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:

  1. writing a list of the relevant work tasks that may be ordered according to their relative priority or some other principle
  2. remembering to consult the list during the workday
  3. 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

Hutchins, E. (1995) Cognition in the Wild. The MIT Press.

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

Kirsh, D. (2010) Thinking with External Representations. AI & Society 25: 441–454.

Lakoff, G. & Johnson, M. (2003) Metaphors We Live by (With a New Afterword). The University of Chicago Press.

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

Malafouris, L., & Renfrew, C. (Eds.). (2010). The Cognitive Life of Things: Recasting the Boundaries of the Mind. McDonald Institute Monographs.

Menary, R. & Gillett, A (2022) The Tools of Enculturation. Topics in Cognitive Science: 1–25. https://onlinelibrary.wiley.com/doi/10.1111/tops.12604

Norman, D.A. (1991) Cognitive Artifacts. In: Carroll, J.M. (ed.) Designing Interaction. Cambridge University Press, pp.17–38.

Norman, D.A. (1993) Things That Make Us Smart: Defending Human Attributes in the Age of the Machine. Addison–Wesley.

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.

 

The Lexical Semantics of Agency (Part I)

The concept of agency has been central in sociological theory at least since Parsons’s (selective) systematization of the late-nineteenth European tradition of social theory around the problematic of “action” (Parsons, 1937). Yet, since the dissolution of the sociological functionalist synthesis in the mid-1970s, anglophone social theory has been characterized by little agreement about what the proper conceptualization of agency should be (Joas, 1996; Campbell, 1996; Archer, 2000). The hope of consensus becomes even more tenuous (and the debate more acrimonious) when theorists try to join their preferred conceptualization of agency to their favorite conceptualization of structure in developing so-called “structure-agency” or “structuration” theories (Giddens, 1979; Sewell, 1992). Despite the difficulty of the overall endeavor, most analysts would agree that coming up with a coherent conceptualization of the nature of action/agency is a worthwhile endeavor (Emirbayer and Mische 1998; Hitlin & Elder, 2007). 

In this post, I argue that the hopes of developing a unitary conception of the notion of agency (and, by implication, of the relation between agency and structure) are indeed slim. Yet, this is not for the reasons that most theorists propose. Rather than being the product of the inherent ambiguity of all social science concepts or just the sheer difficulty of dealing with something as elusive as human subjectivity, a coherent account of the nature of action and agency is elusive because most social theorists misunderstand the nature of concepts and conceptualization. Drawing on an approach that takes seriously the embodied, embedded, and perceptual nature of concepts (see e.g., Lizardo, 2013, 2021). In this and following posts, I argue that the notions of action and agency in social theory are systematically organized according to underlying idealized cognitive models of agency, which include the grammatical category of agency concepts, their primary domain of instantiation, as well as various metaphorical extensions allowing agency to be expressed as an ᴏʙᴊᴇᴄᴛ or a ꜰᴏʀᴄᴇ possessed by actors or as a ᴅɪᴍᴇɴꜱɪᴏɴ of the actions people do. 

What (Kind of Concept) is Agency?

I will begin by asking a simple preliminary question. When contemporary sociological theorists use the concept of agency, what grammatical category does the lexeme agency fall under? Theorists who think of theory in purely propositional or sentential terms seldom ask this question. This is because they buy into the idea that we can separate the way that we use words from what words mean. Here I draw on work on cognitive grammar and cognitive semantics (e.g., Langacker, 1987, 1991) to suggest that conceptualization and grammatical symbolization are not separable: Grammatical symbolization tracks the underlying conceptual representation. Changing the grammatical category thus changes the underlying concept you are pointing to. Examining the grammatical status of the lexeme agency when social theorists use the concept thus gives a window as to what the underlying conceptualization—e.g., frames and folk idealized cognitive models—of this theoretical term is among them. It also sheds light on possible changes in its core meanings over time or even within the work of a single theorist or set of theorists. 

To answer the first question: When theorists use the concept of agency, they symbolize it as a noun (e.g., different from symbolizing as an adjective, such as “agentic”). Moreover, one thing that is particular about the work of contemporary social theorists is that agency is not just any noun; it is a mass noun. The mass noun status of agency in social theory today can be quickly verified by the impossibility of pluralizing it without changing the meaning (Langacker, 1987). For instance, “agencies” may refer to a series of government offices, but not to the hallowed concept developed by sociologists to deal with the element of “freedom from constraint” or “capacity to change structures” in human action. In cognitive linguistics, the grammatical category of noun, in the most general sense can be defined as a term that designates “a region in some domain, where a region is defined abstractly as a set of interconnected entities” (Langacker, 1991, p. 15).

Mass nouns—such as water, anxiety, or money—differ from count nouns (a glass of water, an anxiety attack, or a dollar bill) mainly because the region profiled by the lexical term is thought of as unbounded, although possibly “distributed” in uneven or disconnected regions in its domain of instantiationWhat is the domain of instantiation of entities referred to by nouns? The domain of instantiation of a noun is the realm of basic experience (e.g., space, time, mental life, social life, and the like) where the entities the noun designates can be found. We will see that the domain of instantiation of the most popular contemporary versions of the concept of agency is time.  

As noted, a central semantic feature of mass nouns is that they cannot be precisely counted. However, they can, however, be quantified, using so-called “vague quantifiers.” Thus, it is possible to say “some agency,” “more/less agency,” and the like. Construing an entity as a mass noun also imposes a series of other restrictions on the relevant conceptual content. The most important of these (see Langacker, 1991, p. 15), in addition to bounding, are homogeneity (all the “interconnected entities” that compose the unbounded region are thought of as interchangeable), contractibility (any sub-part of the abstract “substance” of agency is generally equivalent to any other subpart), and replicability (it is possible to produce more of the substance and the entity remains the same). A key conclusion of the analysis is that the “curiously abstract” (see Hitlin & Elder, 2007) concept of agency in social theory inherits all these properties, and acquires its curiously abstract status because it is largely conceived by theorists as a mass noun. 

Examples of the Mass Noun Conception of Agency

I have claimed that the “technical” concept of agency in contemporary social theory has two semantic characteristics that make it idiosyncratic; first, it is conceived as a mass noun; second, it is conceived as being instantiated in the temporal domain. Let us see some textual evidence that this is indeed the case in natural instances of conceptual usage among prominent theorists. 

Conceptualizations of agency as a mass noun, and the conceptual contrast between this construal and that of agency as a “count noun” are most clearly articulated in Giddens’s influential rendering of the concept:

‘Action’ or agency, as I use it, thus does not refer to a series of discrete acts combined together [sic] but to a continuous flow of conduct…involving a ‘stream of actual or contemplated causal interventions of corporeal beings in the ongoing process of events-in-the world’ (Giddens 1979: 55, italics added). 

First, analysts may find Giddens’s effort to note that agency is not a “series of discrete acts” but instead a “continuous flow of conduct” obscure, elusive, and unnecessary. Yet, this is a key conceptual move from the perspective of cognitive semantics; in terms of the ontology of abstract nouns in conceptual semantics, what Giddens is trying to say here is that agency is not a (countable) bounded ᴛʜɪɴɢ or object-like ᴇɴᴛɪᴛʏ (like a “discrete act”). Instead, agency is an abstract, unbounded ꜱᴜʙꜱᴛᴀɴᴄᴇ. This substance is continuously distributed (hence the reference to a “continuous flow”). Contrasting the “discrete act” and “continuous flow” cognitive models of agency is thus crucial for the point Giddens wants to make here.

This brings up a second question that is seldom explicitly posed by propositional analysts of agency: what is the domain of instantiation of agency as a mass noun? In other words, where does the unbounded, continuously distributed substance called “agency” reside? Giddens (1979) proposes an answer: The natural (prototypical) domain of instantiation of the concept of agency is time. Agency occurs in time. 

The intimate conceptual relation between agency and time is also clear in Emirbayer and Mische’s (1998) classic article on the subject:

…[O]ur central contribution is to begin to reconceptualize human agency as a temporally embedded process of social engagement, informed by the past (in its habitual aspect), but also oriented toward the future (as a capacity to imagine alternative possibilities) and toward the present (as a capacity to contextualize past habits and future projects within the contingencies of the moment). The agentic dimension of social action can only be captured in its full complexity, we argue, if it is analytically situated within the flow of time (963, italics added). 

Note that here, Emirbayer & Mische give us three distinct construals of the concept of agency: (1) agency as process, (2) agency as capacity, and (3) agency as dimension. Their conceptualization of agency is, therefore, not unitary, but combines different ways of conceiving the idea. These construals are incompatible concerning the underlying cognitive models they presuppose, and therefore, the definition of agency Emirbayer & Mische provide can best be thought of as a “conceptual federation” of the idea rather than a unitary construct. This is something that has not been explicitly noted in the secondary literature.

Nevertheless, Emirbayer & Mische’s process construal of agency is compatible with Giddens’s temporally distributed substance concept of agency as involving properties of a “flow” or “stream” of conduct (in time). For Giddens, the basic idea is that this flow of intended or contemplated acts can “change” the causal flow of events in the world. Just like Emirbayer and Mische (1998), Giddens sees time (the realm of process and change) as the primary domain of instantiation of agency as an abstract substance. 

Giddens elaborates as follows:

…it is a necessary feature of action that, at any point in time, the agent ‘could have acted otherwise’: either positively in terms of attempted intervention in the process of ‘events in the world’, or negatively in terms of forbearance (1979: 56, italics added).

Compare to Emirbayer and Mische (1998) who note that:

The key to grasping the dynamic possibilities of human agency is to view it as composed of variable and changing orientations within the flow of time (964, italics added). 

Thus, a key conclusion from this preliminary analysis is that there seems to be at least one “technical” concept of agency shared across various influential theorists in the contemporary scene, especially those subscribing to a “structuration” perspective. This is the idea of agency as a continuous abstract substance distributed in time. In a future post, I will examine other conceptions.

Why the Process Conception of Agency is Unbearably Abstract

Agency as an unbounded substance instantiated in time functions as a pleasing, even aesthetic theoretical “solution.” Yet, when theorists attempt to use this notion for the practical job of theorizing, they find it “curiously abstract” and thus conceptually unusable (Hitlin & Elder, 2007)

The curiously abstract nature of the mass noun agency concept, as well as its limitations as a resource to “think with” should not surprise us. Abstract concepts have a direct or indirect grounding in embodied concepts (Grady, 1997; Lakoff & Johnson, 1999), and mass nouns, especially those denoting material substances or fluids such liquids, gases, and so forth serve as the image-schematic experiential grounding for many abstract concepts and grammatical categories (Janda, 2004; Lakoff & Johnson, 1980). Thus, the mass noun status of agency builds abstraction by default. Count nouns, on the other hand, tend to point toward conceptual entities at the concrete end of the construal spectrum; contrast for instance money (mass noun) with a dollar (count noun). In addition, as work by Lera Boroditsky (2001) and others have shown, the target domain of time conceived on its own is hard to conceptualize without resorting to more concrete source domains. Instead, most “objective” conceptualizations of the temporal dimension rely on conceptual metaphors from the spatial and physical movement source domains to conceive of time, its passage, duration, calendrical, and the like. 

This means that the process conceptions of agency instantiated in the time domain are bound to be doubly abstract. Agency is conceptualized as an unbounded, continuous substance, and it is instantiated in time. This over-abstractness accounts for why this particular cognitive model of agency is of limited use to most social theorists (let alone applied researchers) despite the analytic elegance and seeming appeal of such formulations (Emirbayer & Mische, 1998; Giddens, 1979) and its status as an entrenched technical formulation in contemporary social theory.

Another key limitation is that the abstract substance version of the concept of agency is hard to compare, link or contrast to its favorite “opposite,” namely, the notion of structure, which is decidedly object-like at a conceptual level (Lizardo, 2013).  In other words, the mass noun status of the technical concept clashes conceptually with most default conceptualizations of social structure(s) which see the latter as  “concrete” (as in the standard social networks mantra), object-like, and countable. Accordingly, the process conception of agency embedded in time does not play well with conceptions of structure that try to keep these two abstract entities separable (Archer, 2000).

As noted, the reason the curiously abstract concept of agency is hard to mesh with the tremendously concrete concept of structure dominant in contemporary sociology is that the underlying conceptual bases of the (prototypical) notion of structure are not abstract substances, but concrete countable objects or ᴇɴᴛɪᴛɪᴇꜱ (Lizardo, 2013). This is the reason we can refer to social structures in the plural while preserving semantics (Martin, 2009), but not human “agencies.” In fact, this is the reason Emirbayer & Mische (1998, p. 966), after noting that in typical social theory structure “a spatial category rather than…a temporal construction,” attempted to recast the notion of structure—with mixed success—in temporal not spatial terms, essentially trying to shift the prototypical domain of instatiation of that notion so that it could fit with that of of agency. Accordingly, agency/structure theorists outside the structuration tradition (e.g., critical realists, symbolic interaction) reject conceptions of agency, such as Giddens’s but also by implication that of Emirbayer and Mische because these analysts construe agency as inherently embedded, and thus inseparable from an abstract temporal flow that cannot be “bounded” or cut into distinct, separable and countable “instances” (Archer, 2000; Hitlin & Elder, 2007). What is at stake here is precisely the conceptual status of agency as a mass or count noun. 

References

Abelson, R. P. (1986). Beliefs Are Like Possessions. Journal for the Theory of Social Behaviour16(3), 223-250.

Archer, M. S., & Archer, M. S. (2000). Being Human: The Problem of Agency. Cambridge University Press.

Campbell, C. (2009). Distinguishing the Power of Agency from Agentic Power: A Note on Weber and the “Black Box” of Personal Agency. Sociological Theory, 27(4), 407–418.

Emirbayer, M., & Mische, A. (1998). What is agency? The American Journal of Sociology, 103(4), 962–1023.

Giddens, A. (1979). Central Problems in Social Theory: Action, Structure, and Contradiction in Social Analysis. University of California Press.

Hitlin, S., & Elder, G. H., Jr. (2007). Time, Self, and the Curiously Abstract Concept of Agency. Sociological Theory, 25(2), 170–191.

Joas, H. (1996). The Creativity of Action. University of Chicago Press.

Langacker, R. W. (1987). Foundations of Cognitive Grammar: Theoretical prerequisites (Vol. 1). Stanford University Press.

Langacker, R. W. (1991). Foundations of Cognitive Grammar: descriptive application (Vol. 2). Stanford University Press.

Langacker, R. W. (2008). Cognitive Grammar: A Basic Introduction. Oxford University Press.

Lizardo, O. (2013). R e‐conceptualizing Abstract Conceptualization in Social Theory: The Case of the “Structure” Concept. Journal for the Theory of Social Behaviour.

Lizardo, O. (2021). The Cognitive-Historical Origins of Conceptual Ambiguity in Social Theory. In S. Abrutyn & O. Lizardo (Eds.), Handbook of Classical Sociological Theory (pp. 607–630). Springer International Publishing.

Sewell, W. H., Jr. (1992). A Theory of Structure: Duality, Agency, and Transformation. The American Journal of Sociology, 98(1), 1–29.

Wax On, Wax Off: Transposability and the Problem with “Domains”

 

In the film Happy Gilmore, Adam Sandler plays a hockey player who is a terrible skater but has a powerful slap shot. The main story arc of the film is that Sandler will use this ability in the entirely different sport of golf. This is a fairly common trope. Very often this becomes associated with something biological—we don’t know where Sandler’s character learned to hit the puck as he does, he may just be “a natural.” In the Karate Kid, though, we famously see the “wax on, wax off” motions of waxing Mr. Miyagi’s car turned into blocking motions in hand-to-hand combat. This same scenario occurs in, for example, the zombie series Santa Clarita Diet. Joel is instructed to shove a pear into a dead chicken as quickly as possible. Later, when fighting a zombie, he shoves a lemon into the zombie’s mouth as if by muscle memory. We then see that the odd pear-chicken skill is meant to remove the zombie’s ability to bite. In each case, we see an ability seemingly transposed across domains.

