives and it shapes them profoundly. It shapes the way we think (e.g., Nisbett, 2003 ), feel (e.g., Osgood et al., 1975 ; Russell, 1991 ), and perceive (e.g., Segall et al., 1966 ). It shapes our hopes, our fears, and our sorrows. It shapes the things we consider to be desirable and the ones we despise. A brief look at history is enough to realize that different communities have created completely different lifestyles, sets of rules, and moral principles (for a classic but controversial example, see Hofstede, 1980 , 1991 ). For instance, our modern Western concept of identity substantially differs from the concept of identity not only in pre-modern and ancient times, but also in the medieval ages (for a description of the development of modern Western identity see, e.g., Taylor, 1989 ). As we grew up in our contemporary societies, the way they are designed may feel completely natural to us. Realizing that they are in fact man-made can help us to remain modest. It can free us from the hubris that everyone thinks about the world just as we do. This should not be misunderstood as a plea for relativism: acknowledging the existence of different conceptualizations is rather a starting point for discussions than the end of it (for an overview of the different points of view in the relativism-universalism debate, see, e.g., Berry et al., 2011 , pp. 6–8). “Stress” as a scientific concept was developed in Western, that is, industrialized, wealthy, and democratic societies – to name just a few superficial keywords (for the problem of “weird” samples and theories in psychology, see, e.g., Henrich et al., 2010 ; Apicella et al., 2020 ). Most societies of the past were not societies of this kind. Hence, they probably had different ways of operationalizing and discursivizing their hardships. We can compare these conceptualizations, learn from them, and criticize them. Thus, putting stress in historical context can prevent us from getting caught up with our own ideas and perceptions. It can teach us modesty and help us to avoid the pitfalls that come with assuming that past societies essentially worked in similar ways to our present-day societies. Additionally, carving out the rules and conventions on which other societies were based may be critical for understanding the concepts they used in order to deal with their daily struggles. It is quite likely that we will not be able to understand the solutions that past societies created for coping with certain problems, or that we will find them extremely odd and hard to grasp, unless we manage to identify the key characteristics of the thinking underlying these solutions. That is, until we understand in which ways their thinking was different from our own.

In this context, it has recently been argued that psychology should put more effort into understanding cross-temporal variation ( Muthukrishna et al., 2020 ). This would include analyzing historical data, most likely using a wide range of different methods, which capture the full range of the involved mental, behavioral, and social processes (e.g., Mayrhofer and Hutmacher, 2020 ). Providing a detailed analysis of historical data to see how other times and cultures have dealt with situations in which “things were getting too much and out of balance” is highly desirable, but far beyond the scope of the present paper. Hence, one fictional example shall suffice to illustrate the interplay of the two aspects discussed so far. Imagine a deeply religious peasant in the Middle Ages who has just experienced a crop failure (for a nuanced description of popular religion in the Middle Ages, see, e.g., Brooke and Brooke, 1984 ; Geary, 2001 ). He is desperate as he is expecting a hard winter. He fears that he will be unable to feed his family. His parents, his wife, and his six children will starve or may even die. Hence, he goes to church, lights a candle and prays to God, begging him for mercy. Saying that this peasant is stressed out and trying to cope with his misfortune by turning to God would imply both the attempt to make the peasant similar to us and the inability to see that he is actually doing something quite different. The peasant does not pray to God in order to feel better; turning to God is not a coping strategy for him. Expressed differently, the peasant is not taking an instrumental stance toward God. He is deeply convinced of God’s presence in the world and believes that his fate is in God’s hands. His view of the world and of his place in this world is profoundly different from ours. He believes that turning to God is the only adequate way of reacting to the problems he is facing. While for us, there may be “helpful cognitions” and “reappraisal techniques,” which we can use, for the medieval peasant, there is a fixed world order with eternal rules. While for the most of us, eternal life is a vague possibility at the very most, it is an undisputable certainty for the peasant in the Medieval Ages. While for us expressing our potential and following our personal desires and ambitions is an important part of our lives, the peasant most likely believes in a predetermined societal hierarchy God has given him a fixed place in. Although this is only a rough and oversimplifying sketch, it should have become clear by now that these differences could potentially remain unnoticed when the term “stress” is used uncritically.

So far, “stress” has been presented as a concept that enables us, as modern, Western selves, to experience ourselves and to interact with others in certain ways (see, e.g., Hepburn and Brown, 2001 , for an example of how stress is used in everyday settings). The social practices that we have developed to relate ourselves to our bodily experiences are the result of complex social, historical, and societal processes (for a perspective on the connectedness of biological and cognitive processes, see Varela, 1984 ). That is not to say that these practices are arbitrary or inadequate. Rather, it seems plausible to assume that stress has become “a way to be a person, to experience oneself, to live in society” ( Hacking, 2007 , p. 299) in our times for very good reasons. One may argue, for example, that the rapid technological and economic transformations in the twentieth and twenty-first century have contributed to making stress a popular concept or have at least helped to reinforce its ongoing success (see e.g., Sennett, 1998 , 2006 ; Rosa, 2010 , 2013 ). One may also argue that the concept of stress is deeply intertwined with the way modern identity is understood in our contemporary Western societies ( Hutmacher, 2019 ). If this is the case, it does not matter that the Iceman did not experience himself as being stressed out. We do. Thus, acknowledging that the social practices, in which the physiological and endocrinological stress mechanisms are embedded, have changed over time, may open up a space for reflection. It may not only help us to understand why feeling stressed out has become a way to be a person in our specific historical context; it may also help us to take a step back and to think about the ways “stress” shapes our lives and whether we consider this to be desirable or not.

Author Contributions

FH developed the research idea and wrote the manuscript.

Conflict of Interest

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

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The Historical Context

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• Robert E. White 4  

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This chapter deals with the historical context of performing qualitative research in postcolonial times. It acknowledges the evolutionary and revolutionary nature of qualitative research. The chapter begins with an African proverb, and then proceeds to examine Norman Denzin and Yvonna Lincoln’s article relating to the eight historical moments in qualitative research. A video clip featuring Norman Denzin situates the historical context within qualitative research in general. The chapter concludes with a selected annotated bibliography and questions for further study.

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Cooper, K., White, R.E. (2012). The Historical Context. In: Cooper, K., White, R. (eds) Qualitative Research in the Post-Modern Era. Springer, Dordrecht. https://doi.org/10.1007/978-94-007-2339-9_4

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Home » Historical Research – Types, Methods and Examples

Historical Research – Types, Methods and Examples

Table of Contents

Historical Research

Definition:

Historical research is the process of investigating and studying past events, people, and societies using a variety of sources and methods. This type of research aims to reconstruct and interpret the past based on the available evidence.

Types of Historical Research

There are several types of historical research, including:

Descriptive Research

This type of historical research focuses on describing events, people, or cultures in detail. It can involve examining artifacts, documents, or other sources of information to create a detailed account of what happened or existed.

Analytical Research

This type of historical research aims to explain why events, people, or cultures occurred in a certain way. It involves analyzing data to identify patterns, causes, and effects, and making interpretations based on this analysis.

Comparative Research

This type of historical research involves comparing two or more events, people, or cultures to identify similarities and differences. This can help researchers understand the unique characteristics of each and how they interacted with each other.

Interpretive Research

This type of historical research focuses on interpreting the meaning of past events, people, or cultures. It can involve analyzing cultural symbols, beliefs, and practices to understand their significance in a particular historical context.

Quantitative Research

This type of historical research involves using statistical methods to analyze historical data. It can involve examining demographic information, economic indicators, or other quantitative data to identify patterns and trends.

Qualitative Research

This type of historical research involves examining non-numerical data such as personal accounts, letters, or diaries. It can provide insights into the experiences and perspectives of individuals during a particular historical period.

Data Collection Methods

Data Collection Methods are as follows:

• Archival research : This involves analyzing documents and records that have been preserved over time, such as government records, diaries, letters, newspapers, and photographs. Archival research is often conducted in libraries, archives, and museums.
• Oral history : This involves conducting interviews with individuals who have lived through a particular historical period or event. Oral history can provide a unique perspective on past events and can help to fill gaps in the historical record.
• Artifact analysis: This involves examining physical objects from the past, such as tools, clothing, and artwork, to gain insights into past cultures and practices.
• Secondary sources: This involves analyzing published works, such as books, articles, and academic papers, that discuss past events and cultures. Secondary sources can provide context and insights into the historical period being studied.
• Statistical analysis : This involves analyzing numerical data from the past, such as census records or economic data, to identify patterns and trends.
• Fieldwork : This involves conducting on-site research in a particular location, such as visiting a historical site or conducting ethnographic research in a particular community. Fieldwork can provide a firsthand understanding of the culture and environment being studied.
• Content analysis: This involves analyzing the content of media from the past, such as films, television programs, and advertisements, to gain insights into cultural attitudes and beliefs.

Data Analysis Methods

• Content analysis : This involves analyzing the content of written or visual material, such as books, newspapers, or photographs, to identify patterns and themes. Content analysis can be used to identify changes in cultural values and beliefs over time.
• Textual analysis : This involves analyzing written texts, such as letters or diaries, to understand the experiences and perspectives of individuals during a particular historical period. Textual analysis can provide insights into how people lived and thought in the past.
• Discourse analysis : This involves analyzing how language is used to construct meaning and power relations in a particular historical period. Discourse analysis can help to identify how social and political ideologies were constructed and maintained over time.
• Statistical analysis: This involves using statistical methods to analyze numerical data, such as census records or economic data, to identify patterns and trends. Statistical analysis can help to identify changes in population demographics, economic conditions, and other factors over time.
• Comparative analysis : This involves comparing data from two or more historical periods or events to identify similarities and differences. Comparative analysis can help to identify patterns and trends that may not be apparent from analyzing data from a single historical period.
• Qualitative analysis: This involves analyzing non-numerical data, such as oral history interviews or ethnographic field notes, to identify themes and patterns. Qualitative analysis can provide a rich understanding of the experiences and perspectives of individuals in the past.

Historical Research Methodology

Here are the general steps involved in historical research methodology:

• Define the research question: Start by identifying a research question that you want to answer through your historical research. This question should be focused, specific, and relevant to your research goals.
• Review the literature: Conduct a review of the existing literature on the topic of your research question. This can involve reading books, articles, and academic papers to gain a thorough understanding of the existing research.
• Develop a research design : Develop a research design that outlines the methods you will use to collect and analyze data. This design should be based on the research question and should be feasible given the resources and time available.
• Collect data: Use the methods outlined in your research design to collect data on past events, people, and cultures. This can involve archival research, oral history interviews, artifact analysis, and other data collection methods.
• Analyze data : Analyze the data you have collected using the methods outlined in your research design. This can involve content analysis, textual analysis, statistical analysis, and other data analysis methods.
• Interpret findings : Use the results of your data analysis to draw meaningful insights and conclusions related to your research question. These insights should be grounded in the data and should be relevant to the research goals.
• Communicate results: Communicate your findings through a research report, academic paper, or other means. This should be done in a clear, concise, and well-organized manner, with appropriate citations and references to the literature.

