Implicit Culture and the Insane Clown Posse Stance

In a recent article published online first in the Journal for the Theory of Social Behavior, I attempt to sort out the (various) distinction(s) cultural analysts aim to track when they use the term implicit culture (and, by implication, explicit culture). The article is partly based on reflections developed previously in this blog (see here and here). As I note in the article, things get a bit complex because the term “implicit” tracks a different cluster of distinctions when used to refer to personal culture than it does to public culture, especially that routinely enacted and externalized as institutions (on cultural kinds and institutions, see Lizardo, 2019).

Public versus Personal Implicit Again

Here I would like to focus on a few implications of the argument I left hanging, particularly regarding the epistemic relation between people and the culture the analyst deems to be implicit. The paradigm case here is taken from implicit personal culture (on the distinction between personal and public culture, see Lizardo, 2017), and the prototype is the (either Freudian or modern cognitive-scientific version of) the unconscious (see Khilstrom, 2018). So, personal culture is implicit to the extent that it operates or is used by people for various pragmatic and cognitive tasks (to classify, act, think, and the like) without people being aware that it does so. The prototypical (contemporary) empirical phenomenon manifesting this type of implicit personal culture is the now-classic case of implicit attitudes (see Brownstein, 2018).

In the article, I warned that it is a tempting strategy to attempt to use the model of the epistemic relation people have with their unconscious stock of personal culture (what I called u-implicitness; this is one of two ways personal culture can be implicit; see the article for further argument) to understand the epistemic relation between public-implicit culture and people. This move does not work because implicit public culture exists exclusively as an aspect of either simple or complex external artifacts, with the artifact notion being maximally defined; see here and here (note that this is an explicit—pun intended—and possibly defeasible ontic claim about the nature of implicit public culture). Therefore, an epistemic relation between people and internal mental items can’t be used as a model (at least not without major modifications) for the epistemic relation between people and (the implicit aspect of) external non-mental items. That is, precisely because there is no such thing as cultural kinds that are public and mental (such an entity would violate the Muggle constraint), the epistemic relation between people and the public implicit cannot be the same as that between people and the personal implicit (e.g., within naturalistic constraints, there can’t be such thing as an impersonal but somehow still mental “collective unconscious,” although such a nonsensical thing has been imagined by people in the past).

So, what epistemic relation can plausibly obtain between people and public-implicit culture? Drawing on classic philosophical reflections by members of Insane Clown Posse (ICP), I proposed that the modal epistemic relation between people and implicit public culture is that of ignorance, particularly the sort of ignorance that obtains when we don’t know how a complex natural kind works. Thus, when faced with magnets (a complex natural kind), members of ICP (literally) throw up their hands and exclaim: “fuckin’ magnets, how do they work?” Expressing that the underlying workings of the magnet, productive of observed electromagnetic phenomena, are implicit to them. If ICP were committed vitalists (and as far as I know, they might be), they could have asked the same question about biological kinds: “fuckin’ cats, how do they work?” For the vitalist, the mechanisms that generate and sustain biological life are implicit and, therefore, mysterious (and better left that way). Note that, since magnets are not implicit to trained physicists familiar with Maxwell’s electromagnetic theory (and cats are not implicit to trained biologists), it follows that some (natural or biological kinds) that are implicit to person or group A could be explicit to person or group B; implicitness is a relational property of public cultural kinds and there are always relative to a given knower (or group of knowers). A general definition of (scientific) expertise follows from this; experts are simply those for whom some complex domain (e.g., high-energy physics) is (relatively more) explicit, when it is, in fact, (relatively more) implicit to most of us (see Collins & Evans, 2008).

Implicitness in Public Cultural Kinds

I argued that the ICP implicitness criterion transfers neatly to complex artifactual cultural kinds and particularly to sets of complex artifactual kinds locked together into self-reproducing loops externalized as institutions, like money, debt, gender, race, the state, language, or organizations (see Graeber, 2012; Lizardo, 2019; Jung, 2015; Haslanger, 2005). Just because (via the causal-historical criterion) a piece of public culture is generated via the thinking and practical activity of people does not mean that that piece of public culture is epistemically transparent (e.g., explicit) to those people (or to an external anthropological observer that comes in after the fact and tries to understand it). Thus, we must drop the common fallacy that just because people make public culture (or are implicated in its making and unmaking) it is necessarily explicit to those makers (or, even less likely, to “downstream” users). A moment’s reflection reveals that the opposite will be the case; after a reasonable degree of complexity is reached, most pieces of public culture (e.g., a narrative, a collective memory, a classification system, and the like) will have more implicit than explicit aspects. Nevertheless, those implicit aspects could be potentially recoverable—and thus made explicit—via some analytic procedure (thus justifying—one version of—the project of “measuring culture”). So, we can ask the same question about all types of public artifacts as ICP ask of magnets: “fuckin’ language, how does it work?; fuckin’ states, how do they work?; fuckin’ gender, how does it work?; fuckin’ money, how does it work?”; “fuckin’ organizations, how do they work?” and so forth.