In a recent blog post, Omar offered a critical discussion of the use of “transposability” as a concept in the sociology of culture. Namely, the idea that schematic knowledge is, or must be, “transposable” across “domains” is a critical error:

Bourdieu and Sewell (drawing on Bourdieu) made a crucial property conjunction error, bestowing a magical power (transposability) to implicit (personal) culture. This type of personal culture cannot display the transposability property precisely because it is implicit…

If implicit culture is, by definition, domain-specific, how can it be transposed across domains? The argument, as I understand it is, to the extent schemas are transposed “requires that they be ‘representationally redescribed’… into more flexible explicit formats.” The complication with this discussion thus far, though, is that “domain” is doing a lot of theoretically heavy lifting, and I don’t think it can hold the weight.

The Problem with Domains

Let’s start with Durkheim’s “puzzle” in the introduction to Elementary Forms. As he saw it, in the quest to understand where knowledge comes from there were two camps: the Rationalists and the Empiricists. He thought the Empiricists were on the right track in that we gain knowledge from our moment-to-moment experience. However, the Empiricists didn’t have a solution for integrating what we learn across each moment: 

…the things which persons perceive change from day to day, and from moment to moment. Nothing is ever exactly the same twice, and the stream of perception…must be constantly changing… The question from this perspective, is how general concepts can be derived from this… stream of particular experiences, which are literally not the same from one moment to the next, let alone from person to person.” (Rawls 2005, 56)

As we are exposed to chairs in different moments, what is it that allows us to pull out the basic properties of “chairness”? Indeed, even the same chair at different times and in different places will be objectively “different”—diverse shading, slow decaying, a coating of dust. Of course, Durkheim was less concerned with the mundane (like chairness) than with the “pure categories of the understanding” a.k.a. “skeleton of thought” a.k.a. the “elementary forms” or often just “The Categories.” We would likely call all of these schemas today, and something more like image schemas or primary schemas. 

The developmental neuroscientist Jean Mandler (2004) approaches Durkheim’s problem of knowledge with the question: what is the minimum that must be innate to get learning started? She argues that we have an innate attentional bias towards things in motion, but more importantly, we also have an innate ability to schematize and redescribe experience in terms of those schematizations. Schematization is, in my mind, best understood not as retaining but as forgetting, elegant forgetting. As the richness of an immediate moment slowly starts to fade, certain properties are retained because they have structural analogies in the current moment. Properties that do not have such analogies in the current moment continue along a fading path, slowly falling away (unless brought to the fore by the ecology of a new moment). What is left is a fuzzy structure — a schema — with probabilistic associations among properties. Probabilities shaped by exposure to perceptual regularities. Therefore, the most persistent perceptual regularities will also be the most widely shared.

Mandler also argues that once we have a few basic schemas, as fuzzy and open-ended as they may continue to be, we can then redescribe our experience using these schemas. More importantly for the present discussion, both schematization and redescription seem to implicate transposability. But, Mandler works with infants and toddlers, so much of this occurs rapidly in human development—before what we would typically call “conscious control” is up and running.

It is here where the discussion implicates “domains.” Can we reserve “transposability” as the use of schematic knowledge in a “new domain”? And, then simply call the more pervasive “carrying of schemas from moment to moment” something else? In this setup, if encountering or thinking about a chair in chair-domains (domains where chairs typically are), then drawing on my chair-schema will not qualify as transposability. It is only when chairs are encountered or thought about in non-chair-domains (domains where chairs typically aren’t) that transposition is occurring. Without an analytical definition of what a domain is, however, this becomes slippery: If transposition requires that implicit knowledge be “representationally redescribed into more flexible explicit formats,” then by definition we can only know “new domains” whenever we see this occurring.

Spectrum of Transposability

I think we should ditch domains as the linchpin of transposability rather than salvage it. Schematic knowledge is transposable. At least in the most basic notion of “drawing on implicit knowledge” from moment to moment. But, sure, it is not transposable without constraint. Implicit knowledge is called forth by the recognition of familiar affordances in a moment. The problem is that affordances are not cleanly bundled into mutually exclusive “domains.” 

Perhaps transposition across normatively distinct domains typically occurs via deliberate mediation — but the idea that it only occurs via deliberate mediation is perhaps a step too far. New situations will evoke some implicit knowledge acquired in a prior situation without the individual deliberating. Much of what we call “being a natural” is likely just such a process. True, Mr. Myagi was conscious that “wax on, wax off” would transpose to fighting, but Daniel was not. And, more importantly, it was Daniel who was transposing it, and it was the affordances of the fighting situation that evoked the “wax on, wax off” response.

As a starker example of transposition without deliberation — or even against deliberation — we can look to hysteresis: The mismatch between the person and environment (Strand and Lizardo 2017). When I was a freshman in college, I boxed for extra money. I had never boxed before, but I had wrestled for years.  Luckily for me, someone was kind enough to properly wrap my wrists during my first fight! During that fight, I continually did something I knew was not correct: I got an underhook, a wrestling move involving placing your bicep in the armpit of your opponent and wrapping your hand around their shoulder, giving you leverage over their body position. The second or third time I did this, the referee stopped the fight and informed me that this was not allowed in boxing and I would lose points if I continued to do it. Getting an underhook when the move was “open” was “second nature.” It was “muscle memory.” I  deliberately tried to stop this automatic response. I continued to fail. I lost points. Despite this being a domain distinct from wrestling (normatively), my body interpreted the affordances of the moment as being a familiar domain (ecologically). Transposition occurred against my conscious effort.

References

Durkheim, Emile. 1995. The Elementary Forms of Religious Life. New York: Free Press.

Mandler, Jean Matter. 2004. The Foundations of Mind: Origins of Conceptual Thought. Oxford University Press.

Rawls, Anne Warfield. 2005. Epistemology and Practice: Durkheim’s The Elementary Forms of Religious Life. Cambridge University Press.

Strand, Michael, and Omar Lizardo. 2017. “The Hysteresis Effect: Theorizing Mismatch in Action.” Journal for the Theory of Social Behaviour 47(2):164–94.

From Dual-Process Theories to Cognitive-Process Taxonomies

Although having a history as old as the social and behavioral sciences (and for some, as old as philosophical reflections on the mind itself), dual-process models of cognition have been with us only for a bit over two decades, becoming established in cognitive and social psychology in the late 1990s (see Sloman, 1996 and Smith and DeCoster, 2000 for foundational reviews). The implicit measurement revolution provided the “data” side to the theoretical and computational modeling side, thus fomenting further theoretical and conceptual development (Strack & Deutsch, 2004; Gawronski & Bodenhausen, 2006). Although not without its critics, the dual-process approach has now blossomed into an interdisciplinary framework useful for studying learning, perception, thinking, and action (Lizardo et al., 2016). In sociology, dual-process ideas were introduced by way of the specific dual-process model of moral reasoning developed by Jonathan Haidt (2001) in Steve Vaisey’s (2009) now classic and still heavily cited paper. Sociological applications of the dual-process framework for specific research problems now abound, with developments on both the substantive and measurement sides (Miles, 2015; Miles et al. 2019; Melamed et al. 2019; Srivastava & Banaji, 2011).

The dual-process framework revolves around the ideal-typical distinction between two “modes” or “styles” of cognition (Brett & Miles, 2021). These are now very familiar. One is the effortful, usually conscious, deliberate processing of serially presented information, potentially available for verbal report (as when reasoning through a deductive chain or doing a hard math problem in your head). The other is the seemingly effortless, automatic, usually unconscious, associative processing information (as when a solution to a problem just “comes” to you, or when you just “know” something without seemingly having gone through steps to reach the solution). This last is usually referred to as intuitive, automatic, or associative “Type 1” cognition, and the former is usually referred to as effortful, deliberate, or non-automatic “Type 2” cognition.

As with many hard and fast distinctions, there is the virtue of simplification and analytic power, but there is the limitation, evident to all, that the differentiation between Type 1 versus Type 2 cognition occludes as much as it reveals. For instance, people wonder about the existence of “mixed” types of cognition or iterative cycles between the two modes or the capacity of one mode (usually Type 2) to override the outputs of the other (usually Type 1). It seems like the answer to all these wonders is a general “yes.” We can define a construct like “automaticity” to admit various “in-between” types (Moors & De Houwer, 2006), suggesting that a pure dichotomy is too simple (Melnikoff & Bargh, 2018). And yes, the two types of cognition interact and cycle (Cunningham & Zelazo, 2007). The interactive perspective is even built into some measurement strategies, which rely on overloading or temporarily overwhelming the deliberate system to force people to respond with intuitive Type 1 cognition (as in so-called “cognitive load” techniques; see Miles, 2015 for a sociological application).

Another sort of wonder revolves around whether these are the only types of cognition that exist. Are there any more types? Accordingly, some analysts speak of “tri” or “quad” process models and the like (Stanovich, 2009). It seems, therefore, that field is moving toward a taxonomic approach to the study of cognitive processes. However, the criteria or “dimensions” around which such taxonomies are to be constructed are in a state of flux. As I noted in a previous post, moving toward a taxonomic approach is generally a good thing. Moreover, the field of memory research is a good model for how to build taxonomic theory in cognitive social science (CSS), especially since the “kinds” typically studied in CSS are usually “motley” (natural kinds that decompose into fuzzy subkinds). When studying motley kinds and organizing into fruitful taxonomies, it is essential to focus on the analytic dimensions and let the chips fall where they may. This is different from thinking up “new types” of cognition from the armchair in unprincipled ways, where the dimensions that define the types are ill-defined (as with previous attempts to talk about tri-process models of cognition and the like). Moreover, the dimensional approach leaves things open to discover surprising “subkinds” that join properties that we would consider counter-intuitive.

Accordingly, an upshot of everyone now accepting (even begrudgingly) some version of the dual-process theory is that we also agree that the cognitive-scientific kind “cognition” is itself motley! That is, whatever it is, cognition is not a single kind of thing. Right now, we kind of agree that it is at least two things (as I said, an insight that is as old as the Freudian distinction between primary and secondary process), but it is likely that it could be more than two. In this post, I’d like to propose one attempt to define the possible dimensional space from which a more differentiated typology of cognitive processes can be constructed.

Taxonomizing Cognition

So if we needed to choose dimensions to taxonomize cognition, where would we begin? I think a suitable candidate is to pick two closely aligned dimensions of cognition that people thought were fused or highly correlated but now are seen as partially orthogonal. For example, in a previous post on the varieties of “implictness” (which is arguably the core dimension of cognition that defines the core distinction in dual-process models), I noted that social and cognitive psychologists differentiate between two criteria for deeming something “implicit.” First, a-implicitness uses an “automaticity” criterion. Here, cognition is implicit if it is automatic and explicit if it is deliberate or effortful. Second, there is u-implicitness, which uses a(n) (un)consciousness criterion. Here, cognition is implicit if it occurs outside of consciousness, and it is explicit if it is conscious.

I implied (but did not explicitly argue) in that post that maybe these two dimensions of explicitness could come apart. If they can, these seem like pretty good criteria to build a taxonomy of cognitive process kinds that goes beyond two! This is precisely what the philosophers Nicholas Shea and Chris Frith did in a paper published in 2016 in Neuroscience of ConsciousnessCross-classifying the type of processing (deliberate v. automatic) against the type of representations over which the processing occurs (conscious v. unconscious), yields a new “type” of cognition which they refer to as “Type 0 cognition.”

In Shea and Frith’s taxonomy, our old friend Type 1 cognition refers to the automatic processing of initially conscious representations, typically resulting in conscious outputs. In their words, “[t]ype 1 cognition is characterized by automatic, load-insensitive processing of consciously represented inputs; outputs are typically also conscious.” (p.4). This definition is consistent with Evans’s (2019) more recent specification of Type 1 cognition as working-memory independent cognition that still uses working memory to “deposit” the output of associative processing. In Evans’s words,

While Type 1 processes do not require the resources of working memory or controlled attention for their operation (or they would be Type 2) they do post their products into working memory in a way that many autonomous processes of the brain do not. Specifically, they bring to mind judgements or candidate responses of some kind accompanied by a feeling of confidence or rightness in that judgement (p. 384).

For Shea and Frith (2016), on the other hand, our other good friend, Type 2 cognition, refers to the deliberate, effortful processing of conscious representations. In their words,

Type 2 cognition is characterized by deliberate, non-automatic processing of conscious representations. It is sensitive to cognitive load: type 2 processes interfere with one another. Type 2 cognition operates on conscious representations, typically in series, over a longer timescale than type 1 cognition. It can overcome some of the computational limitations of type 1 cognition, piecemeal, while retaining the advantage of being able to integrate information from previously unconnected domains. It is computation-heavy and learning-light: with its extended processing time, type 2 cognition can compute the correct answer or generate optimal actions without the benefit of extensive prior experience in a domain (p. 5).

By way of contrast with these familiar faces, our new friend Type 0 cognition refers to the automatic processing of non-conscious representations. Shea and Frith see isolating Type 0 cognition as a separate cognitive-process subkind as their primary contribution. Previous work, in their view, has run Type 0 and Type 1 cognition together, to their analytic detriment. Notably, they argue for the greater (domain-specific) efficiency and accuracy of Type 0 cognition over Type 1. They note that various deficiencies of Type 1 cognition identified in such research programs as the “heuristics and biases” literature come from the fact that, in Type 1 cognition, there is a mismatch between process and representation because automatic/associative processes are recruited to deal with conscious representational inputs.

For instance, Type 1 cognition is at work when Haidt asks people whether they would wear Hitler’s t-shirt, and they say “ew, no way!” but are unable to come up with a morally reasonable reason why (or make up an implausible one on the spot). Type 1 moral cognition “misfires” here because the associative (“moral intuition”) system was recruited to process conscious inputs, relied on an associative/heuristic process to generate an answer (in this case, based on implicit contact, purity, and contagion considerations), and produced a conscious output, the origins of with subjects are completely unaware of (and is thus forced to retrospectively confabulate using Type 2 cognition). The same goes for judgment and decision-making producing answers to questions when engaging in the base-rate fallacy, using a representativeness heuristic, and the like (Kahneman, 2011). 

The types of cognition for which a match is made in heaven between process and representation (like Type 2 and their Type 0) result in adaptive cognitive processes that “get the right answer.” Type 2 cognition refers to domain-general problems requiring information integration and the careful weighing of alternatives. In Type 0 cognition, this refers to domain-specific problems requiring fast, adaptive cognitive processing and action control, where consciousness (if it were to rear its ugly head) would spoil the fun and impair the effectiveness of the cognitive system to do what is supposed to do, similar to athletes who “choke” when they become conscious of what they are doing (see Beilock, 2011).

So, what is Type 0 cognition good for? Shea and Frith point to things like the implicit learning of probabilistic action/reward contingencies after many exposures (e.g., reinforcement learning), where neither the probabilities nor the learning process is consciously represented, and the learning happens via associative steps. As they note, in “model-free reinforcement learning can generate optimal decisions when making choices for rewards, and feedback control can compute optimal action trajectories…non-conscious representation goes hand-in-hand with correct performance” (p. 3). In the same way, “Type 0 cognition is likely to play a large role in several other domains, for example in the rich inferences which occur automatically and without consciousness in the course of perception, language comprehension and language production” (ibid).

Organizing the Types

So, where does Shea and Frith’s taxonomy of cognitive process kinds leave us? Well, maybe something like the dimensional typology shown in Figure 1. It seems like at least three different cognitive process kinds are well-defined, especially if you are convinced that we should distinguish Type 0 from Type 1 cognition (and I think I am).

Figure 1.

However, as I argued earlier, a key advantage of beginning with dimensions in any taxonomical exercise is that we may end up with a surprise. Here, it is the fact that a fourth potential type of cognition now appears in the lower-right quadrant, one that no one has given much thought to before. Type ??? cognition: deliberate processing of unconscious representations. Can this even be a thing? Shea and Frith do note this implication of their taxonomic exercise but think it is too weird. They even point out that it may be a positive contribution of their approach to have discovered this “empty” slot in cognitive-process-kind space. In their words, “[w]hat of the fourth box? This would be the home of deliberate processes acting on non-conscious representations. It seems to us that there may well be no type of cognition that fits in this box. If so, that is an important discovery about the nature of consciousness” (p. 7).

