Tuukka Kaidesoja

The MAGA schematic narrative template

In a previous post, I discussed the concept of a schematic narrative template coined by psychologist and social anthropologist James V. Wertsch. In this post, I employ this concept to analyze President Donald Trump’s political rhetoric, which relies on the slogan “Make America Great Again”. I claim that when this slogan is embedded in the context of Trump’s political speeches and social media posts, it often includes a narrative for political mobilization (a recent example is his inaugural speech). I also argue that different MAGA narratives that Trump tells different audiences are based on the same schematic narrative template, which I will call “The MAGA template”.

Here is my analysis of the MAGA template:

There was a time when America was great.
America is not great anymore because of P.
If we get rid of P, then America will become great again.
Let’s make America great again by getting rid of P.

The MAGA template can be understood as a flexible and forward-looking narrative schema that Trump and his supporters apply in different contexts to address different audiences. This is because the variable “P” can be anything that the intended audience dislikes, including illegal immigrants, the Biden-Harris administration, the Washington elite, the “deep state”, “woke ideology”, “foreign terrorist organizations”, “Marxist maniacs and lunatics”, DEI programs, the rights of LGTB+ people, non-binary gender categories, environmental legislation, U.S. memberships in international organizations, scientifically-established facts concerning climate change and biodiversity loss, etc. Some of these items (e.g., the “deep state”) are purely fictional constructs, while others include groups of people, institutions, ideas, and facts.

“We,” in turn, is a fiction that includes both “ordinary Americans” and “the Great MAGA Leader”, who allegedly is on their side. “Us” is typically contrasted with “Them”, which can encompass different groups and social categories depending on the situation in which the story is told and the intended audience.

The time when America supposedly was great can refer to a mythical past that never existed, or it can be specified differently for various audiences and purposes. For example, depending on the audience and the issue addressed, the period of America’s greatness might alternatively be the 1950s, the 1800s, the period of colonization of America, or Trump’s previous presidency.

What is interesting is that the MAGA narrative template is similar to the “Expulsion of Alien Enemies” template (or “the triumph-over-alien-forces” template as it was called in Wertsch’s early work) which, according to Wertsch (2008; 2021), has underlie the official historical narratives in Russia for many decades.

As I show in my previous post, it was also employed by President Vladimir Putin to legitimize Russia’s illegal and brutal invasion of Ukraine. Narratives that are based on these two templates have turned out to be immune to critiques that identify falsehoods and factual inaccuracies in them. Nevertheless, when compared to the “Expulsion of Alien Enemies” template, the MAGA narrative template is less militaristic. This is not to say that it cannot be employed for military purposes, as the variable “P” may take the value of the “ownership of a particular area” that currently belongs to a sovereign country. We have already seen this happen.

In my recently published article “Schematic Narrative Templates in National Remembering”, I propose that, for the purposes of cognitive sociological analysis, it is useful to decompose Wertsch’s notion of a schematic narrative template into three interrelated parts: (1) plot structures, (2) narrative schemata, and (3) the practices of narrative production, dissemination, and consumption. One reason for this suggestion is that these three are different entities that need to be analyzed using different types of methods. I suggested that plot structures can be understood as shared patterns of semiotic affordances and constraints for meaning-making in many narrative texts. In contrast, a narrative schema is a dynamic cognitive structure culturally learned by individuals from many written and oral narratives with a similar plot structure.

For example, the above analysis of the MAGA template can be seen as a representation of the plot structure that is shared by many MAGA narratives that, we may hypothesize, are more or less congruent with Trump’s supporters’ narrative schemas they have developed from the repeated MAGA narratives Trump has told in his campaign rallies and in his social media posts. The practices of narrative production, dissemination, and consumption, in turn, are institutionally embedded social processes through which both narrative texts and narrative schemata spread within a specific population. In the case of national historical narratives that serve traditional authoritarian leaders, they may include, for example, state-controlled formal schooling and the production of history textbooks about the nation’s past. Techno-oligarchies may include social media platforms owned and controlled by billionaires whose interests are served by the state administration.

References

Kaidesoja, Tuukka. 2025. Schematic Narrative Templates in National Remembering. Memory Studies.18(1): 44-58 https://journals.sagepub.com/doi/10.1177/17506980241247264

Wertsch, James V. 2002. Voices of Collective Remembering. Cambridge: Cambridge University Press.

Wertsch, James V. 2008. The Narrative Organization of Collective Memory. Ethos, 36(1): 120–135. https://anthrosource.onlinelibrary.wiley.com/doi/abs/10.1111/j.1548-1352.2008.00007.x

Wertsch, James V. 2021. How Nations Remember: A Narrative Approach. Oxford: Oxford University Press.

Schematic Narrative Templates in Collective Remembering: The Case of Russia

James V. Wertsch introduced the concept of schematic narrative template in his book Voices of Collective Remembering published twenty years ago. The book provides a thorough theoretical discussion on collective remembering and an account of the continuities and discontinuities between the Soviet and post-Soviet collective memory in Russia. In this blog post, I focus on Wertsch’s notion of schematic narrative template and his illustrative example of the triumph-over-alien-forces narrative template that he uses to explain continuities in the Russians’ collective memory through the disintegration of the Soviet Union. By utilizing this template, I also analyze and assess the denazification narrative that Vladimir Putin has used in his attempts to legitimate Russia’s brutal invasion of Ukraine.

Collective Memory and Collective Remembering

Collective memory is an ambiguous term that is used in different ways in different disciplines (Hirst & Manier 2008; Olick 1999; Wertsch 2002, chapter 3). I will not attempt to resolve these ambiguities here. Instead, I will rely on Roediger III and Abel’s (2015, 359) characterization of the core meaning of collective memory as “a form of memory that is shared by a group and of central importance to the social identity of the group’s members”. This account distinguishes collective memory from both historical research and idiosyncratic autobiographical memories of individuals.

Wertsch (2002) shares this understanding of collective memory. However, he prefers using the term collective remembering instead of collective memory since he wants to emphasize the dynamical and mediated nature of collective memory. In his view, collective remembering is a process that is distributed across many individuals and their cultural tools. He regards narrative texts about past events as the primary – albeit not the only – cultural tools that mediate collective remembering in literate societies. His book focuses on the processes of production and consumption of narrative texts in modern states by using Russia as an exemplary case.

Schematic Narrative Templates

The notion of schematic narrative template plays an important role in Wertsch’s (2002, 60-62) analysis of how modern states produce official national histories through state-controlled schooling and how these official histories are appropriated by citizens who consume these narratives. He describes schematic narrative templates as generalized forms that include abstract types of settings, actors, and events, and suggests that a specific narrative template may “underlie a range of narratives in cultural tradition” (p. 61) that fill in the template in different ways. The idea then is that narrative templates of this kind mediate collective remembering of past events in specific groups. Wertsch (2002, 62) also uses the term “textual community” to describe “imagined communities” (Anderson 1991), such as nations, that are “grounded in the use of a shared set of texts”. He illustrates the notion schematic narrative template by analyzing the history textbooks used in the secondary schools during the Soviet and post-Soviet periods and interviewing people who have consumed these books during their schooling.

The Triumph-Over-Alien-Forces Narrative Template

According to Wertsch’s (2002) analysis of the Russian case, the schematic narrative template of “the triumph-over-alien-forces” affects Russians’ shared understanding of those past events that are considered important for the national history of the country and the social identity of its citizens. This is his depiction of the basic elements of this template:

Triumph-Over-Alien-Forces:

An “initial situation” in which the Russian people are living in a peaceful setting where they are no threat to others is disturbed by:
The initiation of trouble or aggression by an alien force, or agent, which leads to:
A time of crises and great suffering, which is:
Overcome by the triumph over the alien force by the Russian people, acting heroically and alone (Wertsch 2002, 156; also 93; cf. Wertsch 2022, 461)

The idea is that the nature of the trouble, aggression, alien force, alien agent, crises, and suffering as well as the ways in which Russian people overcome the trouble or aggression caused by the alien forces may take different forms in different narratives about different episodes in the national history of Russia. Despite its flexibility, the template incorporates a strict distinction between peaceful Russian people (“us”) and hostile alien forces or agents (“them”), which is an instance of the “Manichean consciousness” that allows no neutral parties (Wertsch 2002, 95).