That we can be ignorant of how these artifactual kinds work is the (non-Kantian) condition of possibility for there to be experts (e.g., linguists, political scientists, political sociologists, gender and race theorists, economic anthropologists, organization theorists, and the like) for whom the relevant public cultural kinds are (relatively) less implicit than for most of us. Durkheim (1895) pointed to a version of this in his anti-philosophical argument for an empirical science of society in Rules of Sociological Method; if “social facts” (his name for public-cultural kinds) were purely explicit and thus epistemically transparent to anyone with a brain and some spare time to ponder, they could be thoroughly analyzed from the philosophical armchair and no empirical science of society would be needed. The fact that a good chunk of their nature is not epistemically transparent, thus justifies the need for and the existence of an empirical science of those facts, which helps alleviate our ICP-style ignorance relative to them.

Implicit Public Cultural Kinds and the Knowledge Illusion

Interestingly, this gives us a somewhat different perspective—different from Freudian-style versions that make the fundamental mistake outlined earlier—on why people might sometimes be ignorant about their ignorance of how public cultural kinds work, the various effects they have, and the like. It turns out that when it comes to various domains (e.g., physical, biological, and artifactual), most people do not follow the venerable example of epistemic humility set out by ICP. They do not fully admit their ignorance, and thus the large swaths of implicit aspects of the kinds in question. Instead, they walk around with a particular form of “knowledge illusion” that the cognitive scientists Rozenblit & Keil (2002) baptized as the “illusion of explanatory depth.” They think they know the underlying mechanisms that make artifacts in various mundane domains (e.g., plumbing, electricity, inflation) “work.” When given a paper and a pencil and asked to write down this purported knowledge, most people are stumped and realize that they are, in fact, no better than ICP when faced with a magnet.

It is important to note that being ignorant about how a public-cultural kind works is not the same as being unable to use it or navigate an institutional system partly structured by it. Once again, the analogy with standard artifacts holds. We all know how to use toilets, coffee makers, and computers. Nevertheless, despite knowing how to use these artifacts to accomplish all kinds of practical tasks, most of us don’t know how they work, although we think we do, per the illusion of explanatory depth. Public cultural kinds work the same way; we all know how to “use” money, organizations, and language—admittedly, some better than others—and we even are sort of experts at “doing” all kinds of interactional and boundary work using race, class, and gender (West & Fenstermaker, 1995). However, this “recipe” or “usage-based” knowledge of institutionalized public-cultural artifacts is not really about the fundamental nature—the cogs and wheels—of the relevant cultural kinds and how they work. It has been a crucial mistake in some brands of cultural theory to go from observing the patent fact that most of us (sometimes very skillfully) “use” culture similarly to how we use tools (see, e.g., Swidler, 1986), to conclude that therefore the culture we use is necessarily explicit to the user, under the mistaken assumption that epistemic transparency is a precondition for use. Instead, the opposite is the case. Because public-cultural kinds are artifactual, they are more like computers; we constantly use them without knowing how they work and presuming that we know how they work when we don’t.

Implications for Cultural Analysis

That the knowledge illusion transfers to artifactual public kinds, and by implication, to the highly institutionalized and pervasive versions (e.g., organizations, language, race, gender, money) that fascinate social scientists in the ways just outlined has important implications for cultural analysis. Most significantly, it shows that just like Freud and the old-timey idea of the unconscious (or the newfangled idea of the implicit mind and the cognitive unconscious), where people thought that they had transparent access to their mental life and thus underestimated the amount of personal culture that is u-implicit, people are equally likely to underestimate the amount of implicit public culture out there they are blissfully ignorant of. That is, people think they know how countless complex public cultural domains work, when these are in reality as obscure to them as electromagnetic theory is for members of ICP. Importantly, this gives a somewhat revised “job description” to the social scientist, one that they seldom take (perhaps because a lot of us also fall for the knowledge illusion); social scientists are in the business of making public-implicit culture explicit to people, by revealing the underlying mechanisms that make them work and which are necessarily implicit to the laity.

One uncomfortable (given the populist intuitions of most social scientists and their discomfiture with technocracy) but necessary implication of this is that people are most certainly ignorant of how most public culture works (here ignorant is used to refer to the epistemic relation in a non-normative sense, even though in American English, “ignorant” is seen as an insult or pejorative). Not only that, this is just not just “passive” ignorance; there are pervasive institutional and cognitive loops helping sustain this ignorance, thus keeping people ignorant of their ignorance (Mueller, 2020). Even worse, people likely may have formed all kinds of folk theories about how those cultural domains work. Moreover, most of these theories are very likely wrong. Just like there is a fact of the matter about how a watch, magnets, and cats work, there is a fact of the matter about how racialized social systems and gendered organizations work, and people can have (and are expected to have!) false beliefs about it (if they have any; note that ignorance, accompanied by an illusion of knowing, is the more likely possibility compared to the possession of an elaborate but wrong theory). In other words, the beliefs held by the folk regarding the underlying working of various public-cultural domains should, in principle, be correctable by experts, just like your weird ideas about how magnets (or cats) work are correctable by the relevant scientific experts. The tradition of French-rationalist social science running from Durkheim to Mauss, to Lévi-Strauss, to Bourdieu, to Wacquant, has no problem with this implication and, in fact, derives it from an explicit—pun intended—social scientific theory of expertise relative to the folk.