Nevertheless, are things so simple? Maybe not. The Brains Blog dedicated a symposium to the paper in 2017 in which three authors provided commentaries. Not surprisingly, some of the commenters did not buy the “empty slot” argument. In their commentJacob Berger points to some plausible candidates for Shea and Frith’s Type ??? cognition (referred to as “Type 0.5 cognition”). This includes the (somewhat controversial) work of Dijksterhuis, Aarts, and collaborators (e.g., Dijksterhuis & Nordgren, 2006; Dijksterhuis & Aarts, 2010) on “unconscious thought theory” (UTT) (see Bargh, 2011 for a friendly review). In the UTT paradigm, participants are asked to make seemingly deliberate choices between alternatives, with a “right” answer aimed at maximizing a set of quality dimensions. At the same time, conscious thinking is impaired via cognitive load. The key result is that participants who engage in this “unconscious thinking” end up making choices that are as optimal as people who think about it reflectively. So, this seems to be a case of a deliberate thinking process operating over unconscious representations.

Berger does anticipate an objection to UT as being a candidate for Type ??? cognition, which itself brings up an issue with critical taxonomic ramifications:

S&F might reply that such [UT] cases are not genuinely unconscious because, like examples of type-1 cognition, they involve conscious inputs and outputs. But if this processing is not type 0.5, then it is hard to see where S&F’s taxonomy accommodates it. The cognition does not seem automatic, akin to the processing of type 0 or type 1 of which one is unaware (it seems, for example, rather domain general); nor does it seem to be a case of type-2 cognition, since one is totally unaware of the processing that results in conscious outputs. Perhaps what is needed is an additional distinction between the inputs/outputs of a process’ being conscious and the consciousness of states in the intervening processing. In type-1 cognition, the inputs/outputs are conscious, but the states involved in the automatic processing are not; in type-2, both are conscious. We might therefore regard Dijksterhuis’ work as an instance of ‘type-1.5’ cognition: conscious inputs/outputs, but deliberative unconscious processing.

Thus, Berger proposes to dissociate not only conscious/unconscious representations from deliberate/automatic processing but also adds the dimension of whether the inputs and outputs of the cognitive process and its intervening steps are themselves conscious or unconscious. Berger’s implied taxonomy can thus be represented as in Figure 2.

Figure 2.

Figure 2 clarifies that the actual mystery type does not connect conscious inputs and outputs with deliberate unconscious processing (UT), but a type linking unconscious inputs and outputs with deliberate unconscious processing (the new Type ???). Also, the figure makes clear that the proper empty slot is a type of cognition conjoining unconscious inputs and outputs with deliberate conscious processing; this bizarre and implausible combination can indeed be ruled out on a priori grounds. Note, in contrast, that if there is such a thing as deliberate unconscious processing (and the jury is still out on that), there is no reason to rule out the new Type ??? cognition shown in Figure 2 on a priori grounds (as Shea and Frith tried to do with Berger’s Type 1.5). For instance, Bargh (2011) argues that unconscious goal pursuit (a type of unconscious thought) can be triggered outside of awareness (unconscious input) and also has behavioral consequences (e.g., trying hard on a task) that subjects may also be unaware of (unconscious output). In this sense, Bargh’s unconscious goal pursuit would qualify as a candidate for Type ??? cognition. So, following Berger’s recommendation, we end up with five (I know an ugly prime) candidate cognition types. 

So, What?

Is all we are getting after all of this a more elaborate typology? Well, yes. And that is good! However, I think the more differentiated approach to carving the cognitive-process world also leads to some substantive insight. I refer in particular to Shea and Frith’s introduction of the Type 0/Type 1 distinction. For instance, in a recent review (and critique) of dual-process models of social cognition, Amodio proposes an “interactive memory systems” account of attitudes and impression formation (“Social Cognition 2.0”) that attempts to go beyond the limitations of the traditional dual-process model (“Social Cognition 1.0”).

Amodio’s argument is wide-ranging, but his primary point is that there are multiple memory systems and that a conception of Type 1 cognition as a single network of implicit concept/concept associations over which unconscious cognition operates is incomplete. In addition to concept/concept associations, Amodio points to other types of associative learning, including Pavlovian (affective) and instrumental (reinforcement learning). Amodio’s primary point is that something like an “implicit attitude,” insofar as it recruits multiple but distinct (and dissociable) forms of memory and learning subserved by different neural substrates, is not a single kind of thing (a taxonomical exercise for the future!). This dovetails nicely with the current effort to taxonomize cognitive processes. Thus, a standard conceptual association between categories of people and valenced traits operates via Type 1 cognition. However, it is likely that behavioral approach/avoid tendencies toward the same type of people, being the product of instrumental/reinforcement learning mechanisms, operate via Shea and Frith’s Type 0 cognition.

References

Bargh, J. A. (2011). Unconscious Thought Theory and Its Discontents: A Critique of the Critiques. Social Cognition, 29(6), 629–647.

Beilock, S. L. (2011). Choke. The secret of performing under pressure. London: Constable.

Brett, G., & Miles, A. (2021). Who Thinks How? Social Patterns in Reliance on Automatic and Deliberate Cognition. Sociological Science, 8, 96–118.

Cunningham, W. A., & Zelazo, P. D. (2007). Attitudes and evaluations: a social cognitive neuroscience perspective. Trends in Cognitive Sciences, 11(3), 97–104.

Dijksterhuis, A., & Aarts, H. (2010). Goals, attention, and (un)consciousness. Annual Review of Psychology, 61, 467–490.

Evans, J. S. B. T. (2019). Reflections on reflection: the nature and function of type 2 processes in dual-process theories of reasoning. Thinking & Reasoning, 25(4), 383–415.

Gawronski, B., & Bodenhausen, G. V. (2006). Associative and propositional processes in evaluation: an integrative review of implicit and explicit attitude change. Psychological Bulletin, 132(5), 692–731.

Haidt, J. (2001). The emotional dog and its rational tail: a social intuitionist approach to moral judgment. Psychological Review, 108(4), 814–834.

Kahneman, D. (2011). Thinking, Fast and Slow. Farrar, Straus and Giroux.

Lizardo, O., Mowry, R., Sepulvado, B., Stoltz, D. S., Taylor, M. A., Van Ness, J., & Wood, M. (2016). What are dual process models? Implications for cultural analysis in sociology. Sociological Theory, 34(4), 287–310.

Melamed, D., Munn, C. W., Barry, L., Montgomery, B., & Okuwobi, O. F. (2019). Status Characteristics, Implicit Bias, and the Production of Racial Inequality. American Sociological Review, 84(6), 1013–1036.

Melnikoff, D. E., & Bargh, J. A. (2018). The mythical number two. Trends in cognitive sciences22(4), 280-293.

Miles, A. (2015). The (Re)genesis of Values: Examining the Importance of Values for Action. American Sociological Review, 80(4), 680–704.

Miles, A., Charron-Chénier, R., & Schleifer, C. (2019). Measuring Automatic Cognition: Advancing Dual-Process Research in Sociology. American Sociological Review, 84(2), 308–333.

Moors, A., & De Houwer, J. (2006). Automaticity: a theoretical and conceptual analysis. Psychological Bulletin, 132(2), 297–326.

Sloman, S. A. (1996). The empirical case for two systems of reasoning. Psychological Bulletin, 119(1), 3.-22

Smith, E. R., & DeCoster, J. (2000). Dual-Process Models in Social and Cognitive Psychology: Conceptual Integration and Links to Underlying Memory Systems. Personality and Social Psychology Review: An Official Journal of the Society for Personality and Social Psychology, Inc, 4(2), 108–131.

Srivastava, S. B., & Banaji, M. R. (2011). Culture, Cognition, and Collaborative Networks in Organizations. American Sociological Review, 76(2), 207–233.

Stanovich, K. E. (2009). Distinguishing the reflective, algorithmic, and autonomous minds: Is it time for a tri-process theory? In J. S. B. T. Evans (Ed.), In two minds: Dual processes and beyond , (pp (Vol. 369, pp. 55–88). Oxford University Press.

Strack, F., & Deutsch, R. (2004). Reflective and impulsive determinants of social behavior. Personality and Social Psychology Review: An Official Journal of the Society for Personality and Social Psychology, Inc, 8(3), 220–247.

Vaisey, S. (2009). Motivation and Justification: A Dual-Process Model of Culture in Action. American Journal of Sociology, 114(6), 1675–1715.

Consciousness and Schema Transposition

In a recent paper published in American Sociological ReviewAndrei Boutyline and Laura Soter bring much-needed conceptual clarification to the sociological appropriation of the notion of schemas while also providing valuable and welcome guidance on future uses of the concept for practical research purposes. The paper is a tour de force, and all of you should read it (carefully, perhaps multiple times), so this post will not summarize their detailed argument. Instead, I want to focus on a subsidiary but no less important set of conclusions towards the end, mainly having to do with the relationship between declarative and nondeclarative cognition and an old idea in sociological action theory due to Bourdieu (1980/1990) that was further popularized in the highly cited article by Sewell (1992) on the duality of structure. I refer to the notion of schematic transposition.

In what follows, I will first outline Bourdieu’s and Sewell’s use of the notion and then go over how Boutyline and Soter raise a critical technical point about it, pointing to what is perhaps a consequential theoretical error. Finally, I will close by pointing to some lines of evidence in cognitive neuroscience that seem to buttress Boutyline and Soter’s position.

The idea of schematic transposition is related to an older idea due to Piaget of schema transfer. The basic proposal is that we can learn to engage in a set of concrete activities (e.g., let’s say “seriation” or putting things in rows or lines) in one particular practical context (putting multiple pebbles or marbles in a line). Then, after many repetitions, we develop a schema for it. Later, when learning about things in another context, let’s say “the number line” in basic arithmetic, we understand (assimilate) operations in this domain in terms of the previous seriation schema. Presumably, analogies and conceptual metaphors also depend on this schema transfer mechanism. In Logic of Practice, Bourdieu built this dynamic capacity for schema transfer into the definition of habitus everyone loves to hate, noting that the habitus can be thought of as “[s]ystems of durable, transposable dispositions, structured structures predisposed to function as structuring structures…” and so forth (p. 53).

This idea of transposibility ends up being essential for a habit theory like Bourdieu’s because it adds much-needed flexibility and creativity to how we conceive the social agent going about their lives (Joas, 1996). This is because thinking of action as driven by habitus does not entail people stuck with “one-track” inflexible or mechanical dispositions. Instead, via their capacity to transpose classificatory or practical habits learned in one domain to others, their internalized practical culture functions in a more “multi-track” way, being thus adaptive and creative. In an old paper on the notion of habitus (2004), I noted something similar to this, pointing out that “it is precisely this idea of flexible operations that allows for the habitus to not be tied to any particular content…instead, the habitus is an abstract, non-context specific, transposable matrix” (p. 391-392). Thus, there is something about transposability that seems necessary in a theory of action so that it does not come off as overly deterministic or mechanical.

In his famous 1992 paper, Sewell went even further, putting transposability at the very center of his conception of social change and agency. Departing from a critique of Bourdieu, Sewell noted two things. First (p. 16), any society contains a multiplicity of “structures” (today, we’d probably use the term “field,” “sphere,” or “domain”). Secondly (p. 17), this means people need to navigate across them somehow. Single-track theories of habit and cognition cannot explain how this navigation is possible. This navigation is made possible, according to Sewell, only by theorizing “the transposability of schemas.” As Sewell notes:

…[T]he schemas to which actors have access can be applied across a wide range of circumstances…Schemas were defined above as generalizable or transposable procedures applied in the enactment of social life. The term “generalizable” is taken from Giddens; the term “transposable,” which I prefer, is taken from Bourdieu…To say that schemas are transposable, in other words, is to say that they can be applied to a wide and not fully predictable range of cases outside the context in which they are initially learned…Knowledge of a rule or a schema by definition means the ability to transpose or extend it-that is, to apply it creatively. If this is so, then agency, which I would define as entailing the capacity to transpose and extend schemas to new contexts, is inherent in the knowledge of cultural schemas that characterizes all minimally competent members of society (p. 17-18).

Thus, in Sewell, the very concept of agency becomes defined by the actor’s capacity to transpose schemas across contexts and domains!

Nevertheless, is the link between the idea of schema and that of schematic transposition cogent? Boutyline and Soter (2021) incisively point out that it may not be. To see this, it is important to reiterate their “functional” definition of schemas as “socially shared representations deployable in automatic cognition” (735). The key here is “automatic cognition.” As I noted in an earlier post on “implicit culture,” a common theoretical error in cultural theory consists of taking the properties of forms of “explicit” representations we are familiar with and then postulating that there are “implicit” forms of representation having the same properties, except that they happen to be unconscious, tacit, implicit and the like. The problem is that representations operating at the tacit level need not (and usually cannot) share the same properties as those operating at the explicit level.

Boutyline and Soter note a similar tension in ascribing the property “transposable,” to a tacit or nondeclarative form of culture like a schema, which generally operates in type I cognition. In their words,

A..correlate of Type I cognition is domain-specificity. Type II knowledge can be context-independent and abstract—qualities enabled in part via the powerful expressive characteristics of language—and tied to general-purpose intelligence and logical or hypothetical reasoning…In contrast, Type I knowledge is often domain-specific—thoroughly tied to, and specifically functioning within, contexts closely resembling the one in which it was learned…Type II knowledge (e.g., mathematical or rhetorical tools) can be transposed with relative ease across diverse contexts, but the principles that underlie Type I inferences may not be transferrable to other domains without the help of Type II processes.

So, it seems like both Bourdieu and Sewell (drawing on Bourdieu) made a crucial property conjunction error, bestowing a magical power (transposability) to implicit (personal) culture. This type of personal culture cannot display the transposability property precisely because it is implicit (previously, I argued that people do this with a version of symbolic representational status). Boutyline and Soter (p. 742) revisit Sewell’s example of the “commodity schema,” convincingly demonstrating that, to the extent that this schema ends up being “deep” because it is transposable, specific episodes of transposability cannot themselves operate in automatic autopilot. Instead, “novel instance[s] of commodification” must be “consciously and intentionally devised” (ibid). Thus, to the extent that they are automatically deployable, schemas are non-transposable. Transposability of schemas requires that they be “representationally redescribed” (in terms of Karmiloff-Smith 1995) into more flexible explicit formats. Tying this insight to recent work on the sociological dual-process model, Boutyline and Soter conclude that the “application of existing knowledge to new domains understood as a feature of effortful, controlled cognition” (750).

Boutyline and Souter’s compelling argument does pose a dilemma and a puzzle. The dilemma is that a really attractive theoretical property of schemas (for Bourdieu, Sewell, and the many, many people who have used their insights and been influenced by their formulation) was transposability. Without it, it seems like schemas become a much diminished and less helpful concept. The puzzle is that there are many historical and contemporary examples of empirical instances of what looks like schematic transposition. How does this happen?

Here, Boutyline and Soter provide a very elegant theoretical solution, drawing on recent work suggesting that culture can “travel” within persons across the declarative/nondeclarative divide via redescription processes and across the public/personal one via internalization/externalization processes. They note that because schemas are representational, they can be externalized (or representationally redescribed) into explicit formats (from nondeclarative to declarative). People can also internalize them from the public domain when they interact in the world (from public to personal/nondeclarative; see Arseniev-Koehler and Foster, 2020). As Boutyline and Soter note, representational redescription,

…could make the representational contents of a cultural schema available to effortful conscious cognition, which we suspect may be generally necessary to translate these representations to novel domains. After they are transformed to encompass new settings, the representational contents could then travel the reverse pathway, becoming routinized through repeated application into automatic cognition. The end product of this process would be a cultural schema that largely resembles the original schema but now applies to a broader set of domains. Representational redescription may thus be key to social reproduction, wherein familiar social arrangements backed by widely shared cultural schemas…are adapted so they may continue under new circumstances (751).

Does cognitive neuroscience’s current state of the art support the idea that consciousness is required to integrate elements from multiple experiential and cultural domains? The answer seems to be a qualified “yes,” with the strongest proponents suggesting that the very function of consciousness and explicit processing is cross-domain information integration (Tononi, 2008). A more plausible weaker hypothesis is that consciousness greatly facilitates such integration. Without it, the task would be challenging, and for complex settings such as the socio-cultural domains of interest to sociologists, perhaps impossible. As noted by the philosophers Nicholas Shea and Chris Frith,

The role of consciousness in facilitating information integration can be seen in several paradigms in which local regularities are registered unconsciously, but global regularities are only detected when stimuli are consciously represented…consciousness makes representations available to a wider range of processing, and processing that occurs over conscious representations takes a potentially wider range of representations as input (2016, p. 4).