Wertsch (2002, chapter 5) provides an analysis of how this narrative template is instantiated in the history textbooks’ accounts of the Civil War of Russia (1917-1923) and World War II (1939-1945) in the Soviet and post-Soviet Russia. He argues that both the Soviet and post-Soviet history textbooks’ narratives about these two episodes are based on the triumph-over-alien-forces template. In these narratives, Russians are depicted as victims of a threat or offensive by some alien forces or agents whose aggressive actions caused a crisis, forcing Russians to heroically defeat them without any help from others. In the case of WWII—usually termed as “the Great Patriotic War” in the textbooks—the alien force was, of course, Nazi Germany which invaded Russia and was, according to the textbook narratives, defeated by the Russian soldiers who fought heroically and without the help of others. The role of other allied countries in fighting against Nazi Germany is systematically downplayed in Russian textbook accounts of WWII. However, Wertsch’s analysis shows that specific actors and events mentioned in the narratives about different episodes are different, and the textbooks used at different times include slightly different narratives about both these episodes, with different points of emphasis and moral interpretations.

Wertsch (2002, chapter 5) also shows that his interviewees largely relied on the triumph-over-alien-forces template when they described these two episodes. However, there were some systematic differences in the agents and events that were named in their narratives and in the evaluations concerning the agents’ actions and particular historical events, depending on whether the interviewee’s schooling occurred during the Soviet era or after that. For example, the Communist Party played an important role in the narratives of WWII by the members of the former group while it was mostly absent from the narratives of WWII by the members of the latter group.

Putin’s Legitimation of Russia’s Invasion of Ukraine

Next, I will briefly address the question of the extent to which the triumph-over-alien-forces template was used in Vladimir Putin’s legitimation Russia’s large-scale invasion of Ukraine in February 2022. It can be expected that Putin is familiar with this template since he went to school in Leningrad (currently known as Saint Petersburg) during the Soviet era when, according to Wertsch (2002), the teaching of the history of Russia largely relied on this template. My analysis is mostly based on Putin’s infamous speech preceding Russia’s invasion of Ukraine (the English translation is available on the Kremlin website).

In Putin’s historical narrative, Ukraine was an organic part of the Russian Empire before the Bolshevik revolution in 1917 after which the Ukrainian Soviet State was artificially created under the leadership of V.I. Lenin in the 1920s. However, since the Soviet Union was centrally ruled, Ukraine remained an integral part of Soviet Russia. According to Putin’s narrative, the crisis period begins with the disintegration of the Soviet Union, after which the Ukrainian people have been gradually suppressed by an allied set of “alien forces” consisting of nationalists, Russophobes, and neo-Nazis. In particular, he claims that these “alien agents” have occupied and corrupted Ukrainian political elite and state leadership with the help of Western countries and started planning all kinds of hostile actions towards Russia, such as preparing Ukraine’s membership application to NATO, planning to manufacture nuclear weapons in Ukraine, and making secret plans to invade Russia. Putin mentions these hostile developments as the main reasons why Russia was forced to start a preventive “special military operation” to “denazify” Ukraine. He has also declared that this operation is aimed to “liberate” the Ukrainian people and bring Ukraine back under Russian control.

It seems to me that the elements (1)-(3) of the triumph-over-alien-forces narrative template can be easily identified in Putin’s historical narrative. In line with this template, Putin probably expected a rapid defeat of Ukraine by the Russian soldiers which he could have presented as a heroic triumph over alien forces. However, Russia’s war against Ukraine cannot be described as a triumph in any sense and the actions of Russian soldiers in Ukraine have not been heroic but brutal and cruel. In addition, there are at least three problems with the denazification narrative if we assess it from the epistemic viewpoint. First, there are few neo-Nazis in Ukraine and the Jewish Ukrainian President Volodomir Zelensky is not definitely one of them. Second, there is no evidence about Ukraine’s plans to invade Russia with the help of their Western allies or plans to manufacture nuclear weapons in Ukraine. Third, as Putin has hopefully realized by now, Ukrainians do not want to be “liberated” by Russians. In other words, Putin’s narrative includes many demonstrably false claims.

However, as state control over media and history teaching at schools has again increased in Putin’s Russia and political opposition has been violently repressed, there seem to be no publicly available counter-narratives to this fictional “denazification narrative” in Russia today. Despite the lack of alternatives, it is hard to say to what extent Russian people believe this narrative because there is no reliable information available for estimating its support. However, Putin’s denazification story, as I tried to show above, relies on a familiar triumph-over-alien-forces narrative template many Russians seem to have internalized from their history textbooks and media representations. Likewise, It is possible that Putin, who, according to some media reports, has quite efficiently isolated himself from reliable sources of information, has become a victim of his own propaganda and no one in his administration dares to question his increasingly paranoid interpretations of history. If Russia ends up losing this brutal war, then the previous narrative template will hopefully be thoroughly questioned through open public discussion in Russia. However, this is not likely to happen as long as Putin remains in power.

Concluding Remarks

Wertsch’s notion of schematic narrative template is a promising conceptual tool for analyzing collective remembering in modern societies. It also bears an interesting resemblance to Claudia Strauss and Naomi Quinn’s (1997) notion of cultural schema that has been influential in the so-called interdisciplinary tradition of cognitive sociology (e.g., Kaidesoja et al., 2022). Hence, it may be an intriguing project to compare these two concepts in detail since it seems to me that cognitive sociologists’ recent specifications of the notion of cultural schema (e.g., Boutyline & Soter, 2021; Hunzaker & Valentino, 2019; Wood et al., 2018) may help to clarify the notion of schematic narrative template. In addition, the latter notion raises similar issues regarding the degree of implicitness, internalization, and cultural transmission as the concept of cultural schema. Hence, cognitive sociologists’ recent analyzes of these issues (e.g., Cerulo et al 2021: Lizardo 2017; 2021; 2022) may prove useful in addressing the cognitive and social mechanisms through which schematic narrative templates are internalized by individuals and transmitted between generations.

The concept of affordance could also prove useful for investigating how exactly narrative texts mediate collective remembering in different contexts (see my previous blog post on cognitive artifacts, affordances, and external representations). Wertsch’s (2002, 119-123) distinction between mastery and appropriation of textual means is an interesting one in this respect. Mastery refers here to individuals knowing how to use a specific type of narrative text, such as history textbooks. Mastery of a specific type of text is reflected in one’s “ability to recall them at will and to employ them with facility when speaking” as well as in one’s skills for “reasoning about the actors and motives behind the events discussed” (p. 119). Appropriation in turn refers to the use of a particular narrative text as a resource for building one’s social identity by “making it one’s own” (p. 120). One of Wertsch’s (2002, 120) points in this context is that these two do not go hand in hand since a person may have mastery over history textbooks while resisting them rather than using them as identity resources (and vice versa). The concept of affordance provides an analytical tool for analyzing the possibilities and constraints that a particular text provides for its user with a specific degree of mastery over the text in a specific situation, although it may not help much in investigating the degree to which an individual has appropriated the text. The latter issue seems to be a bigger challenge for cognitively oriented social research.

References

Anderson, B. (1991) Imagined Communities: Reflections on the Origin and Spread of Nationalism. Verso: London.

Boutyline, A., & Soter, L. K. (2021) Cultural Schemas: What They Are, How to Find Them, and What to Do Once You’ve Caught One. American Sociological Review, 86: 728–758. https://doi.org/10.1177/00031224211024525

Cerulo, K., Leschziner V., & Shepherd, H. (2021) Rethinking Culture and Cognition. Annual Review of Sociology, 47: 63–85. https://doi.org/10.1146/annurev-soc-072320-095202

Hirst, W. and Manier, D. (2008) Towards a Psychology of Collective Memory. Memory 16: 183–200. https://doi.org/10.1080/09658210701811912

Hunzaker, M.B. F., & Valentino, L. (2019) Mapping Cultural Schemas: From Theory to Method. American Sociological Review, 84: 950–981. https://doi.org/10.1177/0003122419875638

Kaidesoja, T., Hyyryläinen, M. & Puustinen, R. (2022) Two Traditions of Cognitive Sociology: An Analysis and Assessment of Their Cognitive and Methodological Assumptions. Journal for the Theory of Social Behavior. https://onlinelibrary.wiley.com/doi/10.1111/jtsb.12341

Lizardo, O. (2017) Improving Cultural Analysis: Considering Personal Culture in its Declarative and Nondeclarative Modes. American Sociological Review, 82: 88–115. https://doi.org/10.1177/0003122416675175

Lizardo, O. (2021) Culture, Cognition, and Internalization. Sociological Forum, 36: 1177–1206. https://doi.org/10.1111/socf.12771

Lizardo, O. (2022) What is Implicit Culture? Journal for the Theory of Social Behavior. https://doi.org/10.1111/jtsb.12333

Olick, J. K. (1999) Collective Memory: The Two Cultures. Sociological Theory, 17: 333–348. https://doi.org/10.1111%2F0735-2751.00083

Roediger III, H. L. & Abel, M. (2015) Collective Memory: A New Arena of Cognitive Study. Trends in Cognitive Sciences, 19(7): 359-361. https://doi.org/10.1016/j.tics.2015.04.003

Wertsch, J. V. (2002) Voices of Collective Remembering. Cambridge University Press: Cambridge.