Applications of Historical Research

Historical research has a wide range of applications in various fields, including:

• Education : Historical research can be used to develop curriculum materials that reflect a more accurate and inclusive representation of history. It can also be used to provide students with a deeper understanding of past events and cultures.
• Museums : Historical research is used to develop exhibits, programs, and other materials for museums. It can provide a more accurate and engaging presentation of historical events and artifacts.
• Public policy : Historical research is used to inform public policy decisions by providing insights into the historical context of current issues. It can also be used to evaluate the effectiveness of past policies and programs.
• Business : Historical research can be used by businesses to understand the evolution of their industry and to identify trends that may affect their future success. It can also be used to develop marketing strategies that resonate with customers’ historical interests and values.
• Law : Historical research is used in legal proceedings to provide evidence and context for cases involving historical events or practices. It can also be used to inform the development of new laws and policies.
• Genealogy : Historical research can be used by individuals to trace their family history and to understand their ancestral roots.
• Cultural preservation : Historical research is used to preserve cultural heritage by documenting and interpreting past events, practices, and traditions. It can also be used to identify and preserve historical landmarks and artifacts.

Examples of Historical Research

Examples of Historical Research are as follows:

• Examining the history of race relations in the United States: Historical research could be used to explore the historical roots of racial inequality and injustice in the United States. This could help inform current efforts to address systemic racism and promote social justice.
• Tracing the evolution of political ideologies: Historical research could be used to study the development of political ideologies over time. This could help to contextualize current political debates and provide insights into the origins and evolution of political beliefs and values.
• Analyzing the impact of technology on society : Historical research could be used to explore the impact of technology on society over time. This could include examining the impact of previous technological revolutions (such as the industrial revolution) on society, as well as studying the current impact of emerging technologies on society and the environment.
• Documenting the history of marginalized communities : Historical research could be used to document the history of marginalized communities (such as LGBTQ+ communities or indigenous communities). This could help to preserve cultural heritage, promote social justice, and promote a more inclusive understanding of history.

Purpose of Historical Research

The purpose of historical research is to study the past in order to gain a better understanding of the present and to inform future decision-making. Some specific purposes of historical research include:

• To understand the origins of current events, practices, and institutions : Historical research can be used to explore the historical roots of current events, practices, and institutions. By understanding how things developed over time, we can gain a better understanding of the present.
• To develop a more accurate and inclusive understanding of history : Historical research can be used to correct inaccuracies and biases in historical narratives. By exploring different perspectives and sources of information, we can develop a more complete and nuanced understanding of history.
• To inform decision-making: Historical research can be used to inform decision-making in various fields, including education, public policy, business, and law. By understanding the historical context of current issues, we can make more informed decisions about how to address them.
• To preserve cultural heritage : Historical research can be used to document and preserve cultural heritage, including traditions, practices, and artifacts. By understanding the historical significance of these cultural elements, we can work to preserve them for future generations.
• To stimulate curiosity and critical thinking: Historical research can be used to stimulate curiosity and critical thinking about the past. By exploring different historical perspectives and interpretations, we can develop a more critical and reflective approach to understanding history and its relevance to the present.

When to use Historical Research

Historical research can be useful in a variety of contexts. Here are some examples of when historical research might be particularly appropriate:

• When examining the historical roots of current events: Historical research can be used to explore the historical roots of current events, practices, and institutions. By understanding how things developed over time, we can gain a better understanding of the present.
• When examining the historical context of a particular topic : Historical research can be used to explore the historical context of a particular topic, such as a social issue, political debate, or scientific development. By understanding the historical context, we can gain a more nuanced understanding of the topic and its significance.
• When exploring the evolution of a particular field or discipline : Historical research can be used to explore the evolution of a particular field or discipline, such as medicine, law, or art. By understanding the historical development of the field, we can gain a better understanding of its current state and future directions.
• When examining the impact of past events on current society : Historical research can be used to examine the impact of past events (such as wars, revolutions, or social movements) on current society. By understanding the historical context and impact of these events, we can gain insights into current social and political issues.
• When studying the cultural heritage of a particular community or group : Historical research can be used to document and preserve the cultural heritage of a particular community or group. By understanding the historical significance of cultural practices, traditions, and artifacts, we can work to preserve them for future generations.

Characteristics of Historical Research

The following are some characteristics of historical research:

• Focus on the past : Historical research focuses on events, people, and phenomena of the past. It seeks to understand how things developed over time and how they relate to current events.
• Reliance on primary sources: Historical research relies on primary sources such as letters, diaries, newspapers, government documents, and other artifacts from the period being studied. These sources provide firsthand accounts of events and can help researchers gain a more accurate understanding of the past.
• Interpretation of data : Historical research involves interpretation of data from primary sources. Researchers analyze and interpret data to draw conclusions about the past.
• Use of multiple sources: Historical research often involves using multiple sources of data to gain a more complete understanding of the past. By examining a range of sources, researchers can cross-reference information and validate their findings.
• Importance of context: Historical research emphasizes the importance of context. Researchers analyze the historical context in which events occurred and consider how that context influenced people’s actions and decisions.
• Subjectivity : Historical research is inherently subjective, as researchers interpret data and draw conclusions based on their own perspectives and biases. Researchers must be aware of their own biases and strive for objectivity in their analysis.
• Importance of historical significance: Historical research emphasizes the importance of historical significance. Researchers consider the historical significance of events, people, and phenomena and their impact on the present and future.
• Use of qualitative methods : Historical research often uses qualitative methods such as content analysis, discourse analysis, and narrative analysis to analyze data and draw conclusions about the past.

Advantages of Historical Research

There are several advantages to historical research:

• Provides a deeper understanding of the past : Historical research can provide a more comprehensive understanding of past events and how they have shaped current social, political, and economic conditions. This can help individuals and organizations make informed decisions about the future.
• Helps preserve cultural heritage: Historical research can be used to document and preserve cultural heritage. By studying the history of a particular culture, researchers can gain insights into the cultural practices and beliefs that have shaped that culture over time.
• Provides insights into long-term trends : Historical research can provide insights into long-term trends and patterns. By studying historical data over time, researchers can identify patterns and trends that may be difficult to discern from short-term data.
• Facilitates the development of hypotheses: Historical research can facilitate the development of hypotheses about how past events have influenced current conditions. These hypotheses can be tested using other research methods, such as experiments or surveys.
• Helps identify root causes of social problems : Historical research can help identify the root causes of social problems. By studying the historical context in which these problems developed, researchers can gain a better understanding of how they emerged and what factors may have contributed to their development.
• Provides a source of inspiration: Historical research can provide a source of inspiration for individuals and organizations seeking to address current social, political, and economic challenges. By studying the accomplishments and struggles of past generations, researchers can gain insights into how to address current challenges.

Limitations of Historical Research

Some Limitations of Historical Research are as follows:

• Reliance on incomplete or biased data: Historical research is often limited by the availability and quality of data. Many primary sources have been lost, destroyed, or are inaccessible, making it difficult to get a complete picture of historical events. Additionally, some primary sources may be biased or represent only one perspective on an event.
• Difficulty in generalizing findings: Historical research is often specific to a particular time and place and may not be easily generalized to other contexts. This makes it difficult to draw broad conclusions about human behavior or social phenomena.
• Lack of control over variables : Historical research often lacks control over variables. Researchers cannot manipulate or control historical events, making it difficult to establish cause-and-effect relationships.
• Subjectivity of interpretation : Historical research is often subjective because researchers must interpret data and draw conclusions based on their own biases and perspectives. Different researchers may interpret the same data differently, leading to different conclusions.
• Limited ability to test hypotheses: Historical research is often limited in its ability to test hypotheses. Because the events being studied have already occurred, researchers cannot manipulate variables or conduct experiments to test their hypotheses.
• Lack of objectivity: Historical research is often subjective, and researchers must be aware of their own biases and strive for objectivity in their analysis. However, it can be difficult to maintain objectivity when studying events that are emotionally charged or controversial.
• Limited generalizability: Historical research is often limited in its generalizability, as the events and conditions being studied may be specific to a particular time and place. This makes it difficult to draw broad conclusions that apply to other contexts or time periods.

About the author

Muhammad Hassan

Researcher, Academic Writer, Web developer

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21 Historical Context Examples

Historical context refers to all of the information about the time or era in which something occurs. This information can help us to more fully understand the event.

For example, we might look at the the social, cultural, and political circumstances that influenced an event in the past. All of the circumstances that were contemporaneous to the event will give us ‘historical context’ through which we can analyze the event.

The historical context of an event (or person!) helps in understanding why things happened the way they did and gives meaning to those happenings.

Contextual factors worth considering include:

• Gender roles: How many liberties were women, in particular, able to exercise at that particular time and place in history?
• Technology : What technological innovations were available for people, and did they affect the course of events?
• Social norms: What norms were in place that enabled and constrained people at the time?
• Politics: Was their geopolitical turmoil or relative stability in the world? Did the historical event happen in a free democratic nation or a dictatorship?
• Economy: Were people able to live a good, comfortable life in a functioning economy, or did poverty potentially affect the course of events?

An accurate interpretation of historical events necessitates a deep understanding of the context of the time.

Historical Context Examples

1. the industrial revolution.

The Industrial Revolution was a key turning point in human history. It was a time when manual labor started to be replaced by machines, and mass production became a reality.

This change increased economic productivity and improved living standards for many. However, it also led to a concentration of wealth and power in the hands of a few.

Contextual Factors:

• The status and distribution of technological advancements during the period
• Social class divisions and disparities in access to resources.
• Urbanization and migration trends.
• Impact of economic laws and regulations.
• Effects on environment due to industrial activities.

2. The Civil Rights Movement

Emerging in the mid-20th century, the Civil Rights Movement represented a quest for social justice and equality, specifically for African Americans in the United States.

This movement was rooted in centuries of systemic racial discrimination , segregation, and disenfranchisement. The Civil Rights Movement utilized both legal litigation and nonviolent protest to achieve its goals. Its evolution and success can only be understood by recognizing the broader historical context of racial tensions and legislation in the United States.

• Pre-existing racial segregation laws, also referred to as Jim Crow laws.
• Influence of the media in spreading the cause.
• Key ideologies and actors within the movement.
• The position and response of the federal government during the movement.
• International socio-political climate and feelings towards racial equality.

3. World War II

One of the deadliest and most wide-ranging conflicts in history, World War II brought devastation and unprecedented changes to the global structure.

The war was fought between the Allies (including the U.S., the U.K., Soviet Union, and China) and the Axis (Germany, Japan, and Italy), with battles taking place on every continent except Antarctica.