This account supports Boutyline and Soter’s insightful observation that it was an initial mistake to link the property of transposability to schemas, especially in the initial formulation by Bourdieu, where schemas were seen as part of habitus (Vaisey, 2009). Therefore, schemas reside in the implicit mind and operate as automatic Type I cognition (Sewell was more ambiguous in this last respect). Work in cognitive psychology and the cognitive neuroscience of consciousness supports the idea that transposition requires information integration across domains. For complex domains, conscious representation and deliberate processing may be necessary for the initial stages of transposition (Shea & Frith, 2016). Of course, as Boutyline and Souter note, once institutional entrepreneurs have engaged in the first bout of transposition mediated by explicit representations, the new schema-domain linkage can be learned by others via proceduralization and enskilment, becoming part of implicit personal culture operating as Type I cognition.

Finally, a corollary of the preceding is that we may not want to follow Sewell in completely collapsing the general concept of agency into the more restricted idea of schematic transposition, as this would have the untoward consequence of reducing agency to conscious representations and system II processing over these, precisely the thing that practice and habit theories were designed to prevent. 

References

Arseniev-Koehler, A., & Foster, J. G. (2020). Machine learning as a model for cultural learning: Teaching an algorithm what it means to be fat. In arXiv [cs.CY]. arXiv. https://doi.org/10.31235/osf.io/c9yj3

Bourdieu, P. (1990). The logic of practice (R. Nice, trans.). Stanford University Press. (Original work published 1980)

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 Review86(4), 728–758.

Joas, H. (1996). The Creativity of Action. University of Chicago Press.

Karmiloff-Smith, A. (1995). Beyond Modularity: A Developmental Perspective on Cognitive Science. MIT Press.

Lizardo, O. (2004). The Cognitive Origins of Bourdieu’s Habitus. Journal for the Theory of Social Behavior34(4), 375–401.

Sewell, W. H., Jr. (1992). A Theory of Structure: Duality, Agency, and Transformation. The American Journal of Sociology98(1), 1–29.

Shea, N., & Frith, C. D. (2016). Dual-process theories and consciousness: the case for ‘Type Zero’cognition. Neuroscience of Consciousness2016(1).

Tononi, G. (2008). Consciousness as integrated information: a provisional manifesto. The Biological Bulletin215(3), 216-242.

Vaisey, S. (2009). Motivation and Justification: A Dual-Process Model of Culture in Action. American Journal of Sociology114(6), 1675–1715.

Beyond Cultural Clumps

Clumppity-Clump

Traditional approaches to the study of culture begin with “cultural clumps” and theorize from there. Like the devil, these clumps have been given many names throughout history. For instance, the unqualified use of the term “culture,” from Tylor’s famous definition onward, is usually meant to refer to such a mega clump. But others also use the term “system,” “pattern,” “worldview,” “national character,” and the like to refer to their favorite clump. The only difference is that sometimes the clumps are homogeneous (where the agglomerated parts are all the same kind, such as “beliefs,” or “symbols,”). Other times, as with Tylorian/Boasian definitions, the clumps are heterogeneous, including everything learned and made by people (e.g., “the cultural heritage”), whether mental or material (Bidney, 1968).

In previous posts, I have proposed a different approach: Rather than beginning with clumpy “culture concepts,” start your theorizing with cultural kinds, which are the component pieces out of which cultural clumps are made, not with the clumps. This makes the existence of cultural clumps into an empirical, not an analytic issue. It also shifts the analytic attention of cultural analysis to token examples of the kinds (e.g., a given belief, schema, practice, artifact). Following what is already standard practice in empirical work, we should study specific instances of cultural kinds (e.g., the belief in witches in seventeenth-century Salem), not (usually non-existent or spurious) cultural clumps.

The problems with the cultural clump approach are many and will not be rehearsed in detail here (see, e.g., Turner, 1994; Bourdieu, 1973). These include an ontologically incoherent holism, the unjustified projection of hard to establish (e.g., “downward”) causal power to such spurious cultural wholes, and the like. In this respect, the entire “culture concept” tradition has been an analytic failure to the extent that theorizing about holistic culture clumps (e.g., “systems,” “patterns,” worldviews,” and the like) was the point of departure rather than one possible endpoint. As noted before, most “culture concepts” are (usually doomed) packages of ontic claims not redeemable in any respectable sense. In this sense, “culture concepts” should be abandoned as a starting point for theorizing cultural analysis. Instead, we should stick to studying the actual things that we are interested in. Those things are cultural kinds, not culture concepts. Of course, we can always define the kinds if we like, but we could just point to them if we are stumped.

Does this mean that clumps do not exist? Of course not. Cultural kinds do have the dispositional capacity to come together into clumps. However, none of these clumps will ever be so gigantic as to meet the criteria of the “worldviews,” and “Weltanschauungen” of the old culture clump approach (e.g., encompassing populations in the thousands or millions). Although specific token kinds (e.g., the daily practice of salah among Muslims) can and do reach these distributional scales (Anderson, 1991). So cultural analysts in the social sciences do study clumps. Still, likely, such clumps will seldom go beyond the scale of the “mesolevel” (Rinaldo & Guhin, 2019). Most will be downright “micro” (Fine, 1979). Just like socialism, really existing cultural clumps are smaller, less powerful, and less all-pervasive than previously thought, but that also means we can study them.

So, what are the different clumps? We can proceed to typologize the relevant kinds of clumps we are likely to encounter using our previous typology of cultural kinds. For instance, when it comes to the culture people can internalize, we can distinguish between declarative sentence-sized beliefs people can assent to (e.g., “in America, everyone can make it if they work hard enough”), and nondeclarative practices or skills. So, that means that ideally, there should be at least two types of culture clumps. Clumps made up of various pieces of “knowledge-that,” and clumps made up of multiple pieces of “knowledge-how.”

Belief Systems

The first kind of culture clump, belief systems made from propositions meshed into webs of implication, is a classic of cultural analysis (Archer, 1995). In fact, it may be the uber clump (e.g., the “prototypical” culture clump) having played a central role in some of the most influential (e.g., functionalist) lines of cultural theory in the mid-twentieth century. For instance, the idea of a belief system, still popular in both sociology and political science, is the culture-clump that emerges when various pieces of knowledge-that come to be linked together.

Today, the folk (and some analytic) conceptions of culture are based on the belief system imagery. So, when we say, “in this culture,” things are done this way or that, we mean something like “within the ambit of this particular belief system shared by these people here.” Other lines of cultural analysis reject sentence-like beliefs as the units and go for “word-sized” concepts instead, but retain the basic holistic culture clump imagery. For instance, Sausserian approaches to “symbol systems,” (e.g., Leach, 1976) conceive of culture as a set of semiotic elements (words, concepts) linked together by webs of semantic relations (e.g., antonymy, synonymy, hyponymy, and the like). So if a semiotic “cultural logic” reigns over a given collective (e.g., the American code of civil society), it is presumed to be coherent, shared, and the like, at scale.

As Turner (1994) has noted, there is also an entire tradition of cultural analysis positing various types of clumps (e.g., worldviews and the like), seemingly made up of interlinked sets of “assumptions” and “presuppositions,” except that they live in some (incoherent) “implicit” or “tacit” compartment of the collective mind. As I’ve argued before, this is also a non-starter. So, the whole “collective-presuppositional” tradition of analysis is just another version of the belief-system-style culture clump (but with even more extravagant and indefensible ontic claims), as are some lines of Weberian interpretation that rely on the “world image” concept (Strand & Lizardo, 2015).

Overall, it is unlikely that you are talking about anything if you are talking about any of these clumps. Empirical studies of belief systems in sociology, political science, and the cognitive science of religion show that consistent belief systems are scarce and hard to maintain. If they exist, it is not at the scale imagined by traditional culture clump theory. Instead, pristine, elaborate, and well-connected belief systems tend to exist among numerical minorities. These are usually motivated experts who have a lot of time and energy to invest in maintaining and making explicit all the logical links, expunging contradictions, and the like (e.g., in the Conversian tradition in political science, these are political elites, and in religious studies, these are religious professionals; in most empirical studies of “cultural logics” these are also shared within the ambit of particular professions like journalists). At the folk level, belief systems are fragmented and inconsistent, with any linkages (to the extent they exist) due not to deductive logic but to non-rational or a-rational factors like political identity, heuristics, or ingroup/outgroup dynamics (Boutyline & Vaisey, 2017). This frees up (survey, interview) researchers to just study the cultural kinds (e.g., the specific beliefs or attitudes) themselves à la carte without buying them wholesale as necessarily coherent sets of belief systems (e.g., Kiley & Vaisey, 2020; Vaisey & Lizardo, 2016).

Habitus

But what about clumps made of nondeclarative pieces of know-how? This kind of clump has not had as storied a career in cultural analysis as the belief system type. In fact, only one prominent theorist has argued for the existence of this type of clump. I refer to Bourdieu’s concept of habitus, which, as initially defined, was indeed proposed as a culture clump (Bourdieu, 1990). However, Bourdieu was self-consciously reacting against the anthropological versions of the clumps discussed earlier (both in its belief-systems functionalist form and its semiotic system Sausserian/Levi-Straussian forms). As an alternative, Bourdieu proposed a culture clump made of a different kind of cultural kind. Not sentence-sized beliefs or word-sized symbols, but action-sized pieces of bodily know-how, nondeclarative skills, and abilities linked together to form a clump-like system he called habitus; the culture clump everyone loves to hate.

There is some confusion whether the habitus is a culture clump at all because Bourdieu was so adamant about distinguishing his clump from the anthropologists’ clumps that he suggested that the habitus had nothing to do with the “culture concept” because he equated that to clumps made of beliefs and symbols (Lizardo, 2011). Today we are smart enough to recognize that practices, skills, and the like are bona fide cultural kinds (Reckwitz, 2002), so we can qualify Bourdieu’s proposal. Habitus is a culture clump, it is just a clump whose cultural components are habits, which is a bit counter-intuitive at first, but now we are used to it. However, as a culture clump, the habitus has all the defects and weaknesses of all culture clump concepts:

  1. It is a “holistic” concept, so people begin with the clump rather than study the kinds (e.g., the actual habits the habitus is made of).
  2. The concept takes the clumping for granted instead of giving us a story of where the clump from comes in the first place (habits are assumed to be clumped into a system ex ante).
  3. The clump is applied so that its scale ends up being way more extensive than the clump can credibly handle (so that entire classes and even nations (!!!) have a “habitus“).

Predictably, post-Bourdieusian theorists have just “deconstructed the clump,” pointing out that the habitus (within people) can be cleft, split, fragmented, clivé, and the like; in addition, across people, collectives seldom share a homogeneous habitus, with diversity in habits within-groups and cross-cutting overlaps between-groups being the rule rather than the exception (Lahire, 2011). So, we are left with the pieces (this or that habit or skill) without having to force them into coherent systems where they fit together harmoniously. Theoretically, this is not as dramatic as discovery or theoretical advance as some claim, since “deconstructing the clump” is precisely the story of post-functionalist theory in sociology and anthropology (e.g., Swidler, 2001; Hannerz, 1992).

The recipe is easy. Suppose you give me a culture clump (regardless of what it is made of). In that case, it is easier to show out that it is fragmented, inconsistent, and the like than to show that it is a highly structured holistic entity. The reason for that is that proposing a clump exists is always a stronger claim than suggesting a given standalone component’s existence and causal efficacy. At the end of the post, I will provide you with one reason why.

For instance, the proposition “Americans hate welfare because they believe that with hard work they can make it,” is much easier to defend empirically than saying, “Americans hate welfare because they have imbibed an entire neoliberal ideology composed of hundreds of beliefs linked together by chains of logical implication, and their hating of welfare follows as a strict deduction from the high-level principles up in the chain.” Of course, trying to establish the empirical validity of this last is a hopeless undertaking. But the first hypothesis has a fighting chance. This hypothesis will moreover be consistent with the fact that the same person who hates welfare because they think that with hard work they can make it can also tell you in the next breath that they believe the game is rigged for the little guy like themselves by college professors and other elites, without their hating of welfare because they think that with hard work they can make it, being in the least impinged by the fact that college professors, whose median salary is way smaller than this person’s, are standing in the way of their dreams. 

Note that in this last respect, any “critical” theory of “ideology,” in which this last is just a giant culture clump composed of a bunch of interlinked beliefs, will fail for the same analytic reasons as vanilla functionalist culture clump theory. Thus, regardless of whether you are a happy functionalist who likes the existing state of affairs, or an angry Jacobin who would like the revolution tomorrow, if you live by the clump, you die by the clump.

Regardless, deconstructing the habitus clump has been empirically liberating because it has allowed researchers to just study how particular skills and abilities are acquired in a social context without having to worry about fitting those specific pieces of know-how into a larger habitus-like clump (e.g., Cornelissen, 2016). Ultimately, habitus is a failed concept not because it proposed the (still generative!) idea that pieces of know-how could (theoretically) come together to form soft-assembled systems, but because it took such systems for granted and began their theorizing from there. Just like post-functionalist theory, it is better to follow the post-Bourdieusian clump-deconstructors and point out that splitting, fragmentation, and the like is the norm and that if you end up finding some very coherent set of skills and abilities clumped together into a giant coherent habitus, then you better explain how that happened because that is the actual puzzle.

Clumps versus Entropy

Given the vicissitudes of both know-that clumps and know-how clumps, it seems like we can derive a general lesson for why culture clumps have struggled so much in the history of cultural theorizing. Overall, the moral of the story seems to be to not take clumps as pre-existing analytic entities, take their clumpiness (if it exists) as a puzzle to be explained, and assume that the “normal” state is not clumpiness but disorganization, such that the clumping of cultural kinds into anything resembling a coherent system becomes the explanatory puzzle.

The general proposal goes as follows. Begin with the kinds themselves (more accurately specific tokens thereof) and follow them into the field (or the RStudio interface) to see if they do indeed clump together with others of their kind (or with different kinds altogether!). What we don’t want to do is begin with clumps or “clump concepts” that allegedly tell you about the clumps and their mystical powers over people via ex-ante argumentation. The primary point is that, even if the cultural kinds you follow don’t end up assembling into clumps, you still have something to study. It is a fallacy to think that culture can only be causally powerful, Power Rangers style, only when assembled into giant clumps. Instead, token cultural kinds by themselves have causal powers; whether they come together into clumps is incidental. A single belief or habit can be causally powerful on its own (think of your Twitter habit) independently of whether it is part of a more extensive belief system, cultural logic, or habitus

From this, it follows that even if you were to find and describe a coherent culture clump located at an appropriate mesolevel (e.g., the habitus of French humanities Professors who live in Paris), you should probably also consider all the centripetal forces operating to fragment, split, or otherwise bring disorganization to the clump in question so that the various pieces of the clump go all in their different ways (Cornelissen, 2016).

This last set of considerations give us a clue as to why it is not a good idea to take clumps for granted. Borrowing a generative idea from the work of Terry McDonnell (2016), it is time cultural analysts place the kinds they study within the context of entropy. Things, including cultural things, tend toward disorder and disorganization. That means it is always cheaper to say “this belief exists,” or “some percentage of Americans believe this,” than to say “Americans are under the sway of an individualist ideology.” Following the logic of entropy, the latter would be probabilistically less likely because to keep together a pristine ideology in which the number of logical or inferential links increases exponentially in the number of elements, shared in a population of hundreds, thousands, or millions, just sounds utterly insane and improbable. Too many factors are working against it. People are learning and unlearning that, forgetting this, motivated-reasoning their way to this other thing (Sperber, 2011).

That means that pockets of coherence and clumpiness, where they exist, are deserving of study because there you will have both a causal genetic story to tell (how did this set of beliefs clump emerge from a disorganized collection of considerations?) and a synchronic entropy-negating story to tell (how is this belief maintained so that its clumpiness and organization persist?). Note that both questions also apply to habitus-style know-how clumps. Moreover, both questions play to the comparative strengths of sociological work, since we know that while a given individual may struggle to sustain a coherent belief system or a coherent habitus on their own, this becomes easier when embedded in fields endowed with institutional structures, authority figures, interpersonal relationships and the like (Rawlings, 2020).