Wertsch, J. V. (2022) The Narrative Tools of National Memory. In H.L. Roediger III & J.V. Wertsch (Eds) National Memories: Constructing Identity in Populist Times. Oxford University Press: Oxford, pp. 454-472.

Wood, M. L., Stoltz, D. S., Van Ness, J., & Taylor, M. A. (2018). Schemas and Frames. Sociological Theory, 36(3), 244-261. https://doi.org/10.1177/0735275118794981

Cognitive Artifacts, Affordances, and External Representations: Implications for Cognitive Sociology

We use all kinds of artifacts in our everyday life to accomplish different types of cognitive tasks. We write scientific articles and blog posts by using word-processing programs. We prepare to-do lists to organize work tasks, and those of us who engage in statistical or computational analysis of data use computer programs to perform complex calculations that would be impossible to perform without them.

In this post, I argue that cognitive sociologists should pay more attention to cognitive artifacts and their affordances since many cognitive processes in our everyday lives cannot be properly understood and explained without taking them into account. I will proceed by first characterizing the concepts of cognitive artifact, affordance, and external representation. Then I will briefly discuss my recent paper which analyzes college and university rankings by utilizing these three concepts and the conceptual theory of metaphor.

Cognitive Artifacts

Donald Norman coined the concept of cognitive artifact in the early 1990s. According to his definition, a cognitive artifact is “an artificial device designed to maintain, display, or operate upon information in order to serve a representational function” (Norman 1990: 17). Richard Heersmink (2013) has more recently proposed a taxonomy of cognitive artifacts that includes non-representational cognitive artifacts in addition to representational cognitive artifacts. Here, I will rely on Norman’s definition and focus exclusively on representational cognitive artifacts.

Norman (1990) emphasized that the use of cognitive artifacts changes the nature of the cognitive tasks that a person performs—instead of just amplifying the person’s brain-based cognitive abilities—and, thereby, enhances the overall performance of the integrated system that is composed of the person and her artifact. For example, consider the case of organizing your daily work tasks by means of a to-do list, thereby transforming the cognitive task of remembering and planning your work tasks into the following cognitive tasks:

writing a list of the relevant work tasks that may be ordered according to their relative priority or some other principle
remembering to consult the list during the workday
reading and interpreting the items written on the list one by one.

To-do lists enhance ones’ overall work performance during the workday, for example, by eliminating the moments in which the person thinks about what to do next.

From a cultural-historical and developmental viewpoint, it can also be argued that the uses of cognitive artifacts and technologies have transformed our cognitive lives in profound ways. Norman (1991; 1993) and many others (e.g., Donald 1991; Tomasello 1999) have emphasized that one of the distinctive features of our species is our ability to modify our environments by creating new artifacts, refining the artifacts that our ancestors have invented, and transmitting these artifacts to subsequent generations. Here is a relatively random list of some important types of cognitive artifacts that our species has invented: cave paintings, bookkeeping documents, handwritten texts, maps, calendars, clocks, compasses, printed texts, diagrams, thermometers, physical scale models, computers, computational models, GPS devices, and social media messages.

This list illuminates at least two facts. The first is that cognitive artifacts are not a recent innovation in human history since, for example, the earliest cave paintings date back to over 30 000 years and the earliest writing systems were developed over 5 millennia ago. The second is that most of these artifacts have developed gradually over many generations. Many researchers have also emphasized how new cognitive artifacts, tools, and technologies transform the embodied cognitive processes and capacities of people when they become integral parts of their everyday environments and cultural practices, including those pertaining to cognitive development (e.g., Clark 1997; 2003; Donald 1991; Hutchins 1995; 2008; Malafouris & Renfrew 2010; Menary & Gillett 2022; Kirsh 2010; Vygotsky 1978). Hence, cognitive artifacts and technologies are important for understanding historical and cultural variation in human cognition.

Affordances

The concept of affordance provides a useful tool for analyzing the properties of cognitive artifacts in the contexts where they are used. James J. Gibson (1979) introduced the notion of affordance as a part of his ecological theory of visual perception. Gibson writes that “[t]he affordances of the environment are what it offers the animal, what it provides or furnishes, either for good or ill” (p. 127). Gibson’s theory addressed the question of how living organisms perceive their immediate natural environments and emphasized the action-relatedness of perceptual processes. Norman (1993: 106) extended the concept of affordance to the domain of human-made artifacts and technologies by arguing that “[d]ifferent technologies afford different operations” for their users, thereby making “some things easy to do, others difficult or impossible”. It is important to understand that the affordances of a particular technology or a cognitive artifact not only depend on its intrinsic properties but also on the user’s particular bodily and cognitive features, abilities, and skills. For example, a geographical map provides cognitive affordances for navigation only for those who can read cartographic symbols and compass points. In this sense, affordances are relational.

External Representations

Since cognitive artifacts serve representational functions, the notion of external representation can be used to analyze how the affordances of a cognitive artifact shape how its users process information. According to David Kirsh (2010: 441), external representations that are maintained, displayed, or operated by cognitive artifacts may transform our cognitive capacities in at least seven ways:

They change the cost structure of the inferential landscape; they provide a structure that can serve as a shareable object of thought; they create persistent referents; they facilitate re-representation; they are often a more natural representation of structure than mental representations; they facilitate the computation of more explicit encoding of information; they enable the construction of arbitrarily complex structure; and they lower the cost of controlling thought – they help coordinate thought.

Although not all cognitive artifacts do all these things, Kirsh’s list and his examples clarify that cognitive artifacts are not just external aids to internal cognitive processes. Instead, they tend to alter the cognitive processes of their users by enabling them to outsource cognitive tasks that they would otherwise have to (attempt to) perform internally and, in some cases, enable them to accomplish new cognitive tasks that would be impossible without using the cognitive artifact. In their recent article, Richard Menary and Alexander Gillett (2022) also emphasize that cognitive tools (or cognitive artifacts in my terminology) function as tools for enculturation, thereby transforming the embodied cognitive capacities of their users who participate in culturally specific cognitive practices (see also Hutchins 1995; 2008).

Implications: Explaining the Paradox of University Rankings

In my recent article (Kaidesoja 2022), I used Wendy Nelson Espeland and Michael Sauder’s (e.g., 2016) case study of the U.S. News and World Report (shortly: USN) magazine’s law school ranking as a springboard to develop a theoretical framework for explaining the paradox of university rankings, by which I refer to the process where the impact of global and national university rankings has increased at the same time as a growing number of researchers has documented their methodological flaws and counterproductive consequences for university-based research and education (Kaidesoja 2022: 129-130). One aspect of the theoretical framework was my suggestion that the published league tables of university rankings can be understood as cognitive artifacts that provide specific affordances for their audiences to perform cognitive tasks. For example, the latest USN league table of law schools (see here) provides at least the following affordances to the decision-making of prospective law students who, it is plausible to assume, are all literate and numerate:

Affords them to perceive a hierarchical and transitive order represented by the spatial relations among the names of law schools such that highly ranked law schools are at the top;
Affords them to make unequivocal, quick, and easy comparisons between any two law schools in terms of their rank;
Affords them to coordinate information about the rank, location, tuition, and enrollment for each school;
Affords them to compare the rank of a university to its ranks in the previously published tables;
Affords them to share the ranking results with others (e.g., through social media);
Provides them with a stable object that affords joint attention and references in conversations (either in web-mediated or face-to-face communication) (Kaidesoja 2022: 144–145).

These affordances relate both to the visual features of the league tables and their functional properties as parts of the socially distributed cognitive processes that involve more than one actor. An example of the latter could be a situation where a prospective student justifies her decision to apply to Yale University to her parents by showing them that it is the best law school in the league table.