Note that when it comes to public cultural kinds that people feel like they really, really know how they work (e.g., gender, race, sexuality), this issue becomes even more critical and more vexed, especially when it turns out that many of these kinds are implicated in highly complex self-reproducing loops involving social practices and links between personal and public culture of such intricacy that they will necessarily be primarily implicit even to the most heroic and committed of folks (and even to many “expert” social scientists; otherwise there would be nothing to discover via scientific inquiry). This opens up a familiar can of worms concerning epistemic authority relations between so-called social science experts and the folk, what sort of folk expertise exists out there that social science experts may not have access to, and so forth. These are beyond the scope of this post to deal with; here, I only want to note that any non-trivial commitment to the idea of implicit public culture does force the analyst to take a stance on this complex set of issues. As I remarked, dropping the pseudo-Freudian version of the epistemic relation between people and public-implicit kinds can do a lot to alleviate the concerns of those who see any combination of a Freudo-Durkheimian “authoritarian” epistemology of expert knowledge as necessarily terrible for and dismissive of the folk (see, e.g., Martin, 2011, p. 74ff).

Even more interestingly, recent work by the cognitive psychologist Steve Sloman and collaborators (see Sloman & Fernbach, 2018) reveals that various knowledge illusions are sustained precisely because the folk (implicitly?) think that there are experts out there who possess this knowledge. Thus, a “bottom-up” folk-to-expert relationship can sustain some illusions of knowledge regarding the implicit aspects of public cultural kinds. That is, precisely because there is a social distribution of knowledge and a “division of epistemic labor”—a key implication of “semantic externalism” in philosophy (see, e.g., Burge, 1979; Haslanger, 2005; Putnam, 1975) and social constructionism in sociology (see, e.g., Reay, 2010)—people walk around thinking that they know more about a bunch of stuff they know little to nothing about. The key mechanism here is that, when it comes to knowing, people may (once again implicitly) not differentiate between the knowledge that is “in their heads” and the knowledge that is in other people’s heads (and even knowledge that is stored in non-biological “heads” like books and Wikipedia servers). So one reason people don’t act like ICP all the time is that they (once again personal-implicitly) believe that they live in a community of knowledge (Rabb et al. 2019). In effect, people practically believe that “expert knowledge “out there” is potentially my knowledge “in here,” so I kind of know stuff that I don’t really know.” As long as people believe they have (direct or indirect) social access to how something works, they enter an epistemic stance of ignorance about ignorance because they have access to practical strategies (googling weird rashes) that would relieve them of that ignorance.

Concluding Remarks

In this post, I hope to have shown that the issue of implicit public culture, and the epistemic relation people have with it, goes beyond simple taxonomic matters (although, as I point out in the JTSB piece, the taxonomic piece is essential). Instead, once we get the taxonomic thing straight and develop a coherent way of thinking about the epistemic relation between people and implicit public culture, all kinds of exciting (and controversial) questions open up. These include classic issues in the sociology of knowledge regarding the relationship between people’s practical or personal recipe knowledge and the theoretical or “expert” knowledge of social scientists (which we can tackle using novel theoretical resources), the mechanisms that sustain resistance to knowing more about the implicit aspects of public culture, a version of systematic sociological ignorance concerning how particular cultural and social domains work, along with exciting problems and puzzling phenomena generated by the social distribution and division of epistemic labor.

References

Brownstein, M. (2018). The Implicit Mind: Cognitive Architecture, the Self, and Ethics. Oxford University Press.

Burge, T. (1979). Individualism and the Mental. Midwest Studies In Philosophy, 4(1), 73–121.

Collins, H., & Evans, R. (2008). Rethinking Expertise. University of Chicago Press.

Graeber, D. (2012). Debt: The First 5,000 Years. Melville House.

Haslanger, S. (2005). What Are We Talking About? The Semantics and Politics of Social Kinds. Hypatia, 20(4), 10–26.

Jung, M.-K. (2015). Beneath the Surface of White Supremacy: Denaturalizing U.S. Racisms Past and Present. Stanford University Press.

Kihlstrom, J. F. (2018). The rediscovery of the unconscious. In J. F. Kihlstrom (Ed.), The mind, the brain, and complex adaptive systems (pp. 123–144). Routledge.

Lizardo, O. (2017). Improving Cultural Analysis: Considering Personal Culture in its Declarative and Nondeclarative Modes. American Sociological Review, 82(1), 88–115.

Lizardo, O. (2019). Specifying the “what” and separating the “how”: Doings, sayings, codes, and artifacts as the building blocks of institutions. Research in the Sociology of Organizations, 65A, 217–234.

Martin, J. L. (2011). The Explanation of Social Action. Oxford University Press.