Outside-in versus Inside-out (Again)

Here I want to reiterate that this outside-in story is not a general-purpose story of the causal power of culture. Instead, it is a special-purpose story of where cultural clumps (if they exist) might come from and what social mechanisms help sustain them (Sewell, 2005; Swidler, 2001). It has been an analytic mistake to sell these special-purpose outside-in stories as general substitutes for how “culture” (in general) works. The problem is that this over-generalization of the outside-in story takes away all causal power from internalized cultural kinds (Vaisey, 2008). As noted earlier, this is a fallacy; cultural kinds can be causally powerful on their own, so that a single belief, attitude, or nondeclarative disposition links to action (from the inside-out) without having to be part of a larger clump and without having to fit with or be consistent with the other cultural kinds the same person has internalized (Lizardo, 2017).

So whether “cultural kinds affect action,” is an entirely disjoint question from “what are the mechanisms by which cultural kinds come to form coherent clumps.” For the former, a pure outside-in story is an overreach; for the latter, it is an excellent place to start. As noted, there are now well-established, and long-running lines of work in cultural analysis showing that cultural kinds (specific beliefs, attitudes, or know-how) can affect action from the inside-out independently of their membership in clumps, so answering this question in the affirmative is not a negation of the idea that outside-in mechanisms might be essential for the formation and maintenance of entropy-defying culture clumps at micro and mesolevels.

However, questions remain. Are belief systems made of sentence-sized kinds and habituses made up action-sized habits the only culture clumps that exist? Are all culture clumps affected by entropic forces to the same extent? Do we need to postulate distinct mechanisms keeping the different clumps together? These will be the subject of future posts.

References

Anderson, B. (1991). Imagined Communities. 1983. rev. ed. London: Verso.

Archer, M. S. (1996). Culture and Agency: The Place of Culture in Social Theory. Cambridge University Press.

Bidney, D. (1968). Theoretical Anthropology. Transaction Publishers.

Bourdieu, P. (1973). The three forms of theoretical knowledge. Social Sciences Information. Information Sur Les Sciences Sociales12(1), 53–80.

Boutyline, A., & Vaisey, S. (2017). Belief Network Analysis: A Relational Approach to Understanding the Structure of Attitudes. The American Journal of Sociology122(5), 1371–1447.

Cornelissen, S. (2016). Turning distaste into taste: context-specific habitus and the practical congruity of culture. Theory and Society45(6), 501-529.

Fine, G. A. (1979). Small Groups and Culture Creation: The Idioculture of Little League Baseball Teams. American Sociological Review44(5), 733–745.

Hannerz, U. (1992). Cultural Complexity: Studies in the Social Organization of Meaning. Columbia University Press.

Kiley, K., & Vaisey, S. (2020). Measuring stability and change in personal culture using panel data. American Sociological Review85(3), 477-506.

Lahire, B. (2011). The Plural Actor. Polity.

Leach, E. (1976). Culture and communication: The logic by which symbols are connected. An introduction to the use of structuralist analysis in social anthropology. Cambridge University Press.

Lizardo, O. (2011). Pierre Bourdieu as a post-cultural theorist. Cultural Sociology5(1), 25-44.

Lizardo, O. (2017). Improving Cultural Analysis: Considering Personal Culture in its Declarative and Nondeclarative Modes. American Sociological Review82(1), 88–115.

McDonnell, T. E. (2016). Best Laid Plans: Cultural Entropy and the Unraveling of AIDS Media Campaigns. University of Chicago Press.

Rawlings, C. M. (2020). Cognitive Authority and the Constraint of Attitude Change in Groups. American Sociological Review85(6), 992-1021.

Rinaldo, R., & Guhin, J. (2019). How and Why Interviews Work: Ethnographic Interviews and Meso-level Public Culture. Sociological Methods & Research. https://doi.org/10.1177/0049124119882471

Sewell, W. H., Jr. (2005). The concept (s) of culture. In G. M. Spiegel (Ed.), Practicing History: New Directions in Historical Writing After the Linguistic Turn (pp. 76–95). Routledge.

Sperber, D. (2011). A naturalistic ontology for mechanistic explanations in the social sciences. In P. Demeulenaere (Ed.), Analytical sociology and social mechanisms (pp. 64–77). Cambridge University Press.

Swidler, A. (2001). Talk of love: How culture matters. University of Chicago Press.

Turner, S. P. (1994). The Social Theory of Practices: Tradition, Tacit Knowledge, and Presuppositions. University of Chicago Press.

Vaisey, S. (2008). Socrates, Skinner, and Aristotle: Three Ways of Thinking About Culture in Action. Sociological Forum23(3), 603–613.

Vaisey, S., & Lizardo, O. (2016). Cultural fragmentation or acquired dispositions? A new approach to accounting for patterns of cultural change. Socius2, 2378023116669726.

 

Sociology’s Motivation Problem (Part II)

In a previous post, we outlined the three critical mistakes sociologists make in theorizing about motivation. We referred to them as the mono-motivational, social-psychological, and list-making fallacies. In this post, we briefly summarize each fallacy. We follow with a more extended discussion on how recent interdisciplinary work in social, cognitive, affective, and motivational neuroscience can provide new analytic tools to move the sociological theory of motivation forward while preventing falling into theoretical cul-de-sac previous work fell into. 

Mono-Motivations

The first refers to the sociological penchant to attribute a single “master” motivation to people. Sociologists and social psychologists naturally prefer that this master motivation is of the social kind and that people are primarily driven by social motivations. These range from the usual functionalist penchant to say that people are motivated to conform to the norms imposed by the society that Wrong (1963) castigated, to the Mills-inspired approach that both denies “motivations” exist as motor-springs of action, while simultaneously assuming people are motivated to produce “accounts” of their actions conforming to cultural expectations. Another version of the mono-motivational story links up to the social psychology of “need states.” In this approach, people have an “uber” motivation to “belong” to groups, form strong social ties, and the like (Baumeister and Leary 1995). A special case is “dual” motivation stories in which two “uber” motivations, one social and one anti-social, or one social and one “instrumental,” fight out for supremacy in an endless Manichean struggle (Durkheim 2005; Freud 1989; Kadushin 2002).

Drive-Reduction

The second fallacy is a more general version of this last point. This idea—central to most social and personality psychology work since the early 20th century—argues motivation can be understood as a process by which unmet needs or drives generate an unpleasant state, which people are then motivated to “reduce” or “eliminate.” This general “drive-reduction” model was first developed in behaviorist animal psychology but then generalized to the study of human motivation with the development of “control models” of human behavior after the 1950s (Carver and Scheier 1998; Heise 1977; Powers 1973). The control model imagery provides the ideal formal specification of the drive-reduction model. In this imagery, people can be thought of as “human thermostats.” A “drive” or an unmet “need” (e.g., being lonely) is a deviation from the setpoint (e.g., belongingness). Finally, human motivation is geared toward re-establishing the previous balance (finding some company)–e.g., modern affect and identity control models in social psychology (Burke and Stets 2009; Smith-Lovin and Heise 1988) are built on these foundations. Note that social-psychological control models are also mono-motivational models. They postulate a single abstract motivation (e.g., reduction of “deflection” or identity verification). Most research shows how their motivation (and method of appraising its veracity) is primary to other research programs’ motivation (Burke and Stets 1999). The social psychology behind structuration theory, ethnomethodology, and some versions of social construction, in which people are motivated to re-establish ontological security, facticity, cognitive order, and the like when threatened, also rely on the same underlying imagery (Fararo 2001). 

List-Making

Finally, we noted that multi-motivational (list) models move beyond some drawbacks of mono-motivational and drive-reduction models. The most sophisticated one, developed in sociology by Jonathan Turner (2010), poses the interplay of a multiplicity of motivations operating in every face-to-face encounter. Motivations range from the cognitive to the affective to the instrumental. However, while the multidimensional aspect of Turner’s approach is appreciated, it does inherit some weaknesses of the drive-reduction and control models that it draws upon. One problem is that the “list” of motivations, regardless of how “fundamental” the analyst thinks these are, comes from pre-existing theory, which means it is unlikely that those lists will exhaustively cover all the sources of motivated action. The lists are inherently limited and occlude both the particularity of motivation, the open-ended nature of the objects of motivation, and the situated nature of most motivated action. The other problem with Turner’s model, shared by most social-psychological models, is the assumption that people are motivated to contain or reduce abstract need states. Under this imagery, both the dynamics of motivation and the end states (usually psychological) that people pursue in motivated action are internal. The actual object people are motivated to seek drops out of the picture altogether. 

Overall, we think that the search for “fundamental” motivations, whether of the omnipotent or additive variety, is a red-herring. People are motivated by many things, and it is unlikely that this will fall into analytically neat “fundamental” types. Moreover, what is fundamental for one person, can be peripheral for another because “fundamentality” is determined by a history of learning and accumulating rewarding and non-rewarding experiences with specific objects (and by the psychological and biological potential to constitute them as rewards). Another limitation of conventional approaches is that most motivation is reactive rather than proactive. People are not motivated to act until their needs for facticity are threatened, or their identities fail to be verified, or they end up getting the short end of the deal in exchange. In a strange sense, sociologists have elevated the avoidance or, more typically, removing pain at the expense of the pursuit or enjoyment of pleasure. By relying on removing or avoiding pain and focusing on externalities only, the sociology of motivation fails the fundamental question of why one person pursues one thing and another person other things, even when faced with similar environmental prompts (Kringelbach and Berridge 2016). In short, what is missing from the social psychology of motivation is both a way to theorize the specific pursuit of particular objects, activities and events and an account of motivated action that puts motivation first — that is, in which motivated action emerges pro-actively rather than re-actively. 

Moving Beyond the Fallacies

Beyond Mono-Motivations

Moving beyond mono-motivations is the easiest. “Typing” motivations at an abstract level does not get us very far in this endeavor (Martin and Lembo 2020), so the best fix is just to acknowledge both the diversity and the specificity of motivators, so we don’t fall into the penchant to say that people are motivated to pursue psychological abstractions (like “ontological security” or “belongingness”), let alone a single one of these. Put differently, people are motivated to pursue a multiplicity of objects and lines of action, and the candidate “motivators” are massively diverse. Some are social, some are pro-social, some are anti-social, some are egoistic, others altruistic, and, yes, some are psychological. A good rule of thumb is that if you cannot tell us what people are motivated by — where “what” has to be a concrete object, event, or experience (e.g., that I get tenure) — then you need to move down the “ladder of abstraction” and tell us precisely what you think people are pursuing (Sartori 1984).

The same goes for the crypto-mono-motivational approach inspired by Mills, where people are master-motivated to produce “accounts” of their actions. Sometimes people may be motivated to do this; other times, they are not. The essential analytic point is that we need to separate motive or motivation talk from motivation proper. To foreshadow, motivation has everything to do with objects and rewards and nothing to do with justifications. This is not difficult to imagine. In quantitative research, in particular, but also retrospective and historical qualitative research, motive talk may be the only data available. Understanding the normative frames or motivation schemata actors use to interpret their behavior remains a relevant and essential subject of study (Franzese 2013; Hewitt 2013). Nevertheless, we should not assume post hoc accounts are causal or even verge on tapping into causally relevant factors. 

Beyond Drive-Reduction

However, we have seen that you can conquer the mono-motivational monster while remaining trapped by the constraint of the dominant model of motivation in social psychology — the drive to reduce discomfort, pain, and the like. For instance, if I think meaning maintenance is such a need, when people experience hard to interpret events (e.g., a mother killing her child), then I can posit that they are motivated to reduce the uncomfortable state of deflection this event has produced. There is no question that some motivational processes are of this (reactive) sort. However, taking this as the paradigm for motivation is an analytic mistake. Most motivated action is the proactive pursuit of specific objects, events, persons, or states of affairs; it is, by definition, intentional, guided, and controlled (Miller Tate 2019). The initiation of motivated action need-not (and usually is not) preceded by a “need” state. Instead, it is preceded by an event that activates a memory of the desired object. Later, by a plan (which could also be stored in long-term memory as a habit if repeatedly rehearsed before) that provides a flexible behavioral template for the person to pursue it. 

But what makes objects desired or desirable? This is a question for which contemporary motivational neuroscience’s answer is deceptively simple, but, we think, extraordinarily generative. Objects become the object of motivation when they are constituted as rewards (Schroeder, 2004). Objects are constituted as rewards when, after seeking them out, they lead to satisfying (e.g., pleasurable) experiences in a given context. This is followed by a learning process (reinforcement) in which we bind the experienced qualities of the object to the pleasurable experience while also storing for future use the extent to which the positive experience matches, exceeds, or falls short of the pleasure we predicted we were going to get (where “prediction” can be both implicit or explicit). In this way, objects go, via repeated travels through this cycle, from being “neutral” (non-motivating) to being capable of triggering motivated action (we start “wanting” the object spontaneously or without much effort). 

An object with the capacity to lead to motivated action following positive consummatory experiences is thus constituted (construed, categorized) as a reward in future encounters so that the object begins to function as a salient incentive. We can then speak of the object as being represented (by that person) as a reward, with reward-representations leading to motivated action once they are activated (either by the environment or by the person) on future occasions (Schroeder 2004; Winkielman and Berridge 2003). 

The basic lesson here is that only objects constituted as rewards have the causal power to energize action. Abstract “need-states,” uncomfortable drives, experiences of “deflection,” or “lack of meaning,” “ennui,” “ontological (in)security,” or “loneliness,” are not objects. Therefore, they cannot be constituted as rewards. By implication, they cannot count as causes energizing people to act. However, an apple, a glass of water, a beer, hanging out with your best friend, molly, reaching the solution to a challenging crossword puzzle, publishing a paper, getting released from prison, earning praise from your advisor, cocaine, getting a bunch of Twitter likes, and a zillion others (the list is open-ended) are objects (e.g., they are either things or events). Therefore, they can all be constituted—under the right circumstances, by particular people—as rewards. By implication, they count as causes that energize people to act. 

If you are still mourning the death of homeostatic or drive reduction theories of motivation, think of the last time you stuffed yourself with chocolate lava cake after a hearty dinner. You sure weren’t hungry any longer (thus, there was no “drive” to “reduce”). You probably were beyond your set point for satiation (so the “error” was probably going in the wrong direction. However, you still ate the cake because you either had looked forward to dessert from the start, the cake itself looked delicious; or, even more likely, you might have eaten the cake although the “hedonic impact” (the pleasure experience) was actually much more muted than you thought. All rewards (psychological, social, and the like) work like that (Berridge 2004, 2018). 

Beyond Fundamental Motives

 From the perspective of modern motivational science, we can think of standard fundamental motivation theories as incompletely articulated models of motivation. Thus, people are not motivated to attain abstract states (e.g., trust or predictability) qua external states. The hidden scope condition here is that as long as trust and predictability lead to psychologically rewarding objects, people will be motivated to try to organize their external environment such that those states obtain. Making explicit this scope condition also shows the futility of delving for “universal” motives of this kind. Thus, it is fair to suggest people will be motivated to try to live in trusting and predictable worlds, but there is nothing necessary about this; if trust and predictability fail to be psychologically rewarding, then people will not be motivated to pursue these external conditions. 

For instance, people high on the personality trait usually labeled “openness to experience,” find (moderately) unpredictable environments psychologically rewarding and overly predictable environments non-rewarding. As such, these people will be driven to pursue lines of action that do not conform to the idea of “ontological security” as a general motivator. Jumping from planes, hanging out with grizzly bears, or diving around lethal ocean life, none of which are conducive to ontological (or physical) security, can be constituted as rewards by some people. In that case, people will be motivated to seek out these lines of action. The analytic mistake here is to think of the (usually) rewarding line of action as the “motivation,” when in fact it is the (contingent, not necessary) link between the external state and the internal reward (the real motivator) that makes the former a condition to be striven for. 