• The aggressive foreign policies and expansionist ideologies of Axis powers.
• The lingering effects of World War I, including the Treaty of Versailles.
• The instability caused by the Great Depression and its ripple effects.
• Advancements in military technology and their tactical implications.
• The reaction of the international community and the role of alliances.

4. The Renaissance

The Renaissance was a period of intense intellectual and artistic activity in Europe that spanned from the 14th century to the 17th century.

This era marked a profound cultural shift from the Middle Ages, with new ways of thinking about the world stemming from the study of art, science, literature, and philosophy.

• The decline of the Church’s authority and the rise of secular thinking.
• Societal impacts of the European discovery of new continents.
• Influence of Greek and Roman ancient texts and their rediscovery.
• Changes in socio-economic structures, including the rise of a wealthy merchant class.
• Novel approaches to art and humanist philosophies.

5. The French Revolution

The French Revolution was a period of radical political and societal change in France that lasted from 1789 until 1799, leading to the end of monarchy and the rise of Napoleon Bonaparte.

The Revolution had a lasting impact not only on France but also significantly influenced the direction of modern history. France rose as one of the world’s great democracies, which it remains today.

• The inefficiency and despotism of the French monarchy at the time.
• The severe economic hardship exacerbated by the monarchy’s taxation system.
• Popular Enlightenment ideas challenging monarchy and the Church.
• The impact of the American Revolution on encouraging revolutionary sentiment.
• The vast socio-economic disparities between different classes in French society.

6. The Cold War

The Cold War was a period of ideological and geopolitical tension between the United States and the Soviet Union, and their respective allies, from 1945 to the early 1990s.

This era was characterized by political and military tension, arms races, proxy wars, propaganda warfare, and significant technological competition. Fortunately, it ended relatively peacefully, but threatens to start-up again today with newfound Russian imperialist aggression.

• The conflict of ideologies (Capitalism versus Communism).
• The power vacuum post-World War II leading to bifurcation of global powers.
• Advancements in nuclear technology and the fear of mutual destruction.
• The influence of decolonization and the rise of the Non-Aligned Movement.
• The effect of economic strategies like the U.S.’s Marshall Plan and the Soviet’s Comecon.

7. The Space Race

The Space Race, occurring from 1955 to 1975, was a competition between the United States and the Soviet Union to achieve firsts in spaceflight capabilities.

It took place during the Cold War and symbolized the ideological and technological clash between the two superpowers. One important contextual factor in this point in history was, in fact, the cold war, which acted as the political backdrop to the massive investment in space infrastructure.

• The development of rocket technology in the wake of World War II.
• The geopolitical tensions and surrogate competitions of the Cold War.
• The technological advancements in satellite and manned spaceflight.
• The influence of key individuals and agencies, such as NASA and Sergei Korolev.
• The shift in public opinion towards space exploration.

8. The Abolitionist Movement

The Abolitionist Movement in the United States spanned from the late 18th century until the end of the American Civil War in 1865.

This movement sought to end the practice of slavery and promote equal rights for all citizens, significantly impacting the social and political fabric of the nation.

There was a range of contextual factors at this time, including enlightenment beliefs about the innate natural rights of all humans , religious debate about whether slavery was condoned in the bible, and worries about the economic impact of the loss of slave labor.

Contextual Factors

• The institution of slavery and its economic and social impacts.
• The religious reform movements stressing human equality.
• The influence of key abolitionists like Frederick Douglass and Harriet Beecher Stowe.
• The passing of key legislation and court rulings regarding slavery.
• The division between the North and South on the issue of slavery.

9. Roman Empire

The Roman Empire, at its peak, was the most extensive political and social structure in western civilization.

This empire lasted from 27 BC with Augustus becoming the first emperor until AD 476 when the last emperor of Rome, Romulus Augustus, was overthrown. The Roman Empire had a profound impact on Europe and its influence is still seen in architecture, engineering, law, and language.

• The transition from a republic to an imperial structure and its implications.
• Military conquests and the expansion of the empire.
• Cultural integration and diversification within the empire.
• Economic structure and infrastructure development such as road networks.
• Weakening of political, military, and economic structures leading to the fall of the Roman Empire.

10. Digital Revolution

The Digital Revolution is a historical shift from traditional industry precipitated by the invention and rapid improvement of digital technology.

This revolution started approximately in the 1950s and is ongoing today. Its origins can be traced back to the development of the personal computer, internet and the transition from analog electronic and mechanical devices to digital technology.

• Advances in silicon microchip technology driving the proliferation of digital devices.
• The rise of the personal computer and the conceptualization of the internet.
• The global shift towards information-based economies.
• The evolution of social relationships and interactions with the advent of social media.
• Changes in job markets and sectors due to the impact of automation and digitization.

11. The Enlightenment

Occurring in the 17th and 18th centuries, the Enlightenment was an intellectual and philosophical movement that dominated the world of ideas in Europe.

It was marked by a focused criticism of traditional authorities , including monarchy and the Church, and an emphasis on intellectual interchange and the scientific method.

• The religious turmoil and wars of the Reformation and Counter-Reformation.
• The rise of secularism and rationalism in societal thought.
• The promotion of democratic values and individual freedoms.
• The advancements in scientific discovery and technological innovation.
• The proliferation of salons and printed materials spreading Enlightenment ideas.

12. The Age of Exploration

The Age of Exploration, also known as the Age of Discovery, was a period in history starting in the early 15th century and continuing into the early 17th century.

During this period, technological advancements in navigation allowed European explorers to embark on overseas exploration, leading to the discovery of new lands, trade routes, and civilizations.

• Technological innovations in shipbuilding and navigation.
• The desire to establish new trade routes to avoid Ottoman control.
• The socio-political ambition of European kingdoms to expand their territories.
• Contact and interaction with previously unknown civilizations and cultures.
• The subsequent colonization and exploitation of discovered lands.

13. The Reformation

The Reformation was a major religious movement in the 16th century that led to the theological divide in the Christian Church and the emergence of Protestantism.

Initiated by Martin Luther in 1517, its main objectives were to reform and challenge corrupt practices within the Catholic Church. This revolution led to a range of subsequent Christian denominations, many of which are adhered to around the world to this day.

• Corrupt practices within the Catholic Church, such as selling indulgences.
• The invention of the printing press, allowing the rapid spread of reformative ideas.
• The socio-political climate, including the support or resistance from different monarchs.
• The philosophical underpinnings of the movement, under Martin Luther, John Calvin, and other reformers.
• The counter-reactions of the Church, leading to the Counter-Reformation.

14. The Meiji Restoration

The Meiji Restoration was a major revolution that occurred in Japan in 1868.

This era marked the end of the Edo period during which the country was ruled by the feudal military regime of the Tokugawa shogunate. The Meiji Restoration saw the reinstatement of the emperor to power, signifying a political shift towards a central government based on western ideas of constitutional monarchy and industrialized economy.

• The pressure from Western powers to open Japanese ports to international trade.
• The discontent with the Tokugawa shogunate among many provincial samurai.
• The cultural exchange and absorption of Western culture’s ideas about governance and development.
• Rapid industrialization and modernization efforts in Japan following the restoration.
• The transformation of societal structures, including the class system .

15. The American Revolution

The American Revolution was the conflict fought between Great Britain and thirteen of its North American colonies, which had declared themselves as the independent United States of America.

Starting in 1775, it resulted in the successful separation of the colonies from British rule, establishing the United States as a sovereign nation.

• Unpopular laws and taxes imposed by Britain on their American colonies.
• Influential Enlightenment ideas about government and individual rights.
• Key events leading up to the Revolution, such as the Boston Tea Party and the First Continental Congress.
• The military strategies and alliances that ultimately led to American victory.
• The lasting impact, such as the creation of a democratic republic, marked by the Constitution and Bill of Rights.

16. The Great Depression

The Great Depression was a severe, worldwide economic depression that lasted from 1929 to the late 1930s, with different nations recovering at different times.

The depression began in the United States after a major fall in stock prices that began around September 4, 1929, and became a worldwide news with the stock market crash of October 29, 1929, known as Black Tuesday.

• The speculative bubble in the stock market leading to the 1929 crash.
• Failures in policy responses, such as the America’s Smoot-Hawley Tariff Act.
• The established economic structures, and diversity or lack thereof in different economies.
• Changes in social and cultural spheres as a response to economic hardship.
• Global effects and variations in recovery responses, such as aspects of Franklin D. Roosevelt’s New Deal.

17. The Victorian Era

The Victorian era is the period during which Queen Victoria ruled Britain, from 1837 to 1901.

This era was marked by significant changes and developments in almost every sphere from politics to social norms, giving it a distinct spot in British history. Today, there remain many signs of Victorian architecture throughout the former British colonies.

• Industrialization and its impact on society, including urban growth and changing class structures.
• Queen Victoria’s reign and her influence over national identity.
• Rigid social norms, gender roles, and moral codes.
• Advances in science, technology, and culture which fuelled an age of innovation.
• The British Empire’s vast colonial influence and reach during this time.

18. The Ottoman Empire

The Ottoman Empire was a state that controlled much of Southeast Europe, Western Asia and North Africa from 1302–1922 (though its peak was in the 15th–17th centuries).

This empire was established by Osman I and after a long line of rulers, disintegrated immediately after World War I.

• The empire’s strategic geographic location influencing politics and trade.
• Various phases of expansion and contraction marked by numerous wars and sieges.
• Multicultural and multireligious nature of the empire and its impact on governance.
• Administrative and military systems created during the zenith of the empire, such as the Janissary corps.
• Internal problems and external pressures leading to the fall of the empire.

19. The Age of Enlightenment

The Age of Enlightenment, also known as the Age of Reason, was an intellectual and philosophical movement that dominated Europe during the 18th century.

The Enlightenment was characterized by revolutionary ideas in politics, philosophy, science, and communications – all of which shaped the modern world.

• The influence of thinkers such as Descartes, Locke, and Newton.
• The emphasis on reason, science, and respect for humanity.
• The Frankfurt School’s critique of mass production and consumer culture.
• The importance of education in society’s progression.
• The role of print culture in the spread of Enlightenment values.

20. The Scientific Revolution

The Scientific Revolution was a series of events in the 16th and 17th centuries that led to the birth of modern science.

During this time, new ideas in physics, astronomy, biology, anatomy, and chemistry transformed views of nature and society. It gave rise to the scientific method , which to this day is the gold standard for finding fact from fiction.

• The influence of scholars such as Copernicus, Galileo, and Kepler.
• Shift from a geocentric to a heliocentric model of the solar system.
• The development and refinement of the scientific method.
• Transition from qualitative to quantitative approaches in study.
• The impact of technological advancements on exploration and observation.