However, my argument was not that the USN ranking of law schools is the only factor that affects the decision-making of prospective students, since it is obvious that other things also influence this process, such as law schools’ distance to home, the financial resources of their parents, their career plans, and their own LSAT scores. Despite this, there is evidence that the USN ranking of law schools is an important factor that influences how many prospective students end up with their choices between law schools (see Espeland & Sauder 2016: chapter 3). It seemed to me that one reason for this is that the published league tables afford such perceptions, comparisons, and communications to prospective students that would be difficult or impossible without the league table. Hence, I hypothesized that the affordances of these cognitive artifacts are part of the explanation of why and how many prospective law students use the USN league tables to outsource part of their decision-making to the USN rankings.

I also argued that we must consider the embodied cognitive processes of prospective law students through which they interpret the ranking results since these processes motivate them to integrate the USN rankings as a part of their decision-making. By relying on Lakoff and Johnson’s (e.g., 2003) conceptual theory of metaphor, I proposed that prospective law students use the league tables of team sports as a source system for a metaphorical analogy guiding their understanding of the law schools rankings (that are also published in the league table format by the USN). My hypothesis was that the league table metaphor of this kind leads many prospective students to assume that – just like the competition between teams in a sports league – the competition between law schools for ranking scores is a zero-sum game, in which excellent quality is a scarce resource, and in which the quality is objectively measured by the ranking scores that determine the law school’s ranking position (Kaidesoja 2022, 141–142). Although these assumptions provide prospective students a way of making sense of the ranking results, they are quite problematic given the methodological problems and biases that are involved in the USN rankings, such as the fact that they overlook contextual differences between law schools, overemphasize competitive relations between law schools, and include arbitrary value judgments concerning the quality of law education (Espeland & Sauder 2016: chapter 1; Kaidesoja 2022: 143).

Moving Forward

In a recent paper on two traditions of cognitive sociology co-authored with Mikko Hyyryläinen and Ronny Puustinen (2021), we argued, among other things, that interdisciplinary cognitive sociologists, who emphasize the importance of integrating cognitive scientific perspectives to cultural sociology, have not yet systematically addressed cognitive artifacts and their affordances. Rather, most of them have focused on how culture influences the intracranial cognition of individuals. Without denying the importance of this project, we argued that there are good reasons to also consider the extracranial elements of cognitive mechanisms and begin to develop new theoretical and methodological approaches for studying the role of cognitive artifacts and technologies in social actions and cognitive development (cf. Norton 2020; Lizardo 2022; Turner 2018). I hope that my paper on university rankings provides some ideas about how one could develop mechanistic explanations that include both extracranial and intracranial cognitive elements.

References

Clark, A. (1997). Being There: Putting Brain, Body, and World Together Again. MIT Press.

Clark, A. (2003) Natural-Born Cyborgs: Minds, Technologies, and the Future of Intelligence. Oxford University Press.

Donald, M. (1991). Origins of the Modern Mind: Three Stages in the Evolution of Culture and Cognition. Harvard University Press.

Espeland, W.N. & Sauder M. (2016) Engines of Anxiety: Academic Rankings, Reputation, and Accountability. Russell Sage Foundation.

Gibson, J.J. (1979) The Ecological Approach to Visual Perception. Houghton Mifflin Harcourt.

Heersmink, R. (2013). A Taxonomy of Cognitive Artifacts: Function, Information, and Categories. Review of Philosophy and Psychology, 4(3), 465–481. https://link.springer.com/article/10.1007/s13164-013-0148-1

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Hutchins, E. (2008) The Role of Cultural Practices in the Emergence of Modern Human Intelligence. Philosophical Transactions of the Royal Society B: Biological Sciences 363 (1499): 2011–2019.

Kaidesoja, T. (2022) A Theoretical Framework for Explaining the Paradox of University Rankings. Social Science Information. 61(1) 128–153. https://journals.sagepub.com/doi/full/10.1177/05390184221079470

Kaidesoja, T., Hyyryläinen, M. & Puustinen, R. (2021) Two Traditions of Cognitive Sociology: An Analysis and Assessment of Their Cognitive and Methodological Assumptions. Journal for the Theory of Social Behavior. https://onlinelibrary.wiley.com/doi/full/10.1111/jtsb.12341

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Norton, M. (2020). Cultural Sociology Meets the Cognitive Wild: Advantages of the Distributed Cognition Framework for Analyzing the Intersection of Culture and Cognition. American Journal of Cultural Sociology, 8, 45–62. https://doi.org/10.1057/s41290-019-00075-w

Tomasello, M. (1999). The Cultural Origins of Human Cognition. London: Harvard University Press.

Turner, S. P. (2018). Cognitive Science and the Social. Routledge.

Vygotsky, L. S. (1978). Mind in Society: The Development of Higher Psychological Processes. Harvard University Press.

Explaining social phenomena by multilevel mechanisms

Four questions about multilevel mechanisms

In our previous post, we discussed mechanistic philosophy of science and its contribution to the cognitive social sciences. In this blog post, we will discuss three case studies of research programs at the interface of the cognitive sciences and the social sciences. In our cases, we apply mechanistic philosophy of science to make sense of the epistemological, ontological, and methodological aspects of the cognitive social sciences. Our case studies deal with the phenomena of social coordination, transactive memory, and ethnicity.

In our work, we have drawn on Stuart Glennan’s minimal account of mechanisms, according to which a mechanism for a phenomenon “consists of entities (or parts) whose activities and interactions are organized so as to be responsible for the phenomenon” (Glennan 2017: 17). We understand entities and activities liberally so as to accommodate the highly diverse sets of entities that are studied in the cognitive social sciences, from physically grounded mental representations to material artifacts and entire social systems. In our article, we make use of the following four questions drawn from William Bechtel’s (2009) work to assess the adequacy and comprehensiveness of mechanistic explanations:

What is the phenomenon to be explained (‘looking at’)?
What are the relevant entities and their activities (‘looking down’)?
What are the organization and interactions of these entities and activities through which they contribute to the phenomenon (‘looking around’)?
What is the environment in which the mechanism is situated, and how does it affect its functioning (‘looking up’)?

The visual metaphors of looking at the phenomenon to be explained, looking down at the entities and activities that underlie the phenomenon, looking around at the ways in which these entities and activities are organized, and looking up at the environment in which the mechanism operates, are intended to emphasize that mechanistic explanations are not strongly reductive or “bottom-up” explanations. Rather, multilevel mechanistic explanations can bring together more “bottom-up” perspectives from the cognitive sciences with more “top-down” perspectives from the social sciences in order to provide integrated explanations of complex social phenomena. In the following, we will illustrate how we have used mechanistic philosophy of science in our case studies and what we have learned from them.

Social Coordination

Interpersonal social coordination has been studied during recent decades in many different scientific disciplines, from developmental psychology (e.g., Carpenter&Svetlova 2016) to evolutionary anthropology (e.g., Tomasello et al. 2005) and cognitive science (e.g., Knoblich et al. 2011). However, despite their shared interests, there has so far been relatively limited interaction between different disciplinary research programs studying social coordination. In this case study, we argued that mechanistic philosophy of science can ground a feasible division of labor between researchers in different scientific disciplines studying social coordination.

In evolutionary anthropology and developmental psychology, one of the most important ideas that has gained considerable empirical support during recent decades is that human agents and our nearest primate relatives differ fundamentally in our dispositions to social coordination and cooperation: for example, chimpanzees rarely act together instrumentally in natural settings, and they are not motivated to engage in the types of social games and joint attention that human infants find intrinsically rewarding already at an early age (Warneken et al. 2006). Importantly, this does not seem to be due to a deficit in general intelligence since chimpanzees score as well as young human infants on tests of quantitative, spatial, and causal cognition (Herrmann et al. 2007). According to the shared intentionality -hypothesis of evolutionary anthropologist Michael Tomasello, this is because “human beings, and only human beings, are biologically adapted for participating in collaborative activities involving shared goals and socially coordinated action plans (joint intentions)” (Tomasello et al. 2005).