In the same way, it is essential to not assume that just because something “sounds good,” from the armchair, that it will be a universal motivator. Take, for instance, the oft-discussed case of “belongingness.” It might seem redundant and unnecessary to specify that social ties or group belonging can be constituted as psychological rewards (Baumeister and Leary 1995; Kadushin 2002). But if the full extent of human variation is considered, it is easy to see that they may not be. For instance, recent work in the neuropsychology of autism and the autism-spectrum shows (Carré et al. 2015; Supekar et al. 2018) there is a portion (how large remains unclear) of the population for whom interpersonal relations are either less rewarding or non-rewarding (compared to tangible rewards (Gale, Eikeseth, and Klintwall 2019)), and a smaller proportion for whom they might actually be aversive (so it is the avoidance or cessation of belonging or connection that actually counts as a reward). Interpersonal relationships are generally rewarding for “neurotypical” people because a (developmental, genetic, epigenetic) mechanism has made them so. If this mechanism is either disrupted by, for instance, brain injury or the onset of mental illness (or is non-existent from early on during development as with autistic individuals), then belongingness ceases to be a “fundamental” motivation. 

Throwing Out the Lists

In this last respect, many of the criticisms of fundamental motivations apply to the list-makers. Because of the contingent link between external state (e.g., trust, security, belonging) and reward, it is unlikely that any of the other so-called “fundamental motivations,” that have been proposed in psychology and sociology (e.g., need for “power,” “influence,” “status,” “altruism,” “trust,” and the like) by people who like to write down “lists” of motives are fundamental. This is especially the case for “fundamental” motives theorized as “needs for” some concrete state of affairs. Thus, all of these candidate motives will fail Baumeister and Leary’s criterion of being “universal in the sense of applying to all people” (p. 498). Instead, most of the motives appearing in these sorts of lists and proposals can be best thought of as states, processes, and external conditions commonly (in the probabilistic sense) linked to objects typically constituted as rewards and thus likely to be pursued by most (but not all) people. Diversity, both in terms of “neurodiversity” and diversity of experience and learning history, and institutional location and historical context is the rule rather than the exception. 

Turner’s (2010) list inherits this weakness. Still, it stands out because it does not seek an exhaustive list of drives we have—mostly because he accepts the underlying homeostatic control model seeing a finite number of needs being salient in micro-interaction and because he does not prioritize the items on the list. On the one hand, this is commendable. It adds flexibility to the social scientist: we could add more things to the list as identity verification, trust, facticity, reciprocal fairness, and belongingness are not the only things that might matter. Furthermore, this flexibility does not negate the utility of his list because he does locate the motivational forces, even if he does not specify their neurobiological foundations, inside our heads and bodies. On the other hand, because Turner’s list seeks to contextualize psychological needs within a larger constellation of nested social spaces, it cannot explain a wide array of behaviors that fall outside the interaction or encounter unit in which his microsociology situates itself. Drug or food addiction goes unexplained, as do situations between two or more people who are not motivated by, say, trust, but get along just fine, and so does the ability to make sense of why some scientists pursue celebrity status at all costs while others operate within the rules of their professional field.

From Fundamental “Motivations” to Fundamental Motivational Processes

Ultimately, lists or not, drive-states or not, the fundamental weakness in sociological theories of motivation is the omission of reward and, importantly, the neurophysiological connections between reward/object/schema work. This is perhaps the most controversial thing we can posit to sociologists, given their aversion to intrapersonal dynamics and to any hint at reductionism. But, despite our best efforts to resist over-psychologization and over-economization, sociology’s candidates for motivation continue to psychologize and economize (and, worse, oversocialize), but with very little connection to empirical research on the mechanics of motivation or reflective thought on what, why, and how people are actually compelled to do things. Rewards, then, are central to the explanatory story (Kringelbach and Berridge 2016). Controversial as it may be, it is the best path forward for exercising sociology of the (explicit and implicit) vestiges of a long-standing and venerable tradition, in which analysts sit at their desks trying to come up with the one, or for more modest cogitators, the definitive top list of, motivation and motivations, respectively. Incorporating control-theoretic versions of early twentieth-century homeostatic models or philosophical speculation about “ontological security” did not help matters in this particular regard.

Luckily for us, contemporary work in affective, cognitive, and motivational neuroscience (and increasingly the overlap of these fields with social neuroscience and social and personality psychology) suggests a fundamental theoretical reorientation in the way we think of motivation in broader social and human sciences. Thus, instead of “fundamental motivations,” we propose that the focus should move to the study of fundamental motivational processes, with the understanding that there is a massive (perhaps non-enumerable) set of objects that could count as “motivators.” 

What are these processes? In the earlier discussion, we have made reference to a few of them. Note, for instance, that in the cycle leading objects to be constituted as rewards, there is a seeking phase where we engage in (flexible—either habitual or intentional) motivated activity to attain the object and a consummatory phase—where we enjoy the object. There is also a post-consummation (or satiatory) phase, where we store linkages between the pleasure experienced (if any) to update the “reward status” of the object and where we compare what we thought we were going to get to what we got. Using folk psychological labels for these phases of motivation, we can say that the fundamental motivational processes leading objects to be constituted as rewards are wanting (seeking), liking, and learning. Thus, pleasure is an aspect or “phase” (to use Dewey’s locution) of motivated action, not the whole of it. 

In short, it is this cycle (and, as we will see in a follow-up post, each phase’s neurobiological dissociability), our ability to anticipate — right or wrongly — rewarding experiences with an object (or set of similarly classed objects), and the actual reward itself that constitutes a theory of motivation or motivational processes. Any object can come to intentionally guide and control our motor impulses or become a source of habitually motivated activity. In a follow-up post, we will discuss these fundamental motivational processes, how they are linked together—and most importantly, how they come apart—and the more significant implications the reward-focused approach has for the study of motivated action in institutional settings. 

References

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Berridge, Kent C. 2004. “Motivation Concepts in Behavioral Neuroscience.” Physiology & Behavior 81(2):179–209.

Berridge, Kent C. 2018. “Evolving Concepts of Emotion and Motivation.” Frontiers in Psychology 9:1647.

Burke, Peter J., and Jan E. Stets. 1999. “Trust and Commitment through Self-Verification.” Social Psychology Quarterly 62(4):347–66.

Burke, Peter J., and Jan E. Stets. 2009. Identity Theory. Oxford: Oxford University Press.

Carré, Arnaud, Coralie Chevallier, Laurence Robel, Caroline Barry, Anne-Solène Maria, Lydia Pouga, Anne Philippe, François Pinabel, and Sylvie Berthoz. 2015. “Tracking Social Motivation Systems Deficits: The Affective Neuroscience View of Autism.” Journal of Autism and Developmental Disorders 45(10):3351–63.

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Durkheim, Emile. 2005. “The Dualism of Human Nature and Its Social Conditions.” Durkheimian Studies 11(1). doi: 10.3167/175223005783472211.

Fararo, Thomas J. 2001. Social Action Systems: Foundation and Synthesis in Sociological Theory. Greenwood Publishing Group.

Franzese, Alexis T. 2013. “Motivation, Motives, and Individual Agency.” Pp. 281–318 in Handbook of Social Psychology, edited by J. DeLamater and A. Ward. Dordrecht: Springer Netherlands.

Freud, Sigmund. 1989. The Ego and the Id. WW Norton & Company.

Gale, Catherine M., Svein Eikeseth, and Lars Klintwall. 2019. “Children with Autism Show Atypical Preference for Non-Social Stimuli.” Scientific Reports 9(1):10355.

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Hewitt, John P. 2013. “Dramaturgy and Motivation: Motive Talk, Accounts, and Disclaimers.” Pp. 109–36 in The Drama of Social Life: A Dramaturgical Handbook, edited by C. Edgley. New York: Routledge.

Kadushin, Charles. 2002. “The Motivational Foundation of Social Networks.” Social Networks 24(1):77–91.

Kringelbach, Morten L., and Kent C. Berridge. 2016. “Neuroscience of Reward, Motivation, and Drive.” Pp. 23–35 in Recent Developments in Neuroscience Research on Human Motivation. Vol. 19, Advances in Motivation and Achievement. Emerald Group Publishing Limited.

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Supekar, Kaustubh, John Kochalka, Marie Schaer, Holly Wakeman, Shaozheng Qin, Aarthi Padmanabhan, and Vinod Menon. 2018. “Deficits in Mesolimbic Reward Pathway Underlie Social Interaction Impairments in Children with Autism.” Brain: A Journal of Neurology 141(9):2795–2805.

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Winkielman, Piotr, and Kent Berridge. 2003. “Irrational Wanting and Subrational Liking: How Rudimentary Motivational and Affective Processes Shape Preferences and Choices.” Political Psychology 24(4):657–80.

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A Sociology of “Thinking Dispositions”

In a recent interview about his life and career, the Nobel Prize-winning psychologist and economist Daniel Kahneman said two particularly interesting things. First, he said much of his current work is focused on individual differences in what he refers to as “System 1” and “System 2” thinking. He discussed his fascination with the Cognitive Reflection Test (CRT), which includes the famous “bat and ball problem”:

A bat and a ball cost $1.10 in total. The bat costs $1.00 more than the ball. How much does the ball cost? _____ cents.

What makes this a great question is that it has an intuitive (but wrong) answer that immediately comes to mind (10 cents), and a correct answer (5 cents) that requires you to override that initial intuition and think deliberately to attain it. Some people read this question and simply “go with their gut,” while others take time and think more carefully about it. Kahneman says that what makes this so interesting is that people who are certainly intelligent enough to obtain the correct answer (like students at Harvard) get this wrong all the time and that it predicts important things, including belief in conspiracy theories and receptivity to pseudo-profound “bullshit” (see Pennycook et al., 2015; Rizeq et al., 2020).

     As Shane Frederick (a post-doctoral student of Kahneman’s, who developed the measure) proposed, the CRT measures ““cognitive reflection”—the ability or disposition to resist reporting the response that first comes to mind.” (2005:35). The CRT is one of several measures of what psychologists refer to as “thinking dispositions” or “cognitive styles,” general differences in the propensity to use Type 2 processing to regulate responses primed by Type 1 processing. People with more reflective or analytical thinking dispositions are more careful, thorough, and effortful thinkers, while those with more intuitive or experiential thinking dispositions are more likely to “go with their gut” and trust in their initial responses (Cacioppo et al. 1996; Epstein et al. 1996; Pennycook et al. 2012; Stanovich 2009, 2011).

The second interesting thing Kahneman discussed was his omission of the work of the late psychologist Seymour Epstein. In the early 1970’s, when Kahneman and Amos Tversky started publishing their work on heuristics and biases, Epstein was developing his “cognitive-experiential self theory”: a dual-process theory that proposed that people process information through either a rational-analytical system or an intuitive-experiential system. Apparently, Epstein was upset that Kahneman had failed to recognize his work, even in his popular book Thinking Fast and Slow (2011). Kahneman said that he regretted not engaging with his ideas because they were directly relevant to his work on System 1 and System 2 thinking.

Individual Differences in Thinking Dispositions

What neither Kahneman nor the interviewer seemed to recognize is that Kahneman’s recent interest in individual differences in dual-process cognition and his omission of Epstein’s work are in some ways interrelated. Arguably, Kahneman is quite late to the “individual-differences” party. Psychologists have been using measures of thinking dispositions for many years; they have already been established as a workhorse for research in social and cognitive psychology and proven invaluable for explaining pressing issues, including the susceptibility to fake news, the acceptance of scientific evidence, and beliefs and behaviors around COVID-19 (Erceg et al., 2020; Fuhrer and Cova, 2020; Pennycook et al., 2020; Pennycook and Rand, 2019). However, if he had followed Epstein’s work more closely, he likely would have gotten to these individual differences much sooner in his career. Almost a decade before the validation of the CRT, Epstein and his colleagues (1996) developed the popular Rational-Experiential Inventory (REI), a self-report measure of differences in intuitive and analytical thinking.

If Kahneman is late to the party, sociologists do not even seem to know or care about it. Cultural sociologists have been engaging with dual-process models for years, and this scholarship has been highly generative (e.g., DiMaggio, 1997; Lizardo et al., 2016; Vaisey, 2009). However, this work is almost always accompanied by claims about how cognition operates in general. For example, in DiMaggio`s (1997) agenda-setting “Culture and Cognition,” he asserted that due to its inefficiency, deliberate cognition was “necessarily rare” (1997: 271). Similarly, Vaisey (2009:1683) argued that “practical consciousness” is “usually in charge” (2009: 1683). Conversely, those who argue against these works draw on “social psychologically oriented models that assume greater reflexivity on the part of social actors” (Hitlin and Kirkpatrick-Johnson, 2015: 1434) or suggest that “findings from cognitive neuroscience suggest that this model places too much emphasis on the effects of subconscious systems on decision-making” (Vila-Henninger, 2015: 247). These claims presuppose a general, “one-size fits all” model of social actors and the workings of human cognition.

At some level, the lack of consideration for individual differences in sociological work on dual-process cognition is entirely understandable. The term “individual differences,” closely associated with psychological research on intelligence and personality, certainly sounds “non-sociological.” Accordingly, it is not likely to inspire much faith or curiosity from sociologists, similar to the way they might turn their nose up at psychological research about “choice” and “decision-making” (Vaisey and Valentino, 2018). However, these individual differences exist, and therefore sociological models of culture, cognition, and action may be missing something important by not accounting for this individual variability. Furthermore, there is good reason to think that these “individual” differences are actually socially patterned.   

Thinking Dispositions in Sociological Work

We can go back to the classics to find concepts that approximate thinking dispositions and propositions about how and why they are socially patterned. Georg Simmel argued that the psychological conditions of the metropolis (e.g., constant sensory stimulation, the money economy) produce citizens that (dispositionally and habitually) react “with [their] head instead of [their] heart” (2012[1905]: 25) – a more conscious, intellectual, rational, and calculating mode of thought. Relatedly, John Dewey (2002[1922], 1933) wrote about a “habit of reflection” or a “reflective disposition” born out of education and social customs. 

We can also find this line of thinking in more contemporary works. Pierre Bourdieu (2000) argued that the conditions of the skholè foster a “scholastic disposition” characterized by scholastic reasoning or hypothetical thinking. Annette Lareau’s (2011) account of “concerted cultivation” found that wealthier families aimed to stimulate and encourage their children’s rational thinking and deliberate information processing to develop their “cognitive skills.” Critical realists aiming to hybridize habitus and reflexivity have argued that certain conditions (e.g., late-modernity, socialization that emphasizes contemplation) produce habiti in which reflexivity itself becomes dispositional – a reflexive habitus (Adkins, 2003; Mouzelis, 2009; Sweetman, 2003). All of these accounts broadly suggest that people in different social locations are exposed to different types of social and cultural influences which lead them to develop thinking dispositions. 

Socially Locating Thinking Dispositions

In a recent paper with Andrew Miles, I put these considerations to the empirical test by comprehensively establishing the social patterns of thinking dispositions (Brett and Miles, 2021). We quickly found that some psychologists had indeed tested this, particularly using Epstein’s (1996) REI. However, this research was limited in several respects; these studies measured for differences (usually based on age, education, and gender) with little to no theoretical explanation for why these differences exist, nor analytic justification for why they were tested. Furthermore, they typically used bivariate analyses and convenience samples, and taken together, they offered conflicting findings on whether these variables actually matter. As such, we first performed a meta-analysis of 63 psychological studies that used the REI to measure differences in thinking dispositions based on age, education, and gender, followed by an original analysis with nationally representative data. Overall, we found strong evidence that thinking dispositions vary by age, education, and gender, and weaker evidence that they vary by income, marital status, and religion.

While this covers some social patterns of thinking dispositions as an object of study, sociologists would do well to establish their causes and consequences. The thinkers above suggest a variety of mechanisms that may promote thinking dispositions, including specific child-rearing practices and forms of socialization, heightened sensory stimulation, and having the time and space for imaginative, contemplative, or experimental thought – all of which could be tested empirically. But perhaps more importantly, thinking dispositions likely hold significant consequences for culture, cognition, and action that ought to be explored. 