21. The Civil Rights Act of 1964

The Civil Rights Act of 1964 was a landmark piece of legislation passed in the United States that outlawed major forms of discrimination against racial, ethnic, national, and religious minorities and women.

The Act signaled a significant step in the progression of equal rights in the United States and was precipitated by a range of injustices, now visible on the television screens, as well as a range of court rulings from the newfound liberal majority in the supreme court of the USA.

• The momentum and progress of the civil rights movement, with leaders like Martin Luther King Jr.
• The impact of the televised 1963 March on Washington.
• Influence of previous court rulings, such as Brown v. Board of Education.
• The political climate at the time and support from President Lyndon B. Johnson.
• The long-term effects, including ongoing struggles with racial equality and the passage of additional rights legislation.

Read Next: Social and Cultural Context Examples

Before you Go

When thinking about historical context examples, it’s worth reflecting on how much the contextual factors influenced outcomes. Some people, known as determinists , believe that contextual factors determine outcomes , while others think they just influence outcomes. For example, in the current era of rapidly improving artificial intelligence, we can ask ourselves if AI is going to determine our futures (known as technological determinism) or if we have the power to choose our destiny, while AI acts as only a part of the story. For more, check out our guides on various types of determinism:

• Technological determinism
• Linguistic determinism
• Environmental determinism

Chris Drew (PhD)

Dr. Chris Drew is the founder of the Helpful Professor. He holds a PhD in education and has published over 20 articles in scholarly journals. He is the former editor of the Journal of Learning Development in Higher Education. [Image Descriptor: Photo of Chris]

• Chris Drew (PhD) https://helpfulprofessor.com/author/chris-drew-phd/ 5 Top Tips for Succeeding at University
• Chris Drew (PhD) https://helpfulprofessor.com/author/chris-drew-phd/ 50 Durable Goods Examples
• Chris Drew (PhD) https://helpfulprofessor.com/author/chris-drew-phd/ 100 Consumer Goods Examples
• Chris Drew (PhD) https://helpfulprofessor.com/author/chris-drew-phd/ 30 Globalization Pros and Cons

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Carceral Power in World Historical Context

Bridging the methodological and theoretical contributions of world-systems analysis and radical criminology.

• Zhandarka Kurti
• Zeynep Gönen

This paper invites a conversation between world-systems perspective and radical criminology to contribute to a more robust materialist, historical, and global understanding of policing, prisons, and carceral power. We trace the genealogy of these two approaches to the larger transformations of global capitalism in the 1960s and 1970s, including ruling class responses to capitalist crises vis a vis neoliberal restructuring as well as the social struggles waged by antisystemic movements. Both world-systems and radical criminology brought a critical and Marxist perspective to the liberal social sciences, yet dialogue between them has been lacking. On the one hand, world-systems analysis offers a structural explanation of capitalism but often side steps the role that carceral power plays to manage the system’s deepening contradictions. On the other hand, radical criminology focuses on carceral power but often limits its analysis to advanced core countries and not to the entire capitalist system. We argue that bringing these two critical approaches together can offer us a renewed Marxist perspective to the interrelated issues of capitalist crisis and carceral power and thus make possible new lines of inquiry and research best suited for grappling with the major contradictions of capitalism in the twenty-first century.

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• Published: 17 April 2024

The economic commitment of climate change

• Maximilian Kotz   ORCID: orcid.org/0000-0003-2564-5043 1 , 2 ,
• Anders Levermann   ORCID: orcid.org/0000-0003-4432-4704 1 , 2 &
• Leonie Wenz   ORCID: orcid.org/0000-0002-8500-1568 1 , 3  

Nature volume  628 ,  pages 551–557 ( 2024 ) Cite this article

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• Environmental economics
• Environmental health
• Interdisciplinary studies
• Projection and prediction

Global projections of macroeconomic climate-change damages typically consider impacts from average annual and national temperatures over long time horizons 1 , 2 , 3 , 4 , 5 , 6 . Here we use recent empirical findings from more than 1,600 regions worldwide over the past 40 years to project sub-national damages from temperature and precipitation, including daily variability and extremes 7 , 8 . Using an empirical approach that provides a robust lower bound on the persistence of impacts on economic growth, we find that the world economy is committed to an income reduction of 19% within the next 26 years independent of future emission choices (relative to a baseline without climate impacts, likely range of 11–29% accounting for physical climate and empirical uncertainty). These damages already outweigh the mitigation costs required to limit global warming to 2 °C by sixfold over this near-term time frame and thereafter diverge strongly dependent on emission choices. Committed damages arise predominantly through changes in average temperature, but accounting for further climatic components raises estimates by approximately 50% and leads to stronger regional heterogeneity. Committed losses are projected for all regions except those at very high latitudes, at which reductions in temperature variability bring benefits. The largest losses are committed at lower latitudes in regions with lower cumulative historical emissions and lower present-day income.

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Projections of the macroeconomic damage caused by future climate change are crucial to informing public and policy debates about adaptation, mitigation and climate justice. On the one hand, adaptation against climate impacts must be justified and planned on the basis of an understanding of their future magnitude and spatial distribution 9 . This is also of importance in the context of climate justice 10 , as well as to key societal actors, including governments, central banks and private businesses, which increasingly require the inclusion of climate risks in their macroeconomic forecasts to aid adaptive decision-making 11 , 12 . On the other hand, climate mitigation policy such as the Paris Climate Agreement is often evaluated by balancing the costs of its implementation against the benefits of avoiding projected physical damages. This evaluation occurs both formally through cost–benefit analyses 1 , 4 , 5 , 6 , as well as informally through public perception of mitigation and damage costs 13 .

Projections of future damages meet challenges when informing these debates, in particular the human biases relating to uncertainty and remoteness that are raised by long-term perspectives 14 . Here we aim to overcome such challenges by assessing the extent of economic damages from climate change to which the world is already committed by historical emissions and socio-economic inertia (the range of future emission scenarios that are considered socio-economically plausible 15 ). Such a focus on the near term limits the large uncertainties about diverging future emission trajectories, the resulting long-term climate response and the validity of applying historically observed climate–economic relations over long timescales during which socio-technical conditions may change considerably. As such, this focus aims to simplify the communication and maximize the credibility of projected economic damages from future climate change.

In projecting the future economic damages from climate change, we make use of recent advances in climate econometrics that provide evidence for impacts on sub-national economic growth from numerous components of the distribution of daily temperature and precipitation 3 , 7 , 8 . Using fixed-effects panel regression models to control for potential confounders, these studies exploit within-region variation in local temperature and precipitation in a panel of more than 1,600 regions worldwide, comprising climate and income data over the past 40 years, to identify the plausibly causal effects of changes in several climate variables on economic productivity 16 , 17 . Specifically, macroeconomic impacts have been identified from changing daily temperature variability, total annual precipitation, the annual number of wet days and extreme daily rainfall that occur in addition to those already identified from changing average temperature 2 , 3 , 18 . Moreover, regional heterogeneity in these effects based on the prevailing local climatic conditions has been found using interactions terms. The selection of these climate variables follows micro-level evidence for mechanisms related to the impacts of average temperatures on labour and agricultural productivity 2 , of temperature variability on agricultural productivity and health 7 , as well as of precipitation on agricultural productivity, labour outcomes and flood damages 8 (see Extended Data Table 1 for an overview, including more detailed references). References  7 , 8 contain a more detailed motivation for the use of these particular climate variables and provide extensive empirical tests about the robustness and nature of their effects on economic output, which are summarized in Methods . By accounting for these extra climatic variables at the sub-national level, we aim for a more comprehensive description of climate impacts with greater detail across both time and space.

Constraining the persistence of impacts

A key determinant and source of discrepancy in estimates of the magnitude of future climate damages is the extent to which the impact of a climate variable on economic growth rates persists. The two extreme cases in which these impacts persist indefinitely or only instantaneously are commonly referred to as growth or level effects 19 , 20 (see Methods section ‘Empirical model specification: fixed-effects distributed lag models’ for mathematical definitions). Recent work shows that future damages from climate change depend strongly on whether growth or level effects are assumed 20 . Following refs.  2 , 18 , we provide constraints on this persistence by using distributed lag models to test the significance of delayed effects separately for each climate variable. Notably, and in contrast to refs.  2 , 18 , we use climate variables in their first-differenced form following ref.  3 , implying a dependence of the growth rate on a change in climate variables. This choice means that a baseline specification without any lags constitutes a model prior of purely level effects, in which a permanent change in the climate has only an instantaneous effect on the growth rate 3 , 19 , 21 . By including lags, one can then test whether any effects may persist further. This is in contrast to the specification used by refs.  2 , 18 , in which climate variables are used without taking the first difference, implying a dependence of the growth rate on the level of climate variables. In this alternative case, the baseline specification without any lags constitutes a model prior of pure growth effects, in which a change in climate has an infinitely persistent effect on the growth rate. Consequently, including further lags in this alternative case tests whether the initial growth impact is recovered 18 , 19 , 21 . Both of these specifications suffer from the limiting possibility that, if too few lags are included, one might falsely accept the model prior. The limitations of including a very large number of lags, including loss of data and increasing statistical uncertainty with an increasing number of parameters, mean that such a possibility is likely. By choosing a specification in which the model prior is one of level effects, our approach is therefore conservative by design, avoiding assumptions of infinite persistence of climate impacts on growth and instead providing a lower bound on this persistence based on what is observable empirically (see Methods section ‘Empirical model specification: fixed-effects distributed lag models’ for further exposition of this framework). The conservative nature of such a choice is probably the reason that ref.  19 finds much greater consistency between the impacts projected by models that use the first difference of climate variables, as opposed to their levels.

We begin our empirical analysis of the persistence of climate impacts on growth using ten lags of the first-differenced climate variables in fixed-effects distributed lag models. We detect substantial effects on economic growth at time lags of up to approximately 8–10 years for the temperature terms and up to approximately 4 years for the precipitation terms (Extended Data Fig. 1 and Extended Data Table 2 ). Furthermore, evaluation by means of information criteria indicates that the inclusion of all five climate variables and the use of these numbers of lags provide a preferable trade-off between best-fitting the data and including further terms that could cause overfitting, in comparison with model specifications excluding climate variables or including more or fewer lags (Extended Data Fig. 3 , Supplementary Methods Section  1 and Supplementary Table 1 ). We therefore remove statistically insignificant terms at later lags (Supplementary Figs. 1 – 3 and Supplementary Tables 2 – 4 ). Further tests using Monte Carlo simulations demonstrate that the empirical models are robust to autocorrelation in the lagged climate variables (Supplementary Methods Section  2 and Supplementary Figs. 4 and 5 ), that information criteria provide an effective indicator for lag selection (Supplementary Methods Section  2 and Supplementary Fig. 6 ), that the results are robust to concerns of imperfect multicollinearity between climate variables and that including several climate variables is actually necessary to isolate their separate effects (Supplementary Methods Section  3 and Supplementary Fig. 7 ). We provide a further robustness check using a restricted distributed lag model to limit oscillations in the lagged parameter estimates that may result from autocorrelation, finding that it provides similar estimates of cumulative marginal effects to the unrestricted model (Supplementary Methods Section 4 and Supplementary Figs. 8 and 9 ). Finally, to explicitly account for any outstanding uncertainty arising from the precise choice of the number of lags, we include empirical models with marginally different numbers of lags in the error-sampling procedure of our projection of future damages. On the basis of the lag-selection procedure (the significance of lagged terms in Extended Data Fig. 1 and Extended Data Table 2 , as well as information criteria in Extended Data Fig. 3 ), we sample from models with eight to ten lags for temperature and four for precipitation (models shown in Supplementary Figs. 1 – 3 and Supplementary Tables 2 – 4 ). In summary, this empirical approach to constrain the persistence of climate impacts on economic growth rates is conservative by design in avoiding assumptions of infinite persistence, but nevertheless provides a lower bound on the extent of impact persistence that is robust to the numerous tests outlined above.