Mueller, J. C. (2020). Racial Ideology or Racial Ignorance? An Alternative Theory of Racial Cognition. Sociological Theory, 38(2), 142–169.

Putnam, H. (1975). The Meaning of “Meaning.” In Mind, Language and Reality. Philosophical Papers, Vol. 2 (pp. 215–271). Cambridge University Press.

Rabb, N., Fernbach, P. M., & Sloman, S. A. (2019). Individual Representation in a Community of Knowledge. Trends in Cognitive Sciences, 23(10), 891–902.

Reay, M. (2010). Knowledge Distribution, Embodiment, and Insulation. Sociological Theory, 28(1), 91–107.

Rozenblit, L., & Keil, F. (2002). The misunderstood limits of folk science: an illusion of explanatory depth. Cognitive Science, 26(5), 521–562.

Sloman, S., & Fernbach, P. (2018). The Knowledge Illusion: Why We Never Think Alone. Penguin.

Swidler, A. (1986). Culture in Action: Symbols and Strategies. American Sociological Review, 51(2), 273–286.

West, C., & Fenstermaker, S. (1995). Doing difference. Gender & Society, 9(1), 8–37.

Explaining social phenomena by multilevel mechanisms

Four questions about multilevel mechanisms

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

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

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

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

Social Coordination

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

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

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

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

Transactive Memory

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

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

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

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

Ethnicity

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

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

References

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

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

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

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

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

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

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

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

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

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

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

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

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

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

Internalization and Knowledge What

As discussed in a previous post, the sociological discussion of internalization has been traditionally dominated by an emphasis on processes in which other people, via the mediation of artifacts, serve as the primary conduits via which cultural-cognitive kinds are internalized. In that respect, sociologists do not seem to make too much of an effort to differentiate internalization, or the acquisition of cultural kinds from interaction and experience in the world, from the more specific idea of socialization, or the acquisition of cultural kinds from the concerted efforts of other people (the “agents” of socialization) to try to transmit or teach them to us in some way (Berger and Luckmann 1966; Parsons 1952).

Equating internalization and socialization works well for the cultural-cognitive kinds considered in the previous discussion; in the case of beliefs and skills, internalization necessarily involves interaction with artifacts created by other people (beliefs conveyed via oral or written communications), interaction with people when they produce “live” version of such artifacts in the form of spoken words (or other overt symbols), and even the direct manipulation of the body of apprentices on the part of teachers (Downey 2014).

Interestingly, the case of belief and the case of skill are prototypical versions of two types of knowledge usually contrasted in social and cognitive science, following a classic distinction proposed by the philosopher Gilbert Ryle (2002). In Ryle’s rendering, propositional beliefs rendered as sentences in a natural language are a clear case of “knowledge that,” while skills, hard or impossible to verbalize or put in propositional form, are the prototypical case “knowledge how.” For instance, we would say, of a person who holds this belief, they think that immigrants are good for America and, of a person who commands this skill, they know how to dance Capoeira.

However, more extensive consideration of a lot of the internalized knowledge held by people reveals the existence of a large swath of internalized culture that does not quite fit the neat division between explicit propositional beliefs and skills (in terms of the nature of the kind of involved) nor does it fit the usual origin story we tell of such kinds in terms of their provenance in teachers, socialization agents, role models and the like. Take, for instance, cultural knowledge about such entities as cats, computers, houses, or camping trips. These are the cultural cognitive kinds psychologists refer to as concepts (Barsalou 1992; Machery 2009; Prinz 2004).

Concepts clearly count as a form of internalized culture but it is unlikely any socialization agents set out (or spent much effort) to teach you cats have fur, computers run on electricity, or camping trips happen in the summer and the same for the myriad of concepts you have internalized. Instead, this is knowledge that you likely “picked up,” just by living in a world containing cats, computers, and camping trips. In fact, the reason why people don’t need teachers and socialization agents to internalize that cats and birds are alive but a rock is not, is that this knowledge is taken to be so obvious that it, in the words of anthropologist Maurice Bloch (1998:22ff), it “goes without saying”; accordingly, no socialization agent would expend effort transmitting this knowledge since they presume people will pick it up on their own (saving their energies for things that are not that obvious). This means that a lot of internalized culture does not come about via any “socialization” process at least as this is traditionally conceived (Bloch 1998:23ff; Bourdieu 1990); this, in particular, seems to apply to conceptual knowledge as an internalized cultural kind.

In contrast to most propositional beliefs attaching normative, conventional, or arbitrary predicates to entities (e.g., such as “good for America” to “immigrants”), it is a necessary condition that the world is the way it is for people to internalize a lot of the conceptual knowledge they have. For instance, if you were to take a magical time machine and go back to the fourteenth century armed with your current (explicit) conceptual knowledge of what computers are and do and tried to convey it to medieval denizens by talking to them, it is likely that you would fail to transmit the concept of a computer to your interlocutors (although you might be able to transmit a number of fantastical beliefs about the mysterious entity you are calling a “computer”).