For example, in a recent paper with Vanina Leschziner (Leschziner and Brett, 2019) I used the notion of thinking dispositions to help explain patterns of culinary creativity. We found that chefs who were more invested in innovative styles of cooking tended to be more analytical in their approach, while chefs invested in more traditional styles of cooking held a more heuristic approach to cooking. Notably, this was not simply the result of exogenous pressures they had to create novel dishes; instead, these chefs developed an inclination and excitement for these modes of thought during the creative process that had become dispositional over time. While culture and cognition scholars would typically ascribe these differences to the type of restaurants chefs worked in or the style of food they produced, this misses the distinct link between cognitive styles and culinary styles. As this illustrates, thinking dispositions may hold important but (as of now) largely untapped explanatory value for sociologists.

References

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Bourdieu, Pierre. 2000. Pascalian Meditations. Stanford, CA: Stanford University Press.

Brett, Gordon, and Andrew Miles. 2021. “Who Thinks How? Social Patterns in Reliance on Automatic and Deliberate Cognition.” Sociological Science 8: 96-118.

Cacioppo, John T., Richard E. Petty, Jeffrey A. Feinstein, and W. Blair G. Jarvis. 1996. “Dispositional Differences in Cognitive Motivation: The Life and Times of Individuals Varying in Need for Cognition.” Psychological Bulletin 119(2):197–253.

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Pennycook, Gordon, James Allan Cheyne, Derek Koehler, and Jonathan Albert Fugelsang. 2020. “On the Belief that Beliefs Should Change According to Evidence: Implications for Conspiratorial, Moral, Paranormal, Political, Religious, and Science Beliefs.” Judgment and Decision Making 15 (4):476–498.

Pennycook, Gordon, James Allan Cheyne, Paul Seli, Derek J. Koehler, and Jonathan A. Fugelsang. 2012. “Analytic Cognitive Style Predicts Religious and Paranormal Belief.” Cognition 123(3):335–46.

Pennycook, Gordon, and David G. Rand. 2019. “Lazy, not Biased: Susceptibility to Partisan Fake News is Better Explained by Lack of Reasoning than by Motivated Reasoning.” Cognition 188:39-50.

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Vaisey, Stephen. 2009. “Motivation and Justification: A Dual-Process Model of Culture in Action.” American Journal of Sociology 114(6):1675–715.

Vaisey, Stephen, and Lauren Valentino. 2018.”Culture and Choice: Toward Integrating Cultural Sociology with the Judgment and Decision-Making Sciences.” Poetics 68: 131-143.

Vila‐Henninger, Luis Antonio. 2015. “Toward Defining the Causal Role of Consciousness: Using Models of Memory and Moral Judgment from Cognitive Neuroscience to Expand the Sociological Dual‐Process Model.” Journal for the Theory of Social Behaviour 45(2): 238-260.

Sociology’s Motivation Problem (Part I)

Sociology has an action problem. Explaining social action rests at the core of sociological inquiry. However, at best, the typical explanatory mechanisms focus almost exclusively on two of Mead’s three aspects of the self: the generalized other and the me. Six decades after Dennis Wrong’s (1962, 1963) critique of mid-twentieth-century sociology, its grasp over Mead’s I remains tenuous, at best. In this particular respect, sociology has a motivation problem, as noted by others before (Campbell, 1996; J. H. Turner, 2010). This problem can be traced to two sources.

On the one hand, there is the undue influence of a paper by C. Wright Mills (1940) on vocabulary of motives (Campbell, 1996). On the other hand, there is sociology’s deep-seated fear of over-psychologizing or over-economizing human action (J. H. Turner, 2010). Consequently, sociological solutions to its motivation problem remain on the wrong side of Wrong’s oversocialized critique. Instead of “forces mobilizing, driving, and energizing individuals to act…” (J. H. Turner, 1987, p. 15), we are left either with explanations relying on distal, external forces, like values/norms (Inglehart & Baker, 2000; Schwartz, 2012), or exogenously specified interests/goals (Coleman, 1990). As critics of both normativist and utilitarian approaches note (Martin & Lembo, 2020; Whitford, 2002), the effects, internalization, and patterning of values and interests are mysterious at best and rob individuals of agency at worst. Ultimately, appeal to values and interests as core motivational states to answer the fundamental question of why people “want what they want” falls short of explaining action.

So, what is motivation? We argue that an answer to the question of motivation cannot be obtained by drawing on any single discipline’s intellectual resources. Instead, an interdisciplinary approach is required. Ideally, such an approach would combine the strengths of sociology, psychology, cognitive science, and the emerging fields of affective and motivational neuroscience. Ideally, this would (and, we think, can) be done without sounding the reductionist alarm bells, especially regarding psychology and neuroscience. However, before getting to this, we have to put to bed the Millsian shadow that has distanced sociology’s usage of motivation from every other social and behavioral science, and then consider the potential best candidates for a sociology of motivation.

Motives, Justifications, and Motivation, Oh My!

In his critique of the subjective “springs of action,” Mills (1940) committed sociology to the search for and study of “typical vocabularies having ascertainable functions in delimited societal situations [that] actors do vocalize and impute motives to themselves and to others” (904). Notably, these motives were not in “an individual” but were instead conceived as the “[t]erms with which interpretation of conduct by social actors proceeds.” This theoretical move, celebrated as it may be (e.g., Hewitt, 2013), removed the possibility of considering intrapersonal forces of any sort in theorizing motivation, even in social situations (J. H. Turner, 2010). It has also led to various (unnecessary) mental gymnastics sociologists routinely put themselves through as they seek to recover or reinvent ideas that have well-established, shared meanings in other fields, resulting in the creation of a sociological idiolect that is hard to translate into the lingua franca of the broader social and behavioral sciences (Vaisey & Valentino, 2017). For instance, Martin (2011) proposes a neologism (“impulsion”) to refer to good old-fashioned motivation (internal forces compelling people to act), given the monolithic disciplinary understanding of motivation as a set of stereotyped vocabularies. It also made conceptual confusion surrounding the difference between a motivational process or motivating force and motive talk and justifications (or what Scott and Lyman (1968) eventually called accounts).

Thus, sociologists face a difficult decision. On the one hand, they can risk internal disciplinary criticism for “over-psychologizing” action and examine internal motivational processes or the meanings actors use across different contexts for organizing actions. This is what social psychologists call motives (Perinbanayagam, 1977) and what Mills criticized as subjective springs of social action. On the other hand, they can hew closely to current disciplinary circumscriptions and restrict their studies to post hoc rationales that may or may not be connected to the actual motivation or motive, but what Mills did call a motive (Franzese, 2013). Ultimately, in place of causes of action, the emphasis shifted to post hoc “motivation talk” or accounts (Hewitt, 2013; Scott & Lyman, 1968), restricting the sociology of motivation to the search for and recording of creative post hoc reconstructions (and thus likely to be confabulations not necessarily tied to the causes of action) that attempt to tell a normative appropriate or culturally stereotyped story about “the reasons” why people engage in this or that line of action (Campbell, 1996; Martin, 2011, p. 311ff).

We can trace the pervasive disciplinary influence of Mills’s argument, in part, sociology’s unwitting adherence to the Durkheimian vision of homo duplex (Durkheim, 2005). Under this framework, in its most naïve form, psychological processes are beyond the sociological bailiwick. In its most vulgar form, psychology is unnecessary as explanans because sociological explananda are sui generis (Durkheim, 1895/1982). This unnecessarily lingering barrier keeping psychology and related behavioral sciences at bay prevents sociology from explaining how and why people are motivated to act—a theoretical puzzle resting at the discipline’s foundations. Instead of explicitly theorizing intrapersonal processes, we find implicit sociological versions of psychology working hard to locate motivational forces, like pressures to conform or belongingness, outside the individual. And, yet, like Mills’ own formulation, these efforts always run afoul of Wrong’s (1963) critique in so far as these external causal forces of action must be internalized somehow. This leads to an image of people as marionettes whose strings are pulled by some sort of oversocialized ideological force like neoliberalism or patriarchy or their motive mechanisms like pressure to conform.

In the process of picking one’s favorite ideological force or motive mechanism, those adhering to Mills or Parsons or any externalist commits the more critical error of which we call the mono-motivational fallacy. Central to Wrong’s critique of functionalism was its strict adherence to a single causal force: the need or pressure to conform to normative expectations. A pressure rooted in socialization or enculturation and through alchemy imposes a collective conscience on the individual conscience. Pressure to conform, however, is not the only mono-motivational engine of action. Any external explanation—such as situations or situational vocabularies, networks, and influence—that has a predominant effect on human behavior requires analysts to implicitly or explicitly postulate an overarching “meta-motivation” (Maslow, 1967) to all people: To conform or follow the external prescriptions, normative pressures, and so forth provided by society (Wrong, 1961, 1963).

This fallacy is amplified when distal or exogenous causes, like values or interests, are introduced into the explanation. Asking individuals, after the fact, may “tap” into shared beliefs but in no way allow us to explain why or how someone did what they did. This is a dilemma most pronounced when we consider, for instance, the panoply of a-social or “anti-social” motivations that observers of human behavior from Plato to Freud have described (Wrong, 1963). Luckily, there are sociological alternatives or candidates for a more empirically sound theory of motivation. The first set of alternatives can be found in microsociology and sociological social psychology.

Human Thermostats

A large body of social psychology relies on the notion of homeostasis or, more commonly, control models (Powers, 1973). Like a house thermostat, input comes in from the environment about our identity performance, situational alignment of expected meanings and actual meanings, justice and fairness, or whatever is the need-state du jour. Whenever there is an error or discrepancy between the internal “set” state and the current environmental feedback, we are motivated to return the thermostat to its original setting. In part, this mechanistic view draws inspiration from Dewey’s and Mead’s pragmatism, identifying a mechanism operating in place of pragmatist ideas about problems, problem-situations and sifting through different action possibilities to resolve those problems. But, the control-theoretic approach also over-relies on cognitive appraisals, which suggests, like Mills’ vocabulary of motives, an internalization process sensitive to external pressures keyed to maintaining the (societally) preset “temperature.” After all, someone must set the thermostat; in sociology, that someone is the generalized other. It also relies on, implicitly, an early twentieth-century model of motivation that emerged in physiology (Cannon, 1932), psychology (Hull, 1937), and, especially, psychoanalysis: drive reduction (where the drive is to reduce the discomfort produced by the mismatch between current feedback and internalized expectations). And yet, sociological applications of control theories work hard to obscure the underlying psychological mechanism.

Other possible candidates, however, make these mechanisms explicit. For example, in a naturalist version of utilitarianism, due to Bentham, in its most vulgar form, all action can be explained by the pursuit of pleasure and the avoidance of pain. Some versions of “sociological rational choice theory” borrow this implicit driver but layer various external constraints, tradeoffs, and exchange interdependencies in the pursuit of interests. So, people are driven to realize their interests by pursuing goals, but collectives shape these goals through joint task inseparability, incurring costs for access to collective goods and the like (Coleman, 1990). Likewise, role theory relies upon, at least partially, internal commitment to roles for which actors anticipate being rewarded in the future (Turner 1978) and avoidance of roles punished or sanctioned by institutional authorities (Goffman 1959).

The same can be said for two other quintessential social-psychological motivations: belongingness (Baumeister & Leary, 1995) and ontological security (Giddens, 1984). The former presumes that a fundamental meta-motivation of all social behavior, both expressive and suppressive, is driven by the evolved need to belong to social groups and attachment to other people and collectives. A social psychological form of functionalism, admittedly, this tradition shifts from distal causes (values and external pressures) to proximate causes (evolved needs present at birth). Similarly, a host of sociological traditions, ranging from phenomenology, ethnomethodology, structuration theory, expectation states theory, and role theory, rely on an evolved need for cognitive order, facticity, and predictability (and, relatedly, trust). From these perspectives, people are motivated to assume the world is as it seems to be and actively sustain this belief through consistent, predictable, and stable action. The horrors of anomie or the collapse of plausibility structures, as Berger (1969) defined it, is too great an internal force to not motivate us to act in the positive (by conforming) and in the negative (by avoiding upsetting the moral order).

Despite the temptation of more explicitly delineated psychological mechanisms, these three possible candidates, along with control theories, rely too heavily on implicit (and sometimes explicit) drive and need-state reduction conceptions of motivation, which in turn fancies mono-motivations (to belong, facticity, cognitive order, and the like). They also depend solely on external factors to specify motivational dynamics. For example, belongingness is impossible without a social object to which one belongs. That is, motivation remains external because the things we want or the things that compel us to act have to be beyond our body and brain.

Multi-Motivational Models

Jonathan Turner’s (1987, 2010) work on the motivational dynamics of encounters seems well-poised to deal with the two limitations of need-state and drive reduction models in sociology, namely, their penchant for devolving into mono-motivational accounts and their sole focus on external drives. Turner’s work is synthetic and directed towards explaining how the basic unit of social analysis—the encounter, situation, or interaction depending on one’s persuasion—is built up. The argument is that social psychologists, usually of the “control-model variety” described above, have isolated slivers of a larger microsociological dynamic. However, these pieces need to be combined to get a more robust vision of what sorts of motivational or transactional forces driving micro-level action and interaction. Turner’s criterion for defining motivation is simple: “persistent needs that [people] seek to meet in virtually all encounters, especially focused encounters” (193). Unmet needs generate negative emotions that lead actors to leave the encounter or sanction those who have thwarted their efforts. In contrast, met needs produce positive affect, help maintain the encounter, and leave the actor with a desire to interact again in the future. Turner’s list includes the following five need-states: (1) identity verification, (2) a sense of fairness and justice in exchanges, (3) group inclusion, (4) trust, and (5) facticity. He conceptualizes them as additive, with encounters being possible when one or two of them are met but unlikely to be as satisfying or encouraging of recurrence when they are not met.

Turner’s model achieves two important analytic goals. First, it comes as close to a biopsychological model as any sociologist we are aware of. Second, it locates an explanation for social processes within the individual. In his larger theoretical framework of micro-level dynamics, Turner sees role, status, emotion, and culture “making” as emerging from the combination of these needs. Roles, for instance, emerge from persistent efforts to verify identity–consistency in performance–and ensure facticity and trust–predictability (see R. Turner 1978). But, of course, once roles are created, they become emergent, distinct properties that simplify meeting needs as people take pre-set roles (in addition to statuses, emotions, and culture). Motivation, then, is shaped by the social environment; creative efforts to alter a single encounter or a larger structural-cultural unit like the group, and patterned by the crystallization of certain “vehicles” of structure and culture. Consequently, neither the intra nor interpersonal is reduced in Turner’s model to a meta-motivational need, nor does it succumb to a drive reduction model.

Turner’s model, however, is not without limitations despite its important advances. First, even when the author qualifies them by arguing theirs is not exhaustive, need-state lists are delimiting. They naturally ignore the open-ended nature of desire and, more broadly, the idea of desire itself (Schroeder, 2004). It is not that social life is free of pressure to conform to roles, but even Ralph Turner (1976) labored to show action was often “impulsive.” This was a poorly chosen term, meaning that many situations afforded people the freedom to do many things that can only be explained by thinking about desire. A second problem derives from the first: because lists are incomplete, one could add goals ad infinitum, eventually running into problems like contradictory goals or ideological commitments of the list-maker. Finally, D’Andrade (1992) reminds us that motivations are generally situationally bound: though humans are social creatures reasonably constrained by the scaffolding erected by social institutions and our habits, the truth of the matter is (a) we all tend to respond to the immediate situation, (b) our choice to pursue certain situations, even those that are unhealthy, are rooted as much in neurophysiology as some abstract construct like a role, and (c) many objects that are anticipated, consumed, and reinforced after satiation is inside our bodies (food/sex; belongingness; domination) and, yet, sociologically relevant (Kringelbach & Berridge, 2016). Like all delimiting devices (e.g., the Classical Theory canon), lists are arbitrary, and arbitrary lists are flawed road maps for explaining action.

In a follow-up post, we will tackle the fixes to these three critical mistakes—the mono-motivational, social-psychological, and list-making fallacies.

References

Baumeister, R. F., & Leary, M. R. (1995). The need to belong: desire for interpersonal attachments as a fundamental human motivation. Psychological Bulletin, 117(3), 497–529.

Berger, P. L. (1969). The Sacred Canopy: Elements of a Sociological Theory of Religion. Doubleday.