Given a basic capacity to engage in social coordination, one can raise the question of what types of cognitive mechanisms enable individuals to share mental states and act together with other individuals. To answer this question, we made use of the distinction between emergent and planned forms of coordination put forth by cognitive scientist Günther Knoblich and his collaborators. According to Knoblich et al. (2011: 62), in emergent coordination, “coordinated behavior occurs due to perception-action couplings that make multiple individuals act in similar ways… independent of any joint plans or common knowledge”. In planned coordination, ”agents’ behavior is driven by representations that specify the desired outcomes of joint action and the agent’s own part in achieving these outcomes.” Knoblich et al. (2011) discuss four different mechanisms for emergent coordination: entrainment, common object affordances, action simulation, and perception-action matching. While emergent coordination is explained primarily by sub-intentional mechanisms of action control (which space does not allow us to discuss in more detail here), planned coordination is explained by reference to explicit mental representations of a common goal, the other individuals in joint action, and/or the division of tasks between the participants.

In our article, we argued that cognitive scientists and social scientists answer different questions (see above) about mechanisms that bring about and sustain social coordination in different environments and over time. Thus they are in a position to make mutually interlocking yet irreducible contributions to a unified mechanistic theory of social coordination, although they may also sometimes reach results that challenge assumptions that are deeply ingrained in the other group of disciplines. For a more detailed discussion of how cognitive and social scientists can collaborate in explaining social coordination, we refer the reader to our article (Sarkia et al. 2020: 8-11).

Transactive Memory

Our second case study concerned the phenomenon of transactive memory, which has been studied in the fields of cognitive, organizational, and social psychology as well as in communication studies, information science, and management. The social psychologist Daniel Wegner and his colleagues (Wegner et al. 1985: 256) define transactive memory in terms of the following two components:

An organized store of knowledge that is contained entirely in the individual memory systems of the group members
A set of knowledge-relevant transactive processes that occur among group members.

They attribute transactive memory systems to organized groups insofar as these groups perform functionally equivalent roles in group-level information processing as individual memory mechanisms perform in individual cognition, i.e. (transactive) encoding, (transactive) storing, and (transactive) retrieving of information. For example, Wegner et al. (1985) found that close romantic couples responded to factual and opinion questions by using integrative strategies, such as interactive cueing in memory retrieval. Subsequent research on transactive memory systems has addressed small interaction groups, work teams, and organizations in addition to intimate couples (e.g., Ren & Argote 2011; Peltokorpi 2008). What is crucial for the development of a transactive memory system is that the group members have at least partially different domains of expertise and that the group members have learned about each other’s domains of expertise. If these two conditions are met, each group member can utilize the other group members’ domain-specific information in group-related cognitive tasks and transcend the limitations of their own internal memories.

In our article, we made use of the theory of transactive memory systems to argue that some cognitive mechanisms transcend the brains and bodies of individuals to the social and material environments that they inhabit. For example, in addition to brain-based memories, individual group members may also utilize material artifacts, such as notebooks, archives, and data files, as their memory stores. In addition, other members’ internal and external memory storages may in an extended sense be understood as part of the focal member’s external memory storages as long as she knows their domains of expertise and can communicate with them. Thus the theory of transactive memory can be understood as describing a socially distributed and extended cognitive system that goes beyond intra-cranial cognition (Hutchins 1995; Sutton et al. 2010). For a more detailed discussion of this thesis and its implications for interdisciplinary memory studies, we refer the reader to our article (Sarkia et al. 2011, 11-15).

Ethnicity

The sociologist Rogers Brubaker and his collaborators (Brubaker et al. 2004) has made use of theories in cognitive psychology and anthropology to challenge traditional approaches to ethnicity, nationhood, and race that view them as substantial groups or entities with clear boundaries, interests, and agency. Rather, he treats them as different ways of seeing the world, based on universal cognitive mechanisms, such as categorizing the world into ‘us’ and ‘them.’ Brubaker et al. (2004) also make use of the notions of cognitive schema and stereotype, defining stereotypes as “cognitive structures that contain knowledge, beliefs, and expectations about social groups” and schemas as “representations of knowledge and information-processing mechanisms” (DiMaggio 1997). For example, Brubaker et al. (2004, 44) discuss the process of ethnicization, where ”ethnic schemas become hyper-accessible and… crowd out other interpretive schemas.”

In our article, we made use of Brubaker’s approach to ethnicity to illustrate how cognitive accounts of social phenomena need to be supplemented by traditional social scientific research methods, such as ethnographic and survey methods when we seek to understand the broader social and cultural environment in which cognitive mechanisms operate. For example, in their case study of Cluj, a Romanian town with a significant Hungarian minority, Brubaker et al. (2006) found that while public discourse was filled with ethnic rhetoric, ethnic tension was surprisingly scarce in everyday life. By collecting data with interviews, participant observation, and group discussions, they were able to identify cues in various situations that turned a unique person into a representative of an ethnic group. Importantly, this result could not be achieved simply by studying the universal cognitive mechanisms of stereotypes, schemas, and categorization, since these mechanisms serve merely as the vehicles of ethnic representations, and they do not teach us about the culture-specific contents that these vehicles carry. We refer the reader to our article for more discussion of the complementarity of social scientific and cognitive approaches to ethnicity (Sarkia et al. 2020, 15-17).

References

Bechtel W (2009) “Looking down, around, and up: mechanistic explanation in psychology.” Philosophical Psychology 22(5): 543–564.

Brubaker R, Loveman M and Stamatov P (2004) “Ethnicity as cognition.” Theory and Society 33(1): 31–64.

Brubaker R, Feischmidt M, Fox J, Grancea L (2006) Nationalist Politics and Everyday Ethnicity in a Transylvanian Town. Princeton: Princeton University Press.

Carpenter M, Svetlova M (2016) “Social development.” In: Hopkins B, Geangu E, Linkenauer S (eds) Cambridge Encyclopedia of Child Development. Cambridge: Cambridge University Press, 415–423.

DiMaggio P (1997) “Culture and cognition.” Annual Review of Sociology 23: 263-287.

Herrmann E, Call J, Hernandez-Loreda, M, Hare B, and Tomasello, M (2007). “Humans have evolved specialized skills of social cognition: the cultural intelligence hypothesis.” Science 317: 1360-1366.

Hutchins E (1995) Cognition in the wild. Cambridge (MA): MIT Press.

Peltokorpi V (2008). Transactive memory systems. Review of General Psychology 12(4): 378–394.

Ren Y and Argote L (2011) “Transactive memory systems 1985–2010: An integrative framework of key dimensions, antecedents, and consequences.” The Academy of Management Annals 5(1): 189–229.

Sarkia M, Kaidesoja T, and Hyyryläinen (2020). “Mechanistic explanations in the cognitive social sciences: lessons from three case studies.” Social Science Information. Online first (open access). https://doi.org/10.1177%2F0539018420968742

Sutton J, Harris C.B., Keil P.G. and Barnier A.J. 2010. “The psychology of memory, extended cognition and socially distributed remembering.” Phenomenology and the Cognitive Sciences 9(4), pp. 521-560.

Tomasello M, Carpenter M, Call J, et al. (2005) “Understanding and sharing intentions: The origins of cultural cognition.” Behavioral and Brain Sciences 28: 675–691.

Warneken F, Chen F, Tomasello M (2006) “Cooperative activities in young children and chimpanzees.” Child Development 77(3): 640–663.

Wegner DM, Giuliano T and Hertel P (1985) “Cognitive interdependence in close relationships.” In: Ickes WJ (ed) Compatible and Incompatible Relationships. New York: Springer, pp. 253–276.

Causal mechanisms in the cognitive social sciences

The social sciences and the cognitive sciences have grown closer together during recent decades. This is manifested in the emergence and expansion of new research fields, such as social cognitive neuroscience (Cacioppo et al. 2012; Lieberman 2017), cognitive sociology (Brekhus & Ignatow 2019), behavioral economics (Dhami 2016), and new approaches in cognitive anthropology (Bloch 2012; Hutchins 1995; Sperber 1996). However, increasing interactions between the cognitive and social sciences also raise many pressing philosophical and methodological issues about interdisciplinary integration and division of labor between disciplines. In our recent article (Sarkia, Kaidesoja & Hyyryläinen 2020), we argue that mechanistic philosophy of science can contribute to analyzing these challenges and responding to them.

According to mechanistic philosophy of science (hereafter: MPS), the primary way in which scientists explain complex cognitive and social phenomena is by describing causal mechanisms that produce, underlie, or maintain these phenomena (e.g. Bechtel 2008; Glennan 2017; Hedström & Ylikoski 2010). Commonly cited examples of semi-general social mechanisms include those that generate self-fulfilling prophecies, cumulative advantage, residential segregation, collective action, and diffusion patterns in social networks. Cognitive and neural mechanisms addressed in the cognitive sciences include those underlying perceptual processes, memory functions, learning, imagination, and social cognition.