In this last respect, all of your “socialization” efforts would be for naught, because in order to internalize workable conceptual knowledge about a thing, you need to interact (directly or indirectly) with the thing the concept is about; in addition, you need to have workable conceptual knowledge about a number of other domains related to the thing (e.g., electricity and machinery in the case of computers) and about the likely situations and contexts in which the thing is likely to be found (e.g., offices) (Yeh and Barsalou 2006).

This is different from belief acquisition. For instance, I (a socialization agent) can stipulate the existence of a substance called “dilithium” and transmit to you the belief “dilithium can power a starship.” You do not need to have a working concept of dilithium, beyond the most general one (e..g, dilithium is a kind of substance), in order for you to acquire beliefs about dilithium (although you will have to have some conceptual knowledge, however vague, indirect, and metaphorically structured, about what “powering up” a technological artifact is, and what a “starship” is).

Enculturation versus Socialization

The above discussion suggests that concepts are a theoretically important cultural-cognitive kind, distinct from explicit beliefs and non-conceptual skills, that can help broaden and enrich our understanding of the different ways cognitive-cultural kinds can come to be internalized by people. This is for (at least) two main reasons.

First, the existence and pervasiveness of concepts as internalized cultural-cognitive kinds license the distinction between socialization and enculturation as routes to the internalization of cultural kinds. Most sociologists are like Zerubavel in the birthday party example offered in the previous post and use the terms interchangeably, talking about “socialized or acculturated” people. We are now in a position to make a more principled distinction. Socialization is the internalization of cultural-cognitive kinds, such as beliefs and skills, from interaction with agents who intend for us to learn explicit beliefs via direct or indirect (e.g., put them in the world in artifactual form for us to find) symbolic interaction or apprenticeship relations in which such agents coordinate, supervise, and ensure the acquisition of particular skills (e.g., walking, writing, riding a bike).

Enculturation, on the other hand, is a more general idea, referring to all forms of internalization of cultural kinds, even in cases where no explicit teachers or communicators (either human or artifactual) are involved. In contrast to socialization, where we can reconstruct a direct or indirect communicative or transmissive intention on the part of a socialization agent and directed to a socialization target (which, when successful results in internalization), with enculturation, we encounter the, initially puzzling case, of cultural internalization that seems to work by “osmosis.”

Most conceptual knowledge is not acquired via socialization; instead, the bulk of conceptual knowledge is acquired via enculturation: Non-directive processes of experience with and exposure to (solitary or with others, direct or mediated) to exemplars of the physical, artifactual, biological, or social kind in question. For instance, a lot of the conceptual knowledge about the properties of objects residing in the “middle-sized” world of cats, dogs, rocks, tomatoes, magnets, and computers (e.g., not electron, quarks, and supernovas) is acquired via enculturation (not socialization), although knowledge about implicit aspects of some of those objects, if it exists, is usually acquired via socialization (we can go to engineering school and figure how computers work from a teacher or a book). Contextual or variable knowledge about practices regarding such objects (e.g., that in this house cats stay outside) is clearly acquired by socialization, while knowledge that cats eat food, like to sleep, and can move on their own without having to be pushed around by a person (Mandler 1988), is acquired mainly via enculturation.

While a lot of (lexical) linguistic knowledge (e.g., mapping of word labels to objects) is acquired via socialization, it is important to underscore that conceptual knowledge (e.g., that cats have tails and dogs bark) is distinct from the knowledge of how to map lexical labels to objects in a natural language (Tomasello 2005). Children begin to acquire conceptual knowledge about a lot of categories before they learn the mapping between lexical items and members of that category in their native language (Bloch 1991). In the same way, grammatical linguistic knowledge is acquired via enculturation (Tomasello 2005), although a second-order version of it is re-acquired in school via socialization.

Knowledge What

Second, concepts as cultural-cognitive kinds do not quite fit Ryle’s “knowledge-that” and “knowledge-how” binary mentioned earlier. As already noted, we can have “knowledge-that” beliefs about things we have no (or very faint) concepts of (like dilithium). In addition, the hallmark of procedural knowledge (e.g., knowledge of how to ride a bike) is precisely that it is non-conceptual (Dreyfus 2005). You do not need the conceptual knowledge about bikes (e.g., that they are typically made out of metal) in order to learn how to ride one. In fact, you could theoretically lose the conceptual knowledge (e.g., via some traumatic brain injury causing selective amnesia) while retaining the practical expertise.

In this last respect, the existence of conceptual knowledge as internalized cultural-cognitive kinds, distinct from propositional and procedural knowledge, points to the possibility that Ryle’s classic distinction of know-how/know-that does not provide an exhaustive taxonomy of internalized cultural kinds, as has been presumed in previous work (Lizardo 2017). What is missing is what philosophers Peter Gardenfors and Andreas Stephens (2018; see also Stephens 2019) have recently referred to as knowledge-what; general (impersonal) knowledge about the expected properties and features of objects and events in the world. Knowledge-what is equivalent to what other theorists refer to as “conceptual knowledge” or knowledge stored in the “human conceptual system” (Barsalou 2003; Barsalou et al. 2003).