Campbell, C. (1996). On the concept of motive in sociology. Sociology, 30(1), 101–114.

Cannon, W. B. (1932). The wisdom of the body. Norton.

Coleman, J. C. (1990). Foundations of Social Theory. Harvard University Press.

D’Andrade, R. G. (1992). Schemas and motivation. In R. G. D’Andrade & C. Strauss (Eds.), Human motives and cultural models. (pp. 23–44). Cambridge University Press.

Durkheim, E. (1982). Rules of Sociological Method (S. Lukes (ed.); W. D. Halls, trans.). The Free Press. (Original work published 1895)

Durkheim, E. (2005). The dualism of human nature and its social conditions. Durkheimian Studies, 11(1). https://doi.org/10.3167/175223005783472211

Franzese, A. T. (2013). Motivation, Motives, and Individual Agency. In J. DeLamater & A. Ward (Eds.), Handbook of Social Psychology (pp. 281–318). Springer Netherlands.

Giddens, A. (1984). The constitution of society: Outline of the theory of structuration. Univ of California Press.

Hewitt, J. P. (2013). Dramaturgy and motivation: Motive talk, accounts, and disclaimers. In C. Edgley (Ed.), The Drama of Social Life: A Dramaturgical Handbook (pp. 109–136). Routledge.

Hull, C. L. (1937). Mind, mechanism, and adaptive behavior. Psychological Review, 44(1), 1.

Inglehart, R., & Baker, W. E. (2000). Modernization, Cultural Change, and the Persistence of Traditional Values. American Sociological Review, 65(1), 19–51.

Kringelbach, M. L., & Berridge, K. C. (2016). Neuroscience of Reward, Motivation, and Drive. In Recent Developments in Neuroscience Research on Human Motivation (Vol. 19, pp. 23–35). Emerald Group Publishing Limited.

Martin, J. L. (2011). The explanation of social action. Oxford University Press.

Martin, J. L., & Lembo, A. (2020). On the Other Side of Values. The American Journal of Sociology, 126(1), 52–98.

Maslow, A. (1967). Atheory of metamotivation: The biological rooting of the value-life. Journal of Humanistic Psychology, 7, 93–127.

Mills, C. W. (1940). Situated Actions and Vocabularies of Motive. American Sociological Review, 5(6), 904–913.

Perinbanayagam, R. S. (1977). The structure of motives. Symbolic Interaction, 1(1), 104–120.

Powers, W. T. (1973). Behavior: the Control of Perception. Aldine Publishing Company.

Schroeder, T. (2004). Three Faces of Desire. Oxford University Press.

Schwartz, S. H. (2012). An Overview of the Schwartz Theory of Basic Values. Online Readings in Psychology and Culture, 2(1), 11.

Scott, M. B., & Lyman, S. M. (1968). Accounts. American Sociological Review, 33(1), 46–62.

Turner, J. H. (1987). Toward a Sociological Theory of Motivation. American Sociological Review, 52(1), 15–27.

Turner, J. H. (2010). Motivational Dynamics in Encounters. In J. H. Turner (Ed.), Theoretical Principles of Sociology, Volume 2: Microdynamics (pp. 193–235). Springer New York.

Turner, R. H. (1976). The real self: from institution to impulse. AJS; American Journal of Sociology, 81(5), 989–1016.

Vaisey, S., & Valentino, L. (2017). Culture and Choice: Toward Integrating Cultural Sociology with the Judgment and Decision-Making Sciences. Poetics, 68 , 131–143.

Whitford, J. (2002). Pragmatism and the untenable dualism of means and ends: Why rational choice theory does not deserve paradigmatic privilege. Theory and Society, 31(3), 325–363.

Wrong, D. H. (1961). The Oversocialized Conception of Man in Modern Sociology. American Sociological Review, 26(2), 183–193.

Wrong, D. H. (1963). Human nature and the perspective of sociology. Social Research, 30(3), 300–318.

 

 

On Looping Effects

In this post, I sketch out some preliminary ideas for introducing repetition into theories of social formation and for situating cognition at their base. The major principle for this endeavor is what I (unoriginally) propose as loops. More originally, I argue that loops take at least three different forms and that not all looping effects are created equal. Loops are equal, however, in putting the onus on repetition as a source of scaled orders and formations (e.g. “structures,” “enclosures,” “molds,” “modulations”) rather than on generality.

A loop, quite simply, is a generative process with one necessary condition: a non-identity between two parts, but two parts that repeat in their connection. A repeating loop makes a scaled order particular rather than general, because it is fundamentally a sequence.  Loops might be broadly instantiated, but they cannot find equivalences everywhere. As repetitions, they need the same ingredients. As connections and cycles, they remain distinctive rather than ordinary. 

Douglas (1986: 100-02) suggests that a looping effect need not directly involve a human agent at all; they are mostly natural. Knowledge of microbes leads to medications; when those medications are applied to microbes, the microbes adapt. This explains a clear feedback relation, but it is not a loop: microbes change because of knowledge about them; but the change needs no repetition. It is adaptive instead. 

The thing about a loop is that it must repeat  (again and again). A loop must generate its own momentum. This link between repetition and loops has been neglected to date. Such neglect means that looping effects are discussed separately from the prevalence of scaled orders and formations,  for instance those that are “disciplinary” versus those that are “control,” leaving both of fuzzy meaning and provenance, used interchangeably. When we concentrate on looping effects as repetitions, it becomes clear that orders and formations of scale (e.g. not presumed to be general; that cannot find equivalences everywhere) rest largely on an edifice of cognition that, in practice, does not need to remain implicit in order to be effective.

 

Hacking loops (enclosures, molds)

For Hacking (1995; 2006), loops come from the process of classification and categorization that feeds a dynamic nominalism. Classifications are made by people about people, as an index of traits, of the properties displayed by the latter. In a Hacking loop, classifications made by people about people loop into their target and alter it. The classifiers “create certain kinds of people that in a certain sense did not exist before.” The onus rests on the name given to these traits that collects them together. Hacking loops therefore represent a form of nominalism: they need not become entangled with real kinds or make any difference for them. What matters more is the name, its legitimation by expertise, its elaboration by institutions, its officialization by bureaucracy, all of which reinforces its external, public and legitimate presence. 

As Hacking puts it: 

In 1955 “multiple personalities” was not a way to be a person, people did not experience themselves in this way, they did not interact with their friends, their families, their employers, their counsellors, in this way; but in 1985 this was a way to be a person, to experience oneself, to live in society (2006).

The intervention of 30 years meant the formulation of this name, the proliferation of knowledge and the accumulation of references under its heading, all giving it a stable external presence, by indexing various evident things (e.g. “this is that”) in a distinguishable way. While the traits of multiple personality (or manic depression, anxiety disorder, etc) might have preceded the name, this is not Hacking’s point: as a “way to be a person,” multiple personality needed a name that could index these traits and thereafter be a way of indexing of oneself (e.g. “that is me”).  Such a sequence (this is that → that is me) becomes fully reversible (that is me → this is that). A name, increasingly standardized, rationalized and externalized (e.g. “discourse”) makes up and stabilizes people by feeding back into their identification (this is that ←→ that is me).

To be a certain type of person, to live in society as that person, to be interacted with as that person, and most importantly to experience oneself as that person occurs through a Hacking loop. Importantly, all of these effects require only an external process rather than a change of “inner life.” A name is “deep” in a contingent sense: the loop rests upon the identification of those who are indexed. It makes no substantive difference for the traits that are indexed that they now receive a name. In fact, Hacking loops seem to require this given the proliferation of names and entire professions and forms of expertise dedicated to classification. However, it does make a difference for those who are classified and named. Hacking loops create an enclosure or mold, from which there might be no escape so long as the name is externally maintained.

 

Mutually sustaining relations (structures)

A different loop is proposed by Sewell in what we might call his principle of mutually sustaining relations. The terminology here concentrates on a “mutually sustaining” loop between two different kinds of things (schemas and resources), as mentioned in the following influential formula and applied (famously) to a theory of structure:

Structures … are constituted by mutually sustaining cultural schemas and sets of resources that empower and constrain social action and tend to be reproduced by that action. Agents are empowered by structures, both by the knowledge of cultural schemas that enables them to mobilize resources and by the access to resources that enables them to enact schemas (27).

As Sewell implies, schemas and resources mutually sustain each other through a repeating connection. A schema remains an effect of resources, just resources are the effect of schemas. 

When the priest transforms the host and wine into the body and blood of Christ and administers the host to communicants, the communicants are suffused by a sense of spiritual well-being. Communion therefore demonstrates to the communicants the reality and power of the rule of apostolic succession that made the priest a priest. In short, if resources are instantiations or embodiments of schemas, they therefore inculcate and justify the schemas as well (13)

Unlike a Hacking loop, Sewell’s “mutually sustaining” loop does suggest a deep effect, as the very constitution of a set of properties as “resources” are schema dependent, just as the constitution of mental categories as “schemas” are resource dependent. A resource is equivalent to the traits that a Hacking loop collects under the heading of a name, but a schema does not “name” them. Sewell characterizes the mutually sustaining link as instead “reading” or “interpreting.” A resource needs to be read as a resource in order to be a resource. A schema does the reading. A schema, presumably, is not a schema if it does not read or interpret resources. The loop can be initiated through either end: resource accumulation to a schema (resource → schema) or schema accumulation to a resource (schema → resource). A loop becomes difficult to sustain in cases that allow for too much agency (e.g. transposition of schemas), which prevents an unambiguous rendering of resources. 

In cases where there are limited schemas for “reading” and “interpreting”  a resource, and this is in turn “sustained” by limited resources for other possible schemas, a “structure” will result. A structure is distinguishable from a “mold” or “enclosure” in a Hacking loop. Structure, by contrast, suggests not only a potential source of resistance but also the limits of meaning. This entails the  “depth” of structure as opposed to the externality of a mold. Structure refers to inner life, which it substantially depends on shaping and altering. The surface-level chaos of capitalism, for instance, only signals the depth of a schema ←→ resource loop: the schematic and repeating transformation of use- to exchange-value is a necessary condition for “resource” in this context; resources, meanwhile, accumulate to “schemas” that involve a use-to-exchange transformation.

We should expect structures to change through disruption to an established loop, via the interchangeability and replacement of both parts of structural loops (schemas and resources). This creates demands on inner life through transpositions that likely appear “impractical” in their interpretations and reading of things. The chance of resource accumulation keeps the possibility of structural change open.

 

Expectations-chances loops (modulations)

Hacking loops and Sewell’s mutually sustaining loops are both known well-enough by this point as to render the above discussion boring by comparison. To finish this post, I want to make two proposals: first, that Hacking’s “molds” and “castings” and Sewell’s “structures” are both loops found within a disciplinary order. This suggests a relative limit on their generality, though equally they remain contingent on repetition (as loops). Second, I want to understand a disciplinary order as distinct from a control order based on a different loop that engages cognition differently than naming, reading, or interpreting (Deleuze 1992). This is a expectations-chances loop that works according to (objective) prediction and (subjective) guessing (see Bourdieu 1973: 64).  

In one version of this loop, the tale is told indicatively as follows:

Acrimonious debates about the calculative abilities of individuals and the limits of human rationality have given way to an empirical matter-of-factness about measuring action in real life, and indeed in real time. The computers won, but not because we were able to build abstract models and complex simulations of human reasoning. They bypassed the problem of the agent’s inner life altogether. The new machines do not need to be able to think; they just need to be able to learn. Correspondingly, ideas about action have changed (Fourcade and Healy 2017: 24). 

Hence, a proposal for non-intentional action becomes applicable to data-gathering mechanisms, but the “index” is different in this scenario, as it includes “inner life” no longer. “Culture” is an association rather than internalized pattern generator. It does not have effects, but rather stands for a history of traces:

When people are presumptively rational, behavioral failure comes primarily from the lack of sufficient information, from noise, poor signaling or limited information-processing abilities. But when information is plentiful, and the focus is on behavior, all that is left are concrete, practical actions, often recast as good or bad ‘choices’ by the agentic perspective dominant in common sense and economic discourse. The vast amounts of concrete data about actual ‘decisions’ people make offer many possibilities of judgment, especially when the end product is an individual score or rating. Outcomes are thus likely to be experienced as morally deserved positions, based on one’s prior good actions and good taste.

A theory of action remains, then, even despite the absence of inner life; because data is simply action. Data can modulate action through a “herding” or directing effect, creating futures based on past performance and subsequent encoding. Since there is no inner life, classification is based on information collected at junctures that create possible futures. The causes of action are not of interest (only that action happens), though there are consequences to action. This can exercise a disciplinary effect through anticipation, as facilitated by the rationalization of trials. Since there is no ideal model (or name gathering of characteristics a priori), however, this is not integral to control. There is only the fact that one must have been through certain trials and then out of them. 

Predictions made through data protocols interface with predictions made in action. Trials introduce uncertainties that meet with anticipations; a certain future is achievable when possibilities are presented algorithmically and displace an otherwise “wild’ cognition. Control becomes an algorithmic modulation of future possibilities rather than a generative modulation of guesses. 

The systematic production of “good matches” is based on controls exercised on the means of prediction from both ends: the expropriation of the means of prediction and the controlled distribution of what they predict. This keeps the loop closed between the (objective) provision of possibilities and (subjective) anticipations or guesses, making “this matching feel all the more natural because it comes from within—from cues about ourselves that we volunteered, or erratically left behind, or that were extracted from us in various parts of the digital infrastructure” (Fourcade and Healy 17). 

Modulation takes place through cognitive loops, constructing a “self-deforming cast that will continually change from one moment to the other, or a sieve whose mesh will transmute from point to point” (Deleuze 4). Conventionally, the connection between “schema” and power is content-laden and substantive: it provides a way to “read” resources (Sewell 13). An expectations-chances loop finds no equivalent to “reading” (or interpreting or naming); the key process is guessing instead. A non-individual recorder or record-keeper (qua technology) can guess even if it cannot read, and it can adapt its guesses, improve them. Here looping is incompatible with “molding” or “casting”; “structure” is static by comparison. After all, you can know when you leave the “cast” and its standard no longer applies.

The theory of power embedded in a schema-resources loop puts the onus on schemas that “read” resources; this is where we find agency. In a disciplinary context, an ideal or standard (a telos) is enforced and sought after. In control contexts, such a standard goes missing. Trials are not examinations. A model is volunteered rather than enforced. An individual is a record, though there is no record-keeping individual (“examiner” or “recorder”). Rather than being incorporated into a structure (through schemas), agents are made precise as a code or classification. They do not exercise effects (structural or otherwise) but are given possible futures. They are not shoehorned into the fixed parameters of a schema. They bootstrap themselves into sequences that look increasingly like their own good matches. 

 

Conclusion 

We should therefore expect the genesis and transposition of expectations just as we do those of schemas or names, in looping connection with chances, as a way of inviting chance in or taming it. But there is a catch. The consequence of a “controlled” expectations-chances loop can be similar to the amnesiac returning to memory after several long years: “My God! What did I do in all those years?” (Bourdieu [1995] quoting Deleuze 1993). Consider, along exactly similar lines, a “coming to” after diving down an algorithmically modulated rabbit-hole. The explanation must be cognitive because this occurs through repeating loops. Disciplinary formations can achieve (reflexive) “consciousness” and nothing will change; the same is not true for control formations. 

 

References

Bourdieu, Pierre. (1973). “Three forms of theoretical knowledge.” Social Science Information 12: 53-80.

Bourdieu, Pierre. (1995). The State Nobility. Stanford University Press.

Deleuze, Gilles. (1992). “Postscript on societies of control.” October 59: 3-7.

Deleuze, Gilles. (1993). The Fold: Leibniz and the Baroque. University of Minnesota Press.

Douglas, Mary. (1986). How Institutions Think. Syracuse University Press.

Fourcade, Marion and Kieran Healy. (2017). “Seeing like a market.” Socio-Economic Review 15: 9-29.

Hacking, Ian. (1995). “The looping effects of human kinds.” Pp. 351-394 in Causal Cognition: A Multidisciplinary Debate.

Hacking, Ian. (2006). “Making up people.” LRB 28.

Sewell, William. (1992). “A theory of structure: duality, agency and transformation.” American Journal of Sociology 98: 1-29.