In this post, we take a closer look at causal mechanisms and mechanistic explanations. We also indicate some ways in which MPS could help to bridge the gap between the social and the cognitive sciences. The text partially draws on our article that provides a more detailed account of mechanistic explanations in the cognitive social sciences (Sarkia, Kaidesoja & Hyyryläinen 2020: 3-8).

Mechanisms

A ‘minimal’ account of mechanisms says that a mechanism for a phenomenon “consists of entities (or parts) whose activities and interactions are organized so as to be responsible for the phenomenon” (Glennan 2017: 17). Entities are particular things (in a broad sense) in the world and activities always take place in some entity. The entities that are studied in different sciences are highly diverse, ranging from molecules to brains and complex social systems. Entities may engage in activities either by themselves or in concert with other entities. When the activities of two or more entities influence each other, they interact. In a mechanism that is responsible for some phenomenon, its constituent entities and activities, as well as their interactions, are organized in a way that allows them to produce, maintain or underlie the phenomenon, meaning that there are specific constitutive and causal relations between these constituent entities and activities. This minimal account of mechanisms makes clear that mechanisms are different from universal laws, correlations between variables (or other empirical regularities), and functions that items may perform in some larger system. Advocates of MPS have also provided accounts of mechanisms that are more specific, but most of them are compatible with the minimal account (e.g. Glennan & Illari 2018).

MPS regards mechanisms as hierarchical in the sense that lower-level mechanisms operate as parts of higher-level mechanisms (e.g. Craver & Darden 2013; Glennan 2017). When scientists investigate a mechanism that is responsible for a specific phenomenon, they commonly assume that there are underlying mechanisms that allow the constituent entities of the mechanism to engage in the activities that they engage in. Conversely, a mechanism identified at a lower level of mechanistic organization is typically embedded in some broader (or higher-level) mechanism that affects its functioning. For example, a mechanism underlying the working memory of a particular person may operate as a part of the social mechanism of collaborative learning in which the person is engaged in a common learning task with her classmates. Social and cognitive scientists often implicitly or explicitly attribute different types of cognitive capacities to people, such as the capacities to act intentionally, to communicate using spoken or written language, and to remember things from the past. As Stuart Glennan (2017: 51–52) argues, the capacities of complex entities are mechanism-dependent in the sense that the organized interactions of their parts are responsible for the capacities of the whole entity, which may manifest themselves only in suitable environments. For example, the capacity for speech is dependent on the organized interactions of neural mechanisms and manifested in embodied communicative interactions with other people.

According to MPS, mechanisms are identified on the basis of the phenomena that they contribute to (e.g. Craver & Darden 2013; Hedström & Ylikoski 2010; Glennan 2017). For example, cognitive neuroscientists investigate the neural mechanisms underlying working memory and visual perception (Bechtel, 2008), while social scientists study the social mechanisms of self-fulfilling prophecy and urban segregation (Hedström, 2005). They both use empirically established phenomena to delimit the boundaries of the mechanism under investigation and to identify the entities and activities that are relevant for explaining the phenomenon in question.

When they study highly complex systems, such as biological organisms or social groups, scientists may also get different mechanistic decompositions of the same system when they focus on different phenomena in the system (Glennan 2017: 37–38). But once they have identified a phenomenon in a system, the boundaries of the mechanism that is responsible for it are determinate and do not depend on the ways the mechanism is represented. An important implication of this is that mechanistic levels are always relative to some phenomenon of interest, meaning that there are no global levels of mechanisms. From this, it follows that cognitive social scientists should be cautious regarding the methodological value of highly abstract mechanism types, such as ‘biological mechanism’, ‘psychological mechanism’ and ‘social mechanism’ since they tend to refer to heterogeneous arrays of mechanisms rather than to fixed ‘ontological levels of reality’.

Mechanistic Explanations

While mechanisms are always particular and spatiotemporally local, cognitive and social scientists are interested in making generalizations about them and classifying them into kinds. According to MPS, scientists achieve generality by constructing models about classes of particular mechanisms. In scientific practice, mechanistic models may take many different forms, such as qualitative descriptions, diagrams, equations, or computational simulations. What they share in common is that they can be used to ‘describe (in some degree and some respect) the [target] mechanism that is responsible for some phenomenon’ (Glennan 2017: 66). An important way to construct general models is by abstracting away from the details of particular mechanisms and idealizing some of their features. For example, many models of social mechanisms not only abstract away from most neural and cognitive mechanisms that underlie the interactions of individual actors but may also include idealized descriptions of the cognitive capacities of actual human beings (cf. Hedström, 2005; Hedström & Ylikoski 2010). Abstractions omit details regarding the target mechanism while idealizations distort some features of the target mechanism (Craver & Darden 2013: 33–34, 94; Glennan 2017: 73–74). There is no general criterion regarding the acceptability of abstractions and idealizations in a mechanistic model – rather, the appropriateness of particular abstractions and idealizations should be decided in a case-by-case manner depending on the epistemic aims of the researcher (Craver & Kaplan 2018; Glennan 2017).

In MPS, scientific explanations are understood in terms of mechanistic models that scientists use –in combination with other relevant explanatory factors – to represent those mechanisms that underlie, maintain or produce the phenomenon that they aim to explain (e.g. Bechtel 2008; Craver & Darden 2013; Glennan 2017). Mechanistic explanations may unify phenomena that were earlier regarded as unconnected by revealing that their underlying mechanisms are similar. Mechanistic explanations may also split phenomena that were earlier regarded as similar by revealing that their underlying mechanisms are different.

In the context of the cognitive social sciences, some researchers have recognized the identification of cognitive mechanisms underlying social phenomena as a central argument for the cognitive social sciences (e.g. Sun 2017; Thagard 2019), while others have argued in favor of greater unification (e.g. Gintis 2007), complementarity (e.g. Zerubavel 1997) or mutual constraints (e.g. Bloch 2012) between the cognitive and social sciences without appeal to mechanistic philosophy of science. We have discussed different arguments for the cognitive social sciences in more detail in an earlier article (Kaidesoja et al. 2019) and a blog post that was based on it. However, when evaluating mechanistic explanations for social phenomena, it is important to recognize that such explanations do not reduce the phenomena to be explained to some lower level. Rather, they help us to understand how the phenomena to be explained arise from the organized interactions of its constituent entities and activities in a specific environment. This means that mechanistic explanations often cite mechanisms at many different levels in a local mechanistic hierarchy.

Some critics of MPS have claimed that advocates of this view assume that more detailed mechanistic explanations are always better (e.g. Batterman & Rice 2014), although the latter have explicitly distanced their views from this idea (e.g. Glennan 2017; Craver & Kaplan 2018). Even if it is clear that a mechanistic explanation should describe some entities and activities that contribute to the phenomenon to be explained, mechanistic explanations may vary with respect to their completeness, and the epistemic purposes of researchers should be taken into account when assessing the relevance of adding more detail to a mechanistic model. Accordingly, in their well-known article on causal mechanisms in the social sciences, Peter Hedström and Petri Ylikoski (2010: 60) conclude that ‘only those aspects of cognition that are relevant for the explanatory task at hand should be included in the explanation, and the explanatory task thus determines how rich the psychological assumptions must be’. Cognitive explanations of social phenomena may accordingly involve various degrees of realism and complexity, and more detailed multi-level explanations are not automatically more satisfactory than explanations that focus on a more straightforward or selective subset of causes.

Conclusion

This brief account of causal mechanisms and mechanistic explanations already provides some ideas on how to integrate the social sciences with the cognitive sciences. In the simplest case, mechanisms studied in the cognitive and social sciences can be organized in a hierarchical manner such that cognitive scientists model those cognitive and neural mechanisms that directly underlie those cognitive capacities and activities of social actors that are assumed in social scientists’ models about social mechanisms. However, few mechanistic models in the cognitive and social sciences can be organized into vertical relations of this kind. It is often the case, for example, that cognitive scientific and social scientific models address partially overlapping phenomena in different spatiotemporal scales by using different conceptual frameworks and research methods (e.g. Bloch 2012; Lizardo et al 2020; Turner 2018). This means that there are still significant conceptual gaps and methodological discrepancies that cognitive social scientists need to address in their explanatory practices. In our paper, we used MPS to address some of these difficulties and applied it in three case studies about the cognitive social sciences. In a follow-up post, we discuss our case studies and their lessons.