In terms of the contemporary theory of memory systems, if knowledge-how is associated with non-declarative procedural memory and knowledge-that with declarative episodic memory, then knowledge-what encompasses both non-declarative and declarative aspects of semantic memory (Stephens 2019). Accordingly, if knowledge-how is composed of the sum total of cultural-cognitive kinds internalized as skills, and knowledge-that is that composed of cultural-cognitive kinds internalized as (explicit) beliefs (and other declarative “propositional attitudes” about the world (Schwitzgebel 2013)), then knowledge-what is primarily stored in the form of concepts (although we do not need to settle on any one particular theory about the format in which concepts are stored in long term memory).

What makes conceptual knowledge distinctive from non-conceptual (procedural) or strictly propositional knowledge is the fact that it allows us to categorize, make inferences (e.g., derive new knowledge from old knowledge), and thus make reliable inductions about the properties and characteristics of the physical, biological, and social kinds that fall under the concept (Gärdenfors and Stephens 2018). In this respect, concepts stored in semantic memory seem to have both procedural (they allow us to do things) and declarative components (Parthemore 2011; Stephens 2019). Thus, if we know that an event is a “birthday party” (as with the Zerubavel example above), we can reliably guess (and expect) that cake will be served. If we know something is a cat, then we can reliably guess (and expect) that it likes to sleep, eat food, and it’s not ten feet tall.

In this last respect, it seems like Zerubavel was talking about enculturation (as an example of internalization), not socialization, if only because it would be odd to find socializing agents expending much effort “teaching” people that cakes are eaten at birthday parties; instead, parents bring out the cake since even before kids can talk (or show them picture books with birthday parties featuring cake), so by the time they can talk they expect to see cakes at birthday parties. In this respect, the presence of cake is part of the (Euro-American) concept of a birthday party (and is not a propositional belief about birthday parties although it may be that too), and people learn it via an enculturation process (although a late newcomer from a society in which something else was served on this occasion would probably have to learn it via socialization).

There are of course systematic relations between both enculturation and socialization processes, and knowledge-that and knowledge-what as internalized cultural kinds. People become encultured (exposed to a multimodal ensemble featuring people, activities, and objects in a situational context) at the same time that they are socialized; so these internalization processes are not mutually exclusive. However, since enculturation is the more general form of internalization, it follows that, even though all socialization entails enculturation, a lot of enculturation takes place absent the concerted effort or explicit attempts at teaching coming from socialization agents (Bloch 1998; Bourdieu 1990; Strauss and Quinn 1997). Just by acting pragmatically (alone or in concert with others) in a world populated by physical, biological, artifactual, and social kinds people will come to internalize a large swath of (some easy some hard or impossible to explicitly articulate) conceptual knowledge-what about those kinds.

In this last respect, it is likely that one reason why the distinction between knowledge-that and knowledge-what has not been sharply made in cultural theory has to do with the “linguistic fallacy” (Bloch 1998:23ff); this is the idea that, just because we can paraphrase conceptual knowledge using linguistic propositions (e.g., we can say that cats have tails) in belief-like form, it follows that conceptual knowledge consists of just such a collection of know-that sentences and propositions (e.g., “beliefs about” the kind the concept refers to (Bloch 1991; Strauss and Quinn 1997:51)). However, despite their many differences (Machery 2009), no contemporary theory of concepts taken as a serious contender in cognitive psychology sees them exclusively represented as a collection of sentence-like structures (although some armchair philosophical theories, such as Jerry Fodor’s “language of thought” hypothesis do).

A well-known problem with the proposal that conceptual knowledge-what can be reduced or paraphrased as a lot of “knowledge-that” statements is what the philosopher Daniel Dennett (2006) once referred to as the “frame problem.” This is the idea that the number of explicit beliefs we would have to impute to a person to try to summarize their storehouse of (multimodal, cross-contextual) conceptual knowledge what of even the simplest of “basic level” objects such as a chair is virtually infinite, exploding exponentially once we realize how much “implicit beliefs” people seem to have about the category (e.g., we would have to presume that people “know that” chairs are not made out of cheese, did not exist in the Pleistocene, do not explode five minutes after someone sits on them, are not secretly laughing behind our backs, and so on.)

Partly motivated by this (and other issues; see Prinz (2004) and Barsalou (1992)), some of the more promising accounts of concepts as internalized cultural (and cognitive) kinds, abandon lingua-form representation altogether, suggesting that conceptual knowledge consists of simulations stored in the same modality-specific format as the perceptions we have of the (physical, biological, social, etc.) kinds represented by the concept (Barsalou 1999; Clark 1997; Prinz 2004). This account is consistent with observations about cultural internalization made by ethnographers. As Bloch (1998: 25) notes, “[a]ctors’ concepts of society are represented not as strings of terms and propositions, but as governed by lived-in models, that is, models based as much in experience, practice, sight, and sensation as in language” (see also Shore (1996); Bourdieu (1990) and Strauss and Quinn (1997)); propositional beliefs that are a cultural kind distinct from concepts of. In this respect, concepts as a cultural cognitive kind, acquired via enculturation processes may represent a much more crucial aspect of people’s everyday knowledge of the world than propositional beliefs “about” the world.