Committed damages until mid-century

We combine these empirical economic response functions (Supplementary Figs. 1 – 3 and Supplementary Tables 2 – 4 ) with an ensemble of 21 climate models (see Supplementary Table 5 ) from the Coupled Model Intercomparison Project Phase 6 (CMIP-6) 22 to project the macroeconomic damages from these components of physical climate change (see Methods for further details). Bias-adjusted climate models that provide a highly accurate reproduction of observed climatological patterns with limited uncertainty (Supplementary Table 6 ) are used to avoid introducing biases in the projections. Following a well-developed literature 2 , 3 , 19 , these projections do not aim to provide a prediction of future economic growth. Instead, they are a projection of the exogenous impact of future climate conditions on the economy relative to the baselines specified by socio-economic projections, based on the plausibly causal relationships inferred by the empirical models and assuming ceteris paribus. Other exogenous factors relevant for the prediction of economic output are purposefully assumed constant.

A Monte Carlo procedure that samples from climate model projections, empirical models with different numbers of lags and model parameter estimates (obtained by 1,000 block-bootstrap resamples of each of the regressions in Supplementary Figs. 1 – 3 and Supplementary Tables 2 – 4 ) is used to estimate the combined uncertainty from these sources. Given these uncertainty distributions, we find that projected global damages are statistically indistinguishable across the two most extreme emission scenarios until 2049 (at the 5% significance level; Fig. 1 ). As such, the climate damages occurring before this time constitute those to which the world is already committed owing to the combination of past emissions and the range of future emission scenarios that are considered socio-economically plausible 15 . These committed damages comprise a permanent income reduction of 19% on average globally (population-weighted average) in comparison with a baseline without climate-change impacts (with a likely range of 11–29%, following the likelihood classification adopted by the Intergovernmental Panel on Climate Change (IPCC); see caption of Fig. 1 ). Even though levels of income per capita generally still increase relative to those of today, this constitutes a permanent income reduction for most regions, including North America and Europe (each with median income reductions of approximately 11%) and with South Asia and Africa being the most strongly affected (each with median income reductions of approximately 22%; Fig. 1 ). Under a middle-of-the road scenario of future income development (SSP2, in which SSP stands for Shared Socio-economic Pathway), this corresponds to global annual damages in 2049 of 38 trillion in 2005 international dollars (likely range of 19–59 trillion 2005 international dollars). Compared with empirical specifications that assume pure growth or pure level effects, our preferred specification that provides a robust lower bound on the extent of climate impact persistence produces damages between these two extreme assumptions (Extended Data Fig. 3 ).

Estimates of the projected reduction in income per capita from changes in all climate variables based on empirical models of climate impacts on economic output with a robust lower bound on their persistence (Extended Data Fig. 1 ) under a low-emission scenario compatible with the 2 °C warming target and a high-emission scenario (SSP2-RCP2.6 and SSP5-RCP8.5, respectively) are shown in purple and orange, respectively. Shading represents the 34% and 10% confidence intervals reflecting the likely and very likely ranges, respectively (following the likelihood classification adopted by the IPCC), having estimated uncertainty from a Monte Carlo procedure, which samples the uncertainty from the choice of physical climate models, empirical models with different numbers of lags and bootstrapped estimates of the regression parameters shown in Supplementary Figs. 1 – 3 . Vertical dashed lines show the time at which the climate damages of the two emission scenarios diverge at the 5% and 1% significance levels based on the distribution of differences between emission scenarios arising from the uncertainty sampling discussed above. Note that uncertainty in the difference of the two scenarios is smaller than the combined uncertainty of the two respective scenarios because samples of the uncertainty (climate model and empirical model choice, as well as model parameter bootstrap) are consistent across the two emission scenarios, hence the divergence of damages occurs while the uncertainty bounds of the two separate damage scenarios still overlap. Estimates of global mitigation costs from the three IAMs that provide results for the SSP2 baseline and SSP2-RCP2.6 scenario are shown in light green in the top panel, with the median of these estimates shown in bold.

Damages already outweigh mitigation costs

We compare the damages to which the world is committed over the next 25 years to estimates of the mitigation costs required to achieve the Paris Climate Agreement. Taking estimates of mitigation costs from the three integrated assessment models (IAMs) in the IPCC AR6 database 23 that provide results under comparable scenarios (SSP2 baseline and SSP2-RCP2.6, in which RCP stands for Representative Concentration Pathway), we find that the median committed climate damages are larger than the median mitigation costs in 2050 (six trillion in 2005 international dollars) by a factor of approximately six (note that estimates of mitigation costs are only provided every 10 years by the IAMs and so a comparison in 2049 is not possible). This comparison simply aims to compare the magnitude of future damages against mitigation costs, rather than to conduct a formal cost–benefit analysis of transitioning from one emission path to another. Formal cost–benefit analyses typically find that the net benefits of mitigation only emerge after 2050 (ref.  5 ), which may lead some to conclude that physical damages from climate change are simply not large enough to outweigh mitigation costs until the second half of the century. Our simple comparison of their magnitudes makes clear that damages are actually already considerably larger than mitigation costs and the delayed emergence of net mitigation benefits results primarily from the fact that damages across different emission paths are indistinguishable until mid-century (Fig. 1 ).

Although these near-term damages constitute those to which the world is already committed, we note that damage estimates diverge strongly across emission scenarios after 2049, conveying the clear benefits of mitigation from a purely economic point of view that have been emphasized in previous studies 4 , 24 . As well as the uncertainties assessed in Fig. 1 , these conclusions are robust to structural choices, such as the timescale with which changes in the moderating variables of the empirical models are estimated (Supplementary Figs. 10 and 11 ), as well as the order in which one accounts for the intertemporal and international components of currency comparison (Supplementary Fig. 12 ; see Methods for further details).

Damages from variability and extremes

Committed damages primarily arise through changes in average temperature (Fig. 2 ). This reflects the fact that projected changes in average temperature are larger than those in other climate variables when expressed as a function of their historical interannual variability (Extended Data Fig. 4 ). Because the historical variability is that on which the empirical models are estimated, larger projected changes in comparison with this variability probably lead to larger future impacts in a purely statistical sense. From a mechanistic perspective, one may plausibly interpret this result as implying that future changes in average temperature are the most unprecedented from the perspective of the historical fluctuations to which the economy is accustomed and therefore will cause the most damage. This insight may prove useful in terms of guiding adaptation measures to the sources of greatest damage.

Estimates of the median projected reduction in sub-national income per capita across emission scenarios (SSP2-RCP2.6 and SSP2-RCP8.5) as well as climate model, empirical model and model parameter uncertainty in the year in which climate damages diverge at the 5% level (2049, as identified in Fig. 1 ). a , Impacts arising from all climate variables. b – f , Impacts arising separately from changes in annual mean temperature ( b ), daily temperature variability ( c ), total annual precipitation ( d ), the annual number of wet days (>1 mm) ( e ) and extreme daily rainfall ( f ) (see Methods for further definitions). Data on national administrative boundaries are obtained from the GADM database version 3.6 and are freely available for academic use ( https://gadm.org/ ).

Nevertheless, future damages based on empirical models that consider changes in annual average temperature only and exclude the other climate variables constitute income reductions of only 13% in 2049 (Extended Data Fig. 5a , likely range 5–21%). This suggests that accounting for the other components of the distribution of temperature and precipitation raises net damages by nearly 50%. This increase arises through the further damages that these climatic components cause, but also because their inclusion reveals a stronger negative economic response to average temperatures (Extended Data Fig. 5b ). The latter finding is consistent with our Monte Carlo simulations, which suggest that the magnitude of the effect of average temperature on economic growth is underestimated unless accounting for the impacts of other correlated climate variables (Supplementary Fig. 7 ).

In terms of the relative contributions of the different climatic components to overall damages, we find that accounting for daily temperature variability causes the largest increase in overall damages relative to empirical frameworks that only consider changes in annual average temperature (4.9 percentage points, likely range 2.4–8.7 percentage points, equivalent to approximately 10 trillion international dollars). Accounting for precipitation causes smaller increases in overall damages, which are—nevertheless—equivalent to approximately 1.2 trillion international dollars: 0.01 percentage points (−0.37–0.33 percentage points), 0.34 percentage points (0.07–0.90 percentage points) and 0.36 percentage points (0.13–0.65 percentage points) from total annual precipitation, the number of wet days and extreme daily precipitation, respectively. Moreover, climate models seem to underestimate future changes in temperature variability 25 and extreme precipitation 26 , 27 in response to anthropogenic forcing as compared with that observed historically, suggesting that the true impacts from these variables may be larger.

The distribution of committed damages

The spatial distribution of committed damages (Fig. 2a ) reflects a complex interplay between the patterns of future change in several climatic components and those of historical economic vulnerability to changes in those variables. Damages resulting from increasing annual mean temperature (Fig. 2b ) are negative almost everywhere globally, and larger at lower latitudes in regions in which temperatures are already higher and economic vulnerability to temperature increases is greatest (see the response heterogeneity to mean temperature embodied in Extended Data Fig. 1a ). This occurs despite the amplified warming projected at higher latitudes 28 , suggesting that regional heterogeneity in economic vulnerability to temperature changes outweighs heterogeneity in the magnitude of future warming (Supplementary Fig. 13a ). Economic damages owing to daily temperature variability (Fig. 2c ) exhibit a strong latitudinal polarisation, primarily reflecting the physical response of daily variability to greenhouse forcing in which increases in variability across lower latitudes (and Europe) contrast decreases at high latitudes 25 (Supplementary Fig. 13b ). These two temperature terms are the dominant determinants of the pattern of overall damages (Fig. 2a ), which exhibits a strong polarity with damages across most of the globe except at the highest northern latitudes. Future changes in total annual precipitation mainly bring economic benefits except in regions of drying, such as the Mediterranean and central South America (Fig. 2d and Supplementary Fig. 13c ), but these benefits are opposed by changes in the number of wet days, which produce damages with a similar pattern of opposite sign (Fig. 2e and Supplementary Fig. 13d ). By contrast, changes in extreme daily rainfall produce damages in all regions, reflecting the intensification of daily rainfall extremes over global land areas 29 , 30 (Fig. 2f and Supplementary Fig. 13e ).