References

Batterman, RW, and Rice C (2014) “Minimal model explanations.” Philosophy of Science 81(3): 349–76.

Bechtel W (2008) Mental Mechanisms: Philosophical Perspectives on Cognitive Neuroscience. Routledge: London.

Bloch M (2012) Anthropology and the Cognitive Challenge. Cambridge: Cambridge University Press.

Brekhus W and Ignatow G (eds) (2019) Oxford Handbook of Cognitive Sociology. Oxford: Oxford University Press.

Cacioppo J, Berntson G and Decety J (2012) “A history of social neuroscience.” In: Kruglanski A and Stroebe W (eds) Handbook of the History of Social Psychology. New York: Psychology Press, pp.123-136.

Craver C and Darden L (2013) In Search of Mechanisms: Discoveries Across the Life Sciences. Chicago: University of Chicago Press.

Craver C and Kaplan D (2018) “Are more details better? On the norms of completeness for mechanistic explanations.” The British Journal for the Philosophy of Science, 1(71): 287–319

Dhami S (2016) The Foundations of Behavioral Economic Analysis. Oxford University Press.

Gintis H. (2007) A framework for the unification of the behavioral sciences. Behavioral and Brain Sciences, 30: 1–16.

Glennan S (2017) The New Mechanical Philosophy. Oxford: Oxford University Press.

Glennan S and Illari P (eds) (2018) The Routledge Handbook of Mechanisms and Mechanical Philosophy. London: Routledge.

Hedström, P (2005) Dissecting the Social: On the Principles of Analytical Sociology. Cambridge: Cambridge University Press.

Hedström P and Ylikoski P (2010) “Causal mechanisms in the social sciences.” Annual Reviews in Sociology 39: 46-67.

Hutchins E (1995) Cognition in the wild. Cambridge: MIT Press.

Kaidesoja T, Sarkia M and Hyyryläinen M (2019) “Arguments for the cognitive social sciences.” Journal for the Theory of Social Behavior 49(4):1-16. https://onlinelibrary.wiley.com/doi/abs/10.1111/jtsb.12226

Lieberman M (2017) “Social cognitive neuroscience: A review of core processes.” Annual Review of Psychology 58: 259–289.

Lizardo O, Sepulvado B, Stoltz D and Taylor M (2020) “What can cognitive neuroscience do for cultural sociology.” American Journal of Cultural Sociology 8: 3–28.

Sarkia M, Kaidesoja T and Hyyryläinen M (2020) “Mechanistic explanations in the cognitive social sciences: Lessons from three case studies.” Social Science Information. https://doi.org/10.1177%2F0539018420968742

Sperber D (1996) Explaining Culture: a Naturalistic Approach. Oxford: Blackwell.

Sun R (2012) “Prolegomena to the cognitive social sciences.” In R. Sun (ed) Grounding Social Sciences in Cognitive Sciences. Cambridge (MA): MIT Press, pp. 3–32.

Thagard P (2019) Mind-Society: From Brains to Social Sciences and Professions. Oxford: Oxford University Press.

Turner SP (2018) Cognitive Science and the Social. London: Routledge.

Zerubavel, E (1997) Social Mindscapes: An Invitation to Cognitive Sociology. Cambridge, MA: Harvard University Press.

Four arguments for the cognitive social sciences

Despite increasing efforts to integrate ideas, concepts, findings and methods from the cognitive sciences with the social sciences, not all social scientists agree this is a good idea. Some are indifferent to these integrative attempts. Others consider them as overly reductionist and, thereby, as a threat to the identity of their disciplines. As a response to many social scientists’ skepticism towards psychology and cognitive science, cognitive social scientists have provided arguments to convince other social scientists about the benefits of integrating the social sciences with the cognitive sciences. In this blog post, that is based on a recently published article co-authored with Matti Sarkia and Mikko Hyyryläinen (Kaidesoja, Sarkia & Hyyryläinen 2019), I briefly outline and evaluate four arguments for the cognitive social sciences. By cognitive social sciences, I refer to scientific disciplines that aim to integrate the social sciences with the cognitive sciences, including disciplines like cognitive anthropology, cognitive sociology, political psychology, and behavioral economics. By interdisciplinary integration, I mean different ways of bringing disciplines together.

Each argument presupposes a different idea about how the cognitive sciences should be integrated with the social sciences. These arguments can be referred to as explanatory grounding, theoretical unification, constraint and complementarity. Different arguments also subscribe to different visions as to how the cognitive social sciences might look like and make different assumptions about social phenomena and scientific explanations of them. Hence, different arguments provide reasons for engaging in different types of research programs in the cognitive social sciences. For these reasons, it is important not only to reconstruct these four arguments but also to take a closer look at their presuppositions and implications.

I will address each argument in two stages. First, I provide a reconstruction of the argument by specifying its premises, inferential structure and conclusion. Then I briefly evaluate the argument by analyzing some of its presuppositions and the plausibility of its premises. Although I do not claim these four arguments to be the only arguments for the cognitive social sciences, I believe that they are among the most important and influential ones. In addition, while I attribute each argument to a particular author, in the longer piece we also point to other cognitive social scientists who have proposed similar arguments (see Kaidesoja, Sarkia & Hyyryläinen 2019).

Argument from explanatory grounding

Ron Sun (2012) presents the argument from explanatory grounding for the cognitive social sciences. Here is the reconstruction of Sun’s argument that we provided in our paper:

Most social scientists do not currently make use of the knowledge produced in the cognitive sciences when they explain social phenomena.
Cognitive processes are the ontological basis of social processes.
Explanations in the cognitive sciences are deeper than explanations in the social sciences because they bottom out in cognitive processes.
If social scientists ground their explanations in the cognitive sciences, their explanations for social phenomena would become deeper than they are at present.
Conclusion: the social sciences should be grounded in the cognitive sciences (Kaidesoja, Sarkia & Hyyryläinen 2019, 3).

It is important to recognize that Sun’s argument presupposes that the explanatory grounding relation between the cognitive and social sciences is asymmetrical. This means that if the social sciences are grounded in the cognitive sciences, then the cognitive sciences cannot be grounded in the social sciences.

Sun’s key premises 2 and 3 rest on the requirement that scientific explanations should reflect the ontological order of reality. This means that higher-level processes should be explained by the models that represent their lower-level component processes that form the ontological basis of the higher-level processes. Since Sun (2012) assumes that cognitive sciences study cognitive processes that are ontologically more fundamental than social processes studied in the social sciences, he expects that the cognitive sciences are capable of providing deeper explanations for social processes than those currently provided in the social sciences. He does not claim, however, that these cognitive explanations would explain social processes away (e.g. by means of ontologically reducing them to cognitive processes or eliminating them from scientific ontology). In other words, the idea of explanatory grounding of the social sciences in the cognitive sciences is compatible with the assumption that social processes have weakly emergent properties that can be mechanistically explained (e.g. Kaidesoja 2013).

Although it does not reduce social phenomena to cognitive phenomena, the idea of asymmetrical explanatory grounding may pose unnecessary constraints for the development of the cognitive sciences. There is no good a priori reasons to exclude the possibility that the social sciences might have something useful to offer to those parts of the cognitive sciences that address the cognitive aspects of social phenomena. For example, social scientists may indicate that some cognitive mechanisms have social aspects that have been ignored by cognitive scientists. In addition, while Sun (2012) tends to assume that the explanatory grounding of the social sciences in the cognitive sciences should be based on a cognitive architecture that provides a unified theory of the mind, such as his own CLARION architecture, this assumption can be challenged on three grounds. First, many competing cognitive architectures exist and it is not clear which one should be chosen for the purposes of explanatory grounding. Second, mechanistic approach to explanation is perfectly compatible with the idea of local (or phenomenon-specific) explanatory grounding that may proceed without a unified theory of mind. Third, at least arguably, local attempts at explanatory grounding have turned out to be more fruitful than global attempts that rely on unified cognitive architectures.

For these and some other reasons we discuss in the article, it seems that the local version of the explanatory grounding argument is more promising than the global one. The local explanatory grounding arguments are presented in the context of explanatory research on particular social phenomena, such as transactive memory, collaborative learning or moral judgements. In addition, at least some social phenomena may be grounded in cognitive mechanisms understood in an externalist way, meaning that these cognitive mechanisms include important technological, social and/or cultural aspects in addition to brain-bound aspects (see Miłkowski et al., 2018). Cognitive mechanisms of this kind have been theorized and studied in the so called 4E (i.e. embodied, embedded, enactive and extended) approaches to cognition as well as in distributed and situated cognition approaches.