One upshot of the above discussion is that we do not need three separate internalization stories for the three (broad) forms of internalized knowledge (that, how, and what). Instead, enculturation, or, the emergence of personal culture via pragmatic and bodily interaction in the world, serves as a general template, with concept acquisition being the most general form of this process, and skill acquisition and belief formation serving as special-purpose stories featuring artifact-mediated interactions with the world, typically involving other people as intentional drivers of the internalization process (“socialization”). In this respect, all cultural-cognitive kinds (e.g., concepts, skills, beliefs, etc.) are constructed and internalized via people’s activity-driven experience in the world, only a subset of which involve interaction with artifactual cultural kinds. Some cultural-cognitive kinds (e.g., concepts for animals and objects) can emerge from people’s direct interactions with other biological and physical kinds, while others (beliefs about the benefits to America that come from immigration) from people’s interactions with artifactual kinds produced by others with the intent to transmit them to us.

References

Barsalou, L. (2003). Situated simulation in the human conceptual system. Language and Cognitive Processes, 18(5-6), 513–562.

Barsalou, L. W. (1992). Frames, concepts, and conceptual fields. Lawrence Erlbaum Associates, Inc.

Barsalou, L. W. (1999). Perceptual Symbol Systems. Behavioral and Brain Sciences, 22(4), 577–609.

Barsalou, L. W., Kyle Simmons, W., Barbey, A. K., & Wilson, C. D. (2003). Grounding conceptual knowledge in modality-specific systems. Trends in Cognitive Sciences, 7(2), 84–91.

Berger, P. L., & Luckmann, T. (1966). The Social Construction of Reality: A Treatise in the Sociology of Knowledge. Doubleday.

Bloch, M. (1991). Language, Anthropology and Cognitive Science. Man, 26(2), 183–198.

Bloch, M. E. F. (1998). How we think they think: Anthropological approaches to cognition, memory, and literacy. Westview Press.

Bourdieu, P. (1990). The logic of practice. Stanford University Press.

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

Downey, G. (2014). “Habitus in Extremis”: From Embodied Culture to Bio-Cultural Development. Body & Society. http://bod.sagepub.com/content/20/2/113.short

Dreyfus, H. L. (2005). Overcoming the Myth of the Mental: How Philosophers Can Profit from the Phenomenology of Everyday Expertise. Proceedings and Addresses of the American Philosophical Association, 79(2), 47–65.

Gärdenfors, P., & Stephens, A. (2018). Induction and knowledge-what. European Journal for Philosophy of Science, 8(3), 471–491.

Lizardo, O. (2017). Improving Cultural Analysis: Considering Personal Culture in its Declarative and Nondeclarative Modes. American Sociological Review, 82(1), 88–115.

Machery, E. (2009). Doing without Concepts. Oxford University Press.

Mandler, J. M. (1988). How to build a baby: On the development of an accessible representational system. Cognitive Development, 3(2), 113–136.

Parsons, T. (1952). The superego and the theory of social systems. Psychiatry, 15(1), 15–25.

Parthemore, J. E. (2011). Concepts enacted: confronting the obstacles and paradoxes inherent in pursuing a scientific understanding of the building blocks of human thought [Doctoral, University of Sussex]. http://sro.sussex.ac.uk/id/eprint/6954

Prinz, J. J. (2004). Furnishing the Mind: Concepts and Their Perceptual Basis. MIT Press.

Ryle, G. (2002). [1949], The Concept of Mind. Chicago: The University of Chicago Press,. With an lntroduction by Daniel C. Dennett.

Schwitzgebel, E. (2013). A Dispositional Approach to Attitudes: Thinking Outside of the Belief Box. In N. Nottelmann (Ed.), New Essays on Belief: Constitution, Content and Structure (pp. 75–99). Palgrave Macmillan UK.

Stephens, A. (2019). Three levels of naturalistic knowledge. In M. Kaipainen, F. Zenker, A. Hautamäki, & P. Gärdenfors (Eds.), Conceptual Spaces: Elaborations and Applications (pp. 59–75). Springer.

Strauss, C., & Quinn, N. (1997). A cognitive theory of cultural meaning (Vol. 9). Cambridge University Press.

Tomasello, M. (2005). Constructing a Language. Harvard University Press.

Yeh, W., & Barsalou, L. W. (2006). The situated nature of concepts. The American Journal of Psychology, 119(3), 349–384

Does Labeling Make a Thing “a Thing”?

“Reality is continuous” Zerubavel (1996:426) tells us, “and if we envision distinct clusters separated from one another by actual gaps it is because we have been socialized to ‘see’ them.” This assumption, that without “socialization” an individual would experience reality as meaningless—or as William James (1890:488) said of the newborn “one great blooming, buzzing confusion”—is fairly common in sociology.