The spatial distribution of committed damages implies considerable injustice along two dimensions: culpability for the historical emissions that have caused climate change and pre-existing levels of socio-economic welfare. Spearman’s rank correlations indicate that committed damages are significantly larger in countries with smaller historical cumulative emissions, as well as in regions with lower current income per capita (Fig. 3 ). This implies that those countries that will suffer the most from the damages already committed are those that are least responsible for climate change and which also have the least resources to adapt to it.

Estimates of the median projected change in national income per capita across emission scenarios (RCP2.6 and RCP8.5) as well as climate model, empirical model and model parameter uncertainty in the year in which climate damages diverge at the 5% level (2049, as identified in Fig. 1 ) are plotted against cumulative national emissions per capita in 2020 (from the Global Carbon Project) and coloured by national income per capita in 2020 (from the World Bank) in a and vice versa in b . In each panel, the size of each scatter point is weighted by the national population in 2020 (from the World Bank). Inset numbers indicate the Spearman’s rank correlation ρ and P -values for a hypothesis test whose null hypothesis is of no correlation, as well as the Spearman’s rank correlation weighted by national population.

To further quantify this heterogeneity, we assess the difference in committed damages between the upper and lower quartiles of regions when ranked by present income levels and historical cumulative emissions (using a population weighting to both define the quartiles and estimate the group averages). On average, the quartile of countries with lower income are committed to an income loss that is 8.9 percentage points (or 61%) greater than the upper quartile (Extended Data Fig. 6 ), with a likely range of 3.8–14.7 percentage points across the uncertainty sampling of our damage projections (following the likelihood classification adopted by the IPCC). Similarly, the quartile of countries with lower historical cumulative emissions are committed to an income loss that is 6.9 percentage points (or 40%) greater than the upper quartile, with a likely range of 0.27–12 percentage points. These patterns reemphasize the prevalence of injustice in climate impacts 31 , 32 , 33 in the context of the damages to which the world is already committed by historical emissions and socio-economic inertia.

Contextualizing the magnitude of damages

The magnitude of projected economic damages exceeds previous literature estimates 2 , 3 , arising from several developments made on previous approaches. Our estimates are larger than those of ref.  2 (see first row of Extended Data Table 3 ), primarily because of the facts that sub-national estimates typically show a steeper temperature response (see also refs.  3 , 34 ) and that accounting for other climatic components raises damage estimates (Extended Data Fig. 5 ). However, we note that our empirical approach using first-differenced climate variables is conservative compared with that of ref.  2 in regard to the persistence of climate impacts on growth (see introduction and Methods section ‘Empirical model specification: fixed-effects distributed lag models’), an important determinant of the magnitude of long-term damages 19 , 21 . Using a similar empirical specification to ref.  2 , which assumes infinite persistence while maintaining the rest of our approach (sub-national data and further climate variables), produces considerably larger damages (purple curve of Extended Data Fig. 3 ). Compared with studies that do take the first difference of climate variables 3 , 35 , our estimates are also larger (see second and third rows of Extended Data Table 3 ). The inclusion of further climate variables (Extended Data Fig. 5 ) and a sufficient number of lags to more adequately capture the extent of impact persistence (Extended Data Figs. 1 and 2 ) are the main sources of this difference, as is the use of specifications that capture nonlinearities in the temperature response when compared with ref.  35 . In summary, our estimates develop on previous studies by incorporating the latest data and empirical insights 7 , 8 , as well as in providing a robust empirical lower bound on the persistence of impacts on economic growth, which constitutes a middle ground between the extremes of the growth-versus-levels debate 19 , 21 (Extended Data Fig. 3 ).

Compared with the fraction of variance explained by the empirical models historically (<5%), the projection of reductions in income of 19% may seem large. This arises owing to the fact that projected changes in climatic conditions are much larger than those that were experienced historically, particularly for changes in average temperature (Extended Data Fig. 4 ). As such, any assessment of future climate-change impacts necessarily requires an extrapolation outside the range of the historical data on which the empirical impact models were evaluated. Nevertheless, these models constitute the most state-of-the-art methods for inference of plausibly causal climate impacts based on observed data. Moreover, we take explicit steps to limit out-of-sample extrapolation by capping the moderating variables of the interaction terms at the 95th percentile of the historical distribution (see Methods ). This avoids extrapolating the marginal effects outside what was observed historically. Given the nonlinear response of economic output to annual mean temperature (Extended Data Fig. 1 and Extended Data Table 2 ), this is a conservative choice that limits the magnitude of damages that we project. Furthermore, back-of-the-envelope calculations indicate that the projected damages are consistent with the magnitude and patterns of historical economic development (see Supplementary Discussion Section  5 ).

Missing impacts and spatial spillovers

Despite assessing several climatic components from which economic impacts have recently been identified 3 , 7 , 8 , this assessment of aggregate climate damages should not be considered comprehensive. Important channels such as impacts from heatwaves 31 , sea-level rise 36 , tropical cyclones 37 and tipping points 38 , 39 , as well as non-market damages such as those to ecosystems 40 and human health 41 , are not considered in these estimates. Sea-level rise is unlikely to be feasibly incorporated into empirical assessments such as this because historical sea-level variability is mostly small. Non-market damages are inherently intractable within our estimates of impacts on aggregate monetary output and estimates of these impacts could arguably be considered as extra to those identified here. Recent empirical work suggests that accounting for these channels would probably raise estimates of these committed damages, with larger damages continuing to arise in the global south 31 , 36 , 37 , 38 , 39 , 40 , 41 , 42 .

Moreover, our main empirical analysis does not explicitly evaluate the potential for impacts in local regions to produce effects that ‘spill over’ into other regions. Such effects may further mitigate or amplify the impacts we estimate, for example, if companies relocate production from one affected region to another or if impacts propagate along supply chains. The current literature indicates that trade plays a substantial role in propagating spillover effects 43 , 44 , making their assessment at the sub-national level challenging without available data on sub-national trade dependencies. Studies accounting for only spatially adjacent neighbours indicate that negative impacts in one region induce further negative impacts in neighbouring regions 45 , 46 , 47 , 48 , suggesting that our projected damages are probably conservative by excluding these effects. In Supplementary Fig. 14 , we assess spillovers from neighbouring regions using a spatial-lag model. For simplicity, this analysis excludes temporal lags, focusing only on contemporaneous effects. The results show that accounting for spatial spillovers can amplify the overall magnitude, and also the heterogeneity, of impacts. Consistent with previous literature, this indicates that the overall magnitude (Fig. 1 ) and heterogeneity (Fig. 3 ) of damages that we project in our main specification may be conservative without explicitly accounting for spillovers. We note that further analysis that addresses both spatially and trade-connected spillovers, while also accounting for delayed impacts using temporal lags, would be necessary to adequately address this question fully. These approaches offer fruitful avenues for further research but are beyond the scope of this manuscript, which primarily aims to explore the impacts of different climate conditions and their persistence.

Policy implications

We find that the economic damages resulting from climate change until 2049 are those to which the world economy is already committed and that these greatly outweigh the costs required to mitigate emissions in line with the 2 °C target of the Paris Climate Agreement (Fig. 1 ). This assessment is complementary to formal analyses of the net costs and benefits associated with moving from one emission path to another, which typically find that net benefits of mitigation only emerge in the second half of the century 5 . Our simple comparison of the magnitude of damages and mitigation costs makes clear that this is primarily because damages are indistinguishable across emissions scenarios—that is, committed—until mid-century (Fig. 1 ) and that they are actually already much larger than mitigation costs. For simplicity, and owing to the availability of data, we compare damages to mitigation costs at the global level. Regional estimates of mitigation costs may shed further light on the national incentives for mitigation to which our results already hint, of relevance for international climate policy. Although these damages are committed from a mitigation perspective, adaptation may provide an opportunity to reduce them. Moreover, the strong divergence of damages after mid-century reemphasizes the clear benefits of mitigation from a purely economic perspective, as highlighted in previous studies 1 , 4 , 6 , 24 .

Historical climate data

Historical daily 2-m temperature and precipitation totals (in mm) are obtained for the period 1979–2019 from the W5E5 database. The W5E5 dataset comes from ERA-5, a state-of-the-art reanalysis of historical observations, but has been bias-adjusted by applying version 2.0 of the WATCH Forcing Data to ERA-5 reanalysis data and precipitation data from version 2.3 of the Global Precipitation Climatology Project to better reflect ground-based measurements 49 , 50 , 51 . We obtain these data on a 0.5° × 0.5° grid from the Inter-Sectoral Impact Model Intercomparison Project (ISIMIP) database. Notably, these historical data have been used to bias-adjust future climate projections from CMIP-6 (see the following section), ensuring consistency between the distribution of historical daily weather on which our empirical models were estimated and the climate projections used to estimate future damages. These data are publicly available from the ISIMIP database. See refs.  7 , 8 for robustness tests of the empirical models to the choice of climate data reanalysis products.

Future climate data

Daily 2-m temperature and precipitation totals (in mm) are taken from 21 climate models participating in CMIP-6 under a high (RCP8.5) and a low (RCP2.6) greenhouse gas emission scenario from 2015 to 2100. The data have been bias-adjusted and statistically downscaled to a common half-degree grid to reflect the historical distribution of daily temperature and precipitation of the W5E5 dataset using the trend-preserving method developed by the ISIMIP 50 , 52 . As such, the climate model data reproduce observed climatological patterns exceptionally well (Supplementary Table 5 ). Gridded data are publicly available from the ISIMIP database.

Historical economic data

Historical economic data come from the DOSE database of sub-national economic output 53 . We use a recent revision to the DOSE dataset that provides data across 83 countries, 1,660 sub-national regions with varying temporal coverage from 1960 to 2019. Sub-national units constitute the first administrative division below national, for example, states for the USA and provinces for China. Data come from measures of gross regional product per capita (GRPpc) or income per capita in local currencies, reflecting the values reported in national statistical agencies, yearbooks and, in some cases, academic literature. We follow previous literature 3 , 7 , 8 , 54 and assess real sub-national output per capita by first converting values from local currencies to US dollars to account for diverging national inflationary tendencies and then account for US inflation using a US deflator. Alternatively, one might first account for national inflation and then convert between currencies. Supplementary Fig. 12 demonstrates that our conclusions are consistent when accounting for price changes in the reversed order, although the magnitude of estimated damages varies. See the documentation of the DOSE dataset for further discussion of these choices. Conversions between currencies are conducted using exchange rates from the FRED database of the Federal Reserve Bank of St. Louis 55 and the national deflators from the World Bank 56 .