Argument from theoretical unification

Herbert Gintis (e.g. 2007a, 2009, 2012) has developed an argument for a unified and cognitively informed behavioral science. We reconstruct Gintis’s argument as follows:

Scientific disciplines that study the same domain of phenomena should be conceptually and theoretically unified with one another.
The behavioral sciences all study the same domain of phenomena, which have to do with the decision-making and strategic interaction.
Hence, the behavioral sciences ought to be unified with one another.
Conclusion: Unification of the behavioral sciences requires a unified framework for modeling decision-making and strategic interaction in a way that takes into account the contributions of different behavioral sciences (Kaidesoja, Sarkia & Hyyryläinen 2019, 6).

Although theoretical unification surely is one of the epistemic criteria used in scientific evaluation, the problem with Gintis argument is that it fails to notice that it is not the only one nor even the most important one. Indeed, many philosophers of science and social epistemologists have argued that a diversity of perspectives on the world is essential for scientific progress both in the natural sciences and in the social sciences (e.g. Longino, 1990; Weisberg & Muldoon, 2009). This means that the requirement for theoretical unification becomes problematic if it is used to suppress other research programs in the cognitive social sciences. The argument from theoretical unification largely ignores these points.

In addition, it is not at all clear whether Gintis (2007a; 2009; 2012) succeeds in integrating the social sciences with the cognitive sciences in an adequate way. He builds his unifying theoretical framework by combining the slightly revised rational actor model and game theory − both originally developed in neo-classical economics − with the relatively speculative use of some evolutionary principles. One reason to doubt the feasibility of this framework is to note many cognitive scientists and behavioral economists have forcefully criticized the axioms of rational choice theory. Although Gintis (e.g. 2007b) admits this and responds to these critiques, we argued in the paper that his way of dealing with them is highly selective and question begging (Kaidesoja, Sarkia & Hyyryläinen 2019, 7). Moreover, if only those parts of the social sciences studying decision-making and strategic interaction are included in “the unified behavioral science”, then large chunks of the social sciences are excluded from it. This is problematic insofar as one wants to develop an argument for the cognitive social sciences that would encompass research programs on all kinds of social phenomena. In addition, Gintis’ argument from theoretical unification is likely to raise the specter of economics imperialism among social scientists, due to the central role that the rational actor model plays in his unified modeling framework and his principles for unifying the behavioral sciences.

Argument from constraints

Maurice Bloch’s (2012) argument for the cognitive social sciences highlights limitations in social scientists’ and their research subjects’ understanding of how their minds operate. This is how we reconstructed Bloch’s argument form constraints:

Since all social processes involve cognitive aspects, social scientists must make assumptions about human cognition in their research practices.
Social scientists’ assumptions about the cognitive processes of their research subjects are often based on the subjects’ own accounts of these processes and/or the ideas and concepts of “folk psychology” that people use in their everyday life.
Cognitive scientific studies have convincingly demonstrated that our cognitive processes are not transparent to us and that our own understanding of these processes, including social scientists’ and their research subjects’ “folk psychological theories”, is limited and sometimes misleading.
Conclusion: social scientists’ assumptions about cognitive processes of their research subjects should be constrained by the results of cognitive sciences (Kaidesoja, Sarkia & Hyyryläinen 2019, 9).

This argument includes much less ontological, methodological and theoretical presuppositions when compared with the two arguments considered above. For example, instead of celebrating the progress of the cognitive sciences, Bloch (2012, p. 9) holds that “the study of cognition is in its infancy” and that, for this reason, “the cognitive sciences are more certain when telling us what things are not like, than when telling us how things are” (p. 9). Accordingly, the main purpose of his argument is to weed out implausible cognitive assumptions from the social sciences rather than to ground the social sciences in the cognitive sciences or to unify the social sciences with the help of the cognitive sciences.

All of the premises of the above argument seem well justified. Indeed, cognitive scientists have convincingly demonstrated not only that our everyday conceptions about how our minds work are seriously limited and potentially misleading but also that a large part of our action-related cognitive processes are implicit (e.g. Evans & Frankish, 2009; Kahneman, 2012). The conclusion in 4 is also well supported at least to the extent that social scientists studying small-scale social interactions are well-advised to pay attention to the results of cognitive sciences when they make assumptions about the cognitive processes of their research subjects since this enables them to avoid biased explanations.

This does not mean, however, that social scientists should replace their methods with the methods of cognitive sciences, since, as Bloch (2012) rightly argues, ethnographic methods can be used to produce data about social and cultural phenomena that is impossible to obtain by using the experimental and simulation methods of cognitive scientists (see also Hutchins, 1995). What it does mean is that the data social scientists produce by using ethnographic methods should not be interpreted as providing reliable knowledge about the internal cognitive processes of their research subjects and that, for many explanatory purposes, it should be supplemented with data acquired by using other type of methods, including those used in the cognitive sciences.

Nevertheless, the results of cognitive sciences are less significant when it comes to explanatory studies on the outcomes of social interactions of a large number of individuals in a specific institutional context. The reason is that social scientists cannot escape from making trade-offs between the psychological realism and the tractability of their models in this context. The feasibility of their assumptions about cognition should be judged in a case-by-case manner that takes into account the purposes in which they use their models. However, in order to be able make judgements of this kind, social scientists should be aware of the relevant cognitive processes that they abstract from or idealize in their models. To this end, they need cognitive sciences (see Lizardo, 2009).

Argument from complementarity

The argument from complementarity is the oldest one of these four arguments. Eviatar Zerubavel proposed it already in his Social Mindscapes in 1997. We reconstructed Zerubavel’s argument in the paper as follows:

Since cognitive science studies cognitive universals, it cannot answer questions about how cognition varies between groups and how social environments affect cognitive processes.
In order to provide a more comprehensive understanding of human cognition, cognitive science should be complemented with studies that answer questions concerning the domain of sociomental (i.e. cognitive phenomena that vary between groups and cultures but are not entirely idiosyncratic).
Cognitive sociology’s ontological, theoretical and methodological position allows it to answer questions concerning the domain of sociomental.
Conclusion: Cognitive science should be complemented with cognitive sociology (Kaidesoja, Sarkia & Hyyryläinen 2019, 11).

The argument from complementarity is based on a view that different disciplines produce knowledge about human cognition according to their distinct ontological and epistemological commitments that may be incompatible with each other. It suggests that cognitive sociology does not aim to build a bridge between sociology and the cognitive sciences but rather forms an autonomous perspective on the sociomental aspects of human cognition that is meant to complement cognitive science.

This argument assumes a quite narrow and monolithic understanding of cognitive science. Although premise 1 includes a relatively accurate characterization of the state of the cognitive science in 1990s, today it is clearly outdated. The reason is that cognitive science has moved away from a nearly exclusive focus on “the universal foundations of human cognition” (Zerubavel, 1997, p. 3) that are realized in our brains, and included wider perspectives that focus on the embodied, embedded, enactive, extended, situated, distributed and cultural-historical aspects of cognitive processes (e.g. Hutchins, 1995; Clark, 1997; Franks, 2011; Lizardo et al., 2019; Turner, 2018). Although studies on “wide cognition” (Miłkowski et al., 2018) were in their infancy in 1990s, when Zerubavel first developed his argument, it seems that these externalist approaches to human cognition are also ignored in more recent discussions that have been inspired by his work (e.g. Brekhus, 2015). Hence, the argument from complementarity needs to be updated by taking into account recent developments in the cognitive sciences. When this is done, it is not at all clear whether the revised argument provides a distinct argument for the cognitive social sciences.

Another problem with the argument from complementarity concerns the kind of interdisciplinarity it would produce in practice. Omar Lizardo (2014), for example, argues that the sociology of culture and cognition, often used as a synonym for Zerubavellian cognitive sociology, creates “a sense of pseudo-interdisciplinarity”. This means that, although the name suggests at least some degree of interdisciplinary interaction, the actual communication between these disciplines has been almost nonexistent in this tradition. All attempts to create complementary perspectives to cognitive science run the risk of pseudo-interdisciplinarity of this kind. Hence, although interdisciplinary integration is regarded as an ultimate goal of the multilevel approach to cognition in some of Zerubavel’s (e.g. 1997, p. 113) claims, the argument from complementary may actually lead away from this goal.

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