Hand-in-hand is the assumption that socialization is learning language: “It is language that helps us carve out of experiential continua discrete categories such as ‘long’ and ‘short’ or ‘hot’ and ‘cold’” (Zerubavel 1996:427). Boiled down, this view of socialization is a very standard “fax” or “downloading” model in which the socializing agents “install” the language in its entirety into the pre-socialized infant. The previously chaotic mass of reality is now lumped and only then becomes meaningful to the infant. Furthermore, because the socializing agents have the same language installed, the world is lumped in the same (arbitrary) way for them as well. This is what allows for intersubjective experience.

As Edmund Leach puts it:

“I postulate that the physical and social environment of a young child is perceived as a continuum. It does not contain any intrinsically separate ‘things.’ The child, in due course, is taught to impose upon this environment a kind of discriminating grid which serves to distinguish the world as being composed of a large number of separate things, each labeled with a name. This world is a representation of our language categories, not vice-versa.” Leach (1964:34)

Where did this assumption come from?

Generally, Durkheim’s Elementary Forms is cited to shoulder these assumptions. According to the introduction, the problem to be solved is that an individual’s experience was always particular: “A sensation or an image always relies upon a determined object, or upon a collection of objects of the same sort, and express the momentary condition of a particular consciousness” (Durkheim 1995:13). As a result of this, Durkheim attempts to argue, humans cannot have learned the basic “categories” by which we think—like cause, substance, class, etc.—from individual experience, not because it is continuous, but rather always discontinuous and unique. The alternative was that the categories exist “a priori” which, regardless as to whether this apriorism is nativist or idealist, Durkheim found an unsatisfying solution.

While there is of course much debate about this, Durkheim posited a sociogenesis of these basic categories from the organization of “primitive” societies which “preserves all the essential principles of apriorism… It leaves reason with its specific power, accounts for that power, and does so without leaving the observable world” (Durkheim 1995:18). After their genesis, however, there was no need to re-create them: “in contrast to Kant, Durkheim argued that these categories are a concrete historical product, not an axiom of thought, but in contrast to Hume, he acknowledged that these categories are as good as a priori for actual thought, for they are universally shared” (Martin 2011:119).

Once generated at the moment human society first formed, these categories had to simply be passed down from generation to generation. It seems intuitive that language would be the mechanism of transmission: “The system of concepts with which we think in every-day life is that expressed by the vocabulary of our mother tongue; for every word translates a concept” (Durkheim 1995:435).

It is here where we also get the more “relativist” interpretation of Elementary Forms in which each bounded “culture” can live in a distinct reality delimited by each language. Furthermore, while Durkheim’s argument is about the most generic (and universal) concepts of human thought, Zerubavel argues that our perception of the world is changed by highly specific labels: “As we assign them distinct labels, we thus come to perceive ‘bantamweight’ boxers and ‘four-star’ hotels as if they were indeed qualitatively different from ‘featherweight’ boxers and ‘three-star’” (1996:427 emphasis added).

We see a similar notion in The Social Construction of Reality, to which Zerubavel’s work is indebted: “The language used in everyday life continuously provides me with the necessary objectifications and posits the order within which these make sense…” (Berger and Luckmann [1966] 1991:35 emphasis added).

Is such an assumption defensible?

To outline the notion up to this point: First, we imagine the unsocialized person— usually, but not necessarily, the pre-linguistic infant. Their senses are providing information about the world to their brain, but it is either a completely undifferentiated mass or hopelessly particular from one moment to the next. In either case, their experience has no meaning to them. Second, the unsocialized person somehow learns that a portion of their experience has a “label” or “name” and it thus can be both lumped together and split from the rest of experience, and only then becomes meaningful. Third, on this basis, each language forms a kind of “island” or “prison-house” of meaning, carving up the undifferentiated world in culturally-unique ways, such that things “thinkable” in one language are “unthinkable” in others. (I will set aside the problems of how exactly these labels are internalized.)

Buried within this general notion, are four positions: (1) learning a label is necessary and sufficient; (2) learning a label is necessary, not sufficient; (3) learning a label, is not necessary, but is sufficient; (4) learning a label is not necessary, but common evidence that other processes have made a thing “a thing.” For Leach and Zerubavel (and some interpretations of Durkheim), it appears to be (1): once you have a label, boom! Then, and only then, you can perceive a thing. For Berger and Luckmann, it is occasionally (1) and (2) and other times (3) and (4). For example, Berger writes in The Sacred Canopy ([1967] 2011:20):

The objective nomos is given in the process of objectivation as such. The fact of language, even if taken by itself, can readily be seen as the imposition of order upon experience. Language nomizes by imposing differentiation and structure upon the ongoing flux of experience. As an item of experience is named, it is ipso facto, taken out of this flux of experience and given stability as the entity so named.

That’s about as extreme as it gets. However, in The Social Construction of Reality, a slightly tempered view is taken:

The cavalry will also use a different language in more than an instrumental sense… This role-specific language is internalized in toto by the individual as he is trained for mounted combat. He becomes a cavalryman not only by acquiring the requisite skills but by becoming capable of understanding and using this language. (Berger and Luckmann [1966] 1991:159 emphasis added)

Although there are other parts of The Social Construction of Reality which privilege language above