Future socio-economic data

Baseline gridded gross domestic product (GDP) and population data for the period 2015–2100 are taken from the middle-of-the-road scenario SSP2 (ref.  15 ). Population data have been downscaled to a half-degree grid by the ISIMIP following the methodologies of refs.  57 , 58 , which we then aggregate to the sub-national level of our economic data using the spatial aggregation procedure described below. Because current methodologies for downscaling the GDP of the SSPs use downscaled population to do so, per-capita estimates of GDP with a realistic distribution at the sub-national level are not readily available for the SSPs. We therefore use national-level GDP per capita (GDPpc) projections for all sub-national regions of a given country, assuming homogeneity within countries in terms of baseline GDPpc. Here we use projections that have been updated to account for the impact of the COVID-19 pandemic on the trajectory of future income, while remaining consistent with the long-term development of the SSPs 59 . The choice of baseline SSP alters the magnitude of projected climate damages in monetary terms, but when assessed in terms of percentage change from the baseline, the choice of socio-economic scenario is inconsequential. Gridded SSP population data and national-level GDPpc data are publicly available from the ISIMIP database. Sub-national estimates as used in this study are available in the code and data replication files.

Climate variables

Following recent literature 3 , 7 , 8 , we calculate an array of climate variables for which substantial impacts on macroeconomic output have been identified empirically, supported by further evidence at the micro level for plausible underlying mechanisms. See refs.  7 , 8 for an extensive motivation for the use of these particular climate variables and for detailed empirical tests on the nature and robustness of their effects on economic output. To summarize, these studies have found evidence for independent impacts on economic growth rates from annual average temperature, daily temperature variability, total annual precipitation, the annual number of wet days and extreme daily rainfall. Assessments of daily temperature variability were motivated by evidence of impacts on agricultural output and human health, as well as macroeconomic literature on the impacts of volatility on growth when manifest in different dimensions, such as government spending, exchange rates and even output itself 7 . Assessments of precipitation impacts were motivated by evidence of impacts on agricultural productivity, metropolitan labour outcomes and conflict, as well as damages caused by flash flooding 8 . See Extended Data Table 1 for detailed references to empirical studies of these physical mechanisms. Marked impacts of daily temperature variability, total annual precipitation, the number of wet days and extreme daily rainfall on macroeconomic output were identified robustly across different climate datasets, spatial aggregation schemes, specifications of regional time trends and error-clustering approaches. They were also found to be robust to the consideration of temperature extremes 7 , 8 . Furthermore, these climate variables were identified as having independent effects on economic output 7 , 8 , which we further explain here using Monte Carlo simulations to demonstrate the robustness of the results to concerns of imperfect multicollinearity between climate variables (Supplementary Methods Section  2 ), as well as by using information criteria (Supplementary Table 1 ) to demonstrate that including several lagged climate variables provides a preferable trade-off between optimally describing the data and limiting the possibility of overfitting.

We calculate these variables from the distribution of daily, d , temperature, T x , d , and precipitation, P x , d , at the grid-cell, x , level for both the historical and future climate data. As well as annual mean temperature, \({\bar{T}}_{x,y}\) , and annual total precipitation, P x , y , we calculate annual, y , measures of daily temperature variability, \({\widetilde{T}}_{x,y}\) :

the number of wet days, Pwd x , y :

and extreme daily rainfall:

in which T x , d , m , y is the grid-cell-specific daily temperature in month m and year y , \({\bar{T}}_{x,m,{y}}\) is the year and grid-cell-specific monthly, m , mean temperature, D m and D y the number of days in a given month m or year y , respectively, H the Heaviside step function, 1 mm the threshold used to define wet days and P 99.9 x is the 99.9th percentile of historical (1979–2019) daily precipitation at the grid-cell level. Units of the climate measures are degrees Celsius for annual mean temperature and daily temperature variability, millimetres for total annual precipitation and extreme daily precipitation, and simply the number of days for the annual number of wet days.

We also calculated weighted standard deviations of monthly rainfall totals as also used in ref.  8 but do not include them in our projections as we find that, when accounting for delayed effects, their effect becomes statistically indistinct and is better captured by changes in total annual rainfall.

Spatial aggregation

We aggregate grid-cell-level historical and future climate measures, as well as grid-cell-level future GDPpc and population, to the level of the first administrative unit below national level of the GADM database, using an area-weighting algorithm that estimates the portion of each grid cell falling within an administrative boundary. We use this as our baseline specification following previous findings that the effect of area or population weighting at the sub-national level is negligible 7 , 8 .

Empirical model specification: fixed-effects distributed lag models

Following a wide range of climate econometric literature 16 , 60 , we use panel regression models with a selection of fixed effects and time trends to isolate plausibly exogenous variation with which to maximize confidence in a causal interpretation of the effects of climate on economic growth rates. The use of region fixed effects, μ r , accounts for unobserved time-invariant differences between regions, such as prevailing climatic norms and growth rates owing to historical and geopolitical factors. The use of yearly fixed effects, η y , accounts for regionally invariant annual shocks to the global climate or economy such as the El Niño–Southern Oscillation or global recessions. In our baseline specification, we also include region-specific linear time trends, k r y , to exclude the possibility of spurious correlations resulting from common slow-moving trends in climate and growth.

The persistence of climate impacts on economic growth rates is a key determinant of the long-term magnitude of damages. Methods for inferring the extent of persistence in impacts on growth rates have typically used lagged climate variables to evaluate the presence of delayed effects or catch-up dynamics 2 , 18 . For example, consider starting from a model in which a climate condition, C r , y , (for example, annual mean temperature) affects the growth rate, Δlgrp r , y (the first difference of the logarithm of gross regional product) of region r in year y :

which we refer to as a ‘pure growth effects’ model in the main text. Typically, further lags are included,

and the cumulative effect of all lagged terms is evaluated to assess the extent to which climate impacts on growth rates persist. Following ref.  18 , in the case that,

the implication is that impacts on the growth rate persist up to NL years after the initial shock (possibly to a weaker or a stronger extent), whereas if

then the initial impact on the growth rate is recovered after NL years and the effect is only one on the level of output. However, we note that such approaches are limited by the fact that, when including an insufficient number of lags to detect a recovery of the growth rates, one may find equation ( 6 ) to be satisfied and incorrectly assume that a change in climatic conditions affects the growth rate indefinitely. In practice, given a limited record of historical data, including too few lags to confidently conclude in an infinitely persistent impact on the growth rate is likely, particularly over the long timescales over which future climate damages are often projected 2 , 24 . To avoid this issue, we instead begin our analysis with a model for which the level of output, lgrp r , y , depends on the level of a climate variable, C r , y :

Given the non-stationarity of the level of output, we follow the literature 19 and estimate such an equation in first-differenced form as,

which we refer to as a model of ‘pure level effects’ in the main text. This model constitutes a baseline specification in which a permanent change in the climate variable produces an instantaneous impact on the growth rate and a permanent effect only on the level of output. By including lagged variables in this specification,

we are able to test whether the impacts on the growth rate persist any further than instantaneously by evaluating whether α L  > 0 are statistically significantly different from zero. Even though this framework is also limited by the possibility of including too few lags, the choice of a baseline model specification in which impacts on the growth rate do not persist means that, in the case of including too few lags, the framework reverts to the baseline specification of level effects. As such, this framework is conservative with respect to the persistence of impacts and the magnitude of future damages. It naturally avoids assumptions of infinite persistence and we are able to interpret any persistence that we identify with equation ( 9 ) as a lower bound on the extent of climate impact persistence on growth rates. See the main text for further discussion of this specification choice, in particular about its conservative nature compared with previous literature estimates, such as refs.  2 , 18 .

We allow the response to climatic changes to vary across regions, using interactions of the climate variables with historical average (1979–2019) climatic conditions reflecting heterogenous effects identified in previous work 7 , 8 . Following this previous work, the moderating variables of these interaction terms constitute the historical average of either the variable itself or of the seasonal temperature difference, \({\hat{T}}_{r}\) , or annual mean temperature, \({\bar{T}}_{r}\) , in the case of daily temperature variability 7 and extreme daily rainfall, respectively 8 .

The resulting regression equation with N and M lagged variables, respectively, reads:

in which Δlgrp r , y is the annual, regional GRPpc growth rate, measured as the first difference of the logarithm of real GRPpc, following previous work 2 , 3 , 7 , 8 , 18 , 19 . Fixed-effects regressions were run using the fixest package in R (ref.  61 ).

Estimates of the coefficients of interest α i , L are shown in Extended Data Fig. 1 for N  =  M  = 10 lags and for our preferred choice of the number of lags in Supplementary Figs. 1 – 3 . In Extended Data Fig. 1 , errors are shown clustered at the regional level, but for the construction of damage projections, we block-bootstrap the regressions by region 1,000 times to provide a range of parameter estimates with which to sample the projection uncertainty (following refs.  2 , 31 ).

Spatial-lag model

In Supplementary Fig. 14 , we present the results from a spatial-lag model that explores the potential for climate impacts to ‘spill over’ into spatially neighbouring regions. We measure the distance between centroids of each pair of sub-national regions and construct spatial lags that take the average of the first-differenced climate variables and their interaction terms over neighbouring regions that are at distances of 0–500, 500–1,000, 1,000–1,500 and 1,500–2000 km (spatial lags, ‘SL’, 1 to 4). For simplicity, we then assess a spatial-lag model without temporal lags to assess spatial spillovers of contemporaneous climate impacts. This model takes the form:

in which SL indicates the spatial lag of each climate variable and interaction term. In Supplementary Fig. 14 , we plot the cumulative marginal effect of each climate variable at different baseline climate conditions by summing the coefficients for each climate variable and interaction term, for example, for average temperature impacts as:

These cumulative marginal effects can be regarded as the overall spatially dependent impact to an individual region given a one-unit shock to a climate variable in that region and all neighbouring regions at a given value of the moderating variable of the interaction term.

Constructing projections of economic damage from future climate change

We construct projections of future climate damages by applying the coefficients estimated in equation ( 10 ) and shown in Supplementary Tables 2 – 4 (when including only lags with statistically significant effects in specifications that limit overfitting; see Supplementary Methods Section  1 ) to projections of future climate change from the CMIP-6 models. Year-on-year changes in each primary climate variable of interest are calculated to reflect the year-to-year variations used in the empirical models. 30-year moving averages of the moderating variables of the interaction terms are calculated to reflect the long-term average of climatic conditions that were used for the moderating variables in the empirical models. By using moving averages in the projections, we account for the changing vulnerability to climate shocks based on the evolving long-term conditions (Supplementary Figs. 10 and 11 show that the results are robust to the precise choice of the window of this moving average). Although these climate variables are not differenced, the fact that the bias-adjusted climate models reproduce observed climatological patterns across regions for these moderating variables very accurately (Supplementary Table 6 ) with limited spread across models (<3%) precludes the possibility that any considerable bias or uncertainty is introduced by this methodological choice. However, we impose caps on these moderating variables at the 95th percentile at which they were observed in the historical data to prevent extrapolation of the marginal effects outside the range in which the regressions were estimated. This is a conservative choice that limits the magnitude of our damage projections.

Time series of primary climate variables and moderating climate variables are then combined with estimates of the empirical model parameters to evaluate the regression coefficients in equation ( 10 ), producing a time series of annual GRPpc growth-rate reductions for a given emission scenario, climate model and set of empirical model parameters. The resulting time series of growth-rate impacts reflects those occurring owing to future climate change. By contrast, a future scenario with no climate change would be one in which climate variables do not change (other than with random year-to-year fluctuations) and hence the time-averaged evaluation of equation ( 10 ) would be zero. Our approach therefore implicitly compares the future climate-change scenario to this no-climate-change baseline scenario.

The time series of growth-rate impacts owing to future climate change in region r and year y , δ r , y , are then added to the future baseline growth rates, π r , y (in log-diff form), obtained from the SSP2 scenario to yield trajectories of damaged GRPpc growth rates, ρ r , y . These trajectories are aggregated over time to estimate the future trajectory of GRPpc with future climate impacts:

in which GRPpc r , y =2020 is the initial log level of GRPpc. We begin damage estimates in 2020 to reflect the damages occurring since the end of the period for which we estimate the empirical models (1979–2019) and to match the timing of mitigation-cost estimates from most IAMs (see below).

For each emission scenario, this procedure is repeated 1,000 times while randomly sampling from the selection of climate models, the selection of empirical models with different numbers of lags (shown in Supplementary Figs. 1 – 3 and Supplementary Tables 2 – 4 ) and bootstrapped estimates of the regression parameters. The result is an ensemble of future GRPpc trajectories that reflect uncertainty from both physical climate change and the structural and sampling uncertainty of the empirical models.

Estimates of mitigation costs

We obtain IPCC estimates of the aggregate costs of emission mitigation from the AR6 Scenario Explorer and Database hosted by IIASA 23 . Specifically, we search the AR6 Scenarios Database World v1.1 for IAMs that provided estimates of global GDP and population under both a SSP2 baseline and a SSP2-RCP2.6 scenario to maintain consistency with the socio-economic and emission scenarios of the climate damage projections. We find five IAMs that provide data for these scenarios, namely, MESSAGE-GLOBIOM 1.0, REMIND-MAgPIE 1.5, AIM/GCE 2.0, GCAM 4.2 and WITCH-GLOBIOM 3.1. Of these five IAMs, we use the results only from the first three that passed the IPCC vetting procedure for reproducing historical emission and climate trajectories. We then estimate global mitigation costs as the percentage difference in global per capita GDP between the SSP2 baseline and the SSP2-RCP2.6 emission scenario. In the case of one of these IAMs, estimates of mitigation costs begin in 2020, whereas in the case of two others, mitigation costs begin in 2010. The mitigation cost estimates before 2020 in these two IAMs are mostly negligible, and our choice to begin comparison with damage estimates in 2020 is conservative with respect to the relative weight of climate damages compared with mitigation costs for these two IAMs.

Data availability

Data on economic production and ERA-5 climate data are publicly available at https://doi.org/10.5281/zenodo.4681306 (ref. 62 ) and https://www.ecmwf.int/en/forecasts/datasets/reanalysis-datasets/era5 , respectively. Data on mitigation costs are publicly available at https://data.ene.iiasa.ac.at/ar6/#/downloads . Processed climate and economic data, as well as all other necessary data for reproduction of the results, are available at the public repository https://doi.org/10.5281/zenodo.10562951  (ref. 63 ).

Code availability

All code necessary for reproduction of the results is available at the public repository https://doi.org/10.5281/zenodo.10562951  (ref. 63 ).

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Acknowledgements

We gratefully acknowledge financing from the Volkswagen Foundation and the Deutsche Gesellschaft für Internationale Zusammenarbeit (GIZ) GmbH on behalf of the Government of the Federal Republic of Germany and Federal Ministry for Economic Cooperation and Development (BMZ).

Open access funding provided by Potsdam-Institut für Klimafolgenforschung (PIK) e.V.

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Extended data figures and tables

Extended data fig. 1 constraining the persistence of historical climate impacts on economic growth rates..

The results of a panel-based fixed-effects distributed lag model for the effects of annual mean temperature ( a ), daily temperature variability ( b ), total annual precipitation ( c ), the number of wet days ( d ) and extreme daily precipitation ( e ) on sub-national economic growth rates. Point estimates show the effects of a 1 °C or one standard deviation increase (for temperature and precipitation variables, respectively) at the lower quartile, median and upper quartile of the relevant moderating variable (green, orange and purple, respectively) at different lagged periods after the initial shock (note that these are not cumulative effects). Climate variables are used in their first-differenced form (see main text for discussion) and the moderating climate variables are the annual mean temperature, seasonal temperature difference, total annual precipitation, number of wet days and annual mean temperature, respectively, in panels a – e (see Methods for further discussion). Error bars show the 95% confidence intervals having clustered standard errors by region. The within-region R 2 , Bayesian and Akaike information criteria for the model are shown at the top of the figure. This figure shows results with ten lags for each variable to demonstrate the observed levels of persistence, but our preferred specifications remove later lags based on the statistical significance of terms shown above and the information criteria shown in Extended Data Fig. 2 . The resulting models without later lags are shown in Supplementary Figs. 1 – 3 .

Extended Data Fig. 2 Incremental lag-selection procedure using information criteria and within-region R 2 .

Starting from a panel-based fixed-effects distributed lag model estimating the effects of climate on economic growth using the real historical data (as in equation ( 4 )) with ten lags for all climate variables (as shown in Extended Data Fig. 1 ), lags are incrementally removed for one climate variable at a time. The resulting Bayesian and Akaike information criteria are shown in a – e and f – j , respectively, and the within-region R 2 and number of observations in k – o and p – t , respectively. Different rows show the results when removing lags from different climate variables, ordered from top to bottom as annual mean temperature, daily temperature variability, total annual precipitation, the number of wet days and extreme annual precipitation. Information criteria show minima at approximately four lags for precipitation variables and ten to eight for temperature variables, indicating that including these numbers of lags does not lead to overfitting. See Supplementary Table 1 for an assessment using information criteria to determine whether including further climate variables causes overfitting.

Extended Data Fig. 3 Damages in our preferred specification that provides a robust lower bound on the persistence of climate impacts on economic growth versus damages in specifications of pure growth or pure level effects.

Estimates of future damages as shown in Fig. 1 but under the emission scenario RCP8.5 for three separate empirical specifications: in orange our preferred specification, which provides an empirical lower bound on the persistence of climate impacts on economic growth rates while avoiding assumptions of infinite persistence (see main text for further discussion); in purple a specification of ‘pure growth effects’ in which the first difference of climate variables is not taken and no lagged climate variables are included (the baseline specification of ref.  2 ); and in pink a specification of ‘pure level effects’ in which the first difference of climate variables is taken but no lagged terms are included.

Extended Data Fig. 4 Climate changes in different variables as a function of historical interannual variability.

Changes in each climate variable of interest from 1979–2019 to 2035–2065 under the high-emission scenario SSP5-RCP8.5, expressed as a percentage of the historical variability of each measure. Historical variability is estimated as the standard deviation of each detrended climate variable over the period 1979–2019 during which the empirical models were identified (detrending is appropriate because of the inclusion of region-specific linear time trends in the empirical models). See Supplementary Fig. 13 for changes expressed in standard units. Data on national administrative boundaries are obtained from the GADM database version 3.6 and are freely available for academic use ( https://gadm.org/ ).

Extended Data Fig. 5 Contribution of different climate variables to overall committed damages.

a , Climate damages in 2049 when using empirical models that account for all climate variables, changes in annual mean temperature only or changes in both annual mean temperature and one other climate variable (daily temperature variability, total annual precipitation, the number of wet days and extreme daily precipitation, respectively). b , The cumulative marginal effects of an increase in annual mean temperature of 1 °C, at different baseline temperatures, estimated from empirical models including all climate variables or annual mean temperature only. Estimates and uncertainty bars represent the median and 95% confidence intervals obtained from 1,000 block-bootstrap resamples from each of three different empirical models using eight, nine or ten lags of temperature terms.

Extended Data Fig. 6 The difference in committed damages between the upper and lower quartiles of countries when ranked by GDP and cumulative historical emissions.

Quartiles are defined using a population weighting, as are the average committed damages across each quartile group. The violin plots indicate the distribution of differences between quartiles across the two extreme emission scenarios (RCP2.6 and RCP8.5) and the uncertainty sampling procedure outlined in Methods , which accounts for uncertainty arising from the choice of lags in the empirical models, uncertainty in the empirical model parameter estimates, as well as the climate model projections. Bars indicate the median, as well as the 10th and 90th percentiles and upper and lower sixths of the distribution reflecting the very likely and likely ranges following the likelihood classification adopted by the IPCC.

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Kotz, M., Levermann, A. & Wenz, L. The economic commitment of climate change. Nature 628 , 551–557 (2024). https://doi.org/10.1038/s41586-024-07219-0

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Title: ruler: what's the real context size of your long-context language models.

Abstract: The needle-in-a-haystack (NIAH) test, which examines the ability to retrieve a piece of information (the "needle") from long distractor texts (the "haystack"), has been widely adopted to evaluate long-context language models (LMs). However, this simple retrieval-based test is indicative of only a superficial form of long-context understanding. To provide a more comprehensive evaluation of long-context LMs, we create a new synthetic benchmark RULER with flexible configurations for customized sequence length and task complexity. RULER expands upon the vanilla NIAH test to encompass variations with diverse types and quantities of needles. Moreover, RULER introduces new task categories multi-hop tracing and aggregation to test behaviors beyond searching from context. We evaluate ten long-context LMs with 13 representative tasks in RULER. Despite achieving nearly perfect accuracy in the vanilla NIAH test, all models exhibit large performance drops as the context length increases. While these models all claim context sizes of 32K tokens or greater, only four models (GPT-4, Command-R, Yi-34B, and Mixtral) can maintain satisfactory performance at the length of 32K. Our analysis of Yi-34B, which supports context length of 200K, reveals large room for improvement as we increase input length and task complexity. We open source RULER to spur comprehensive evaluation of long-context LMs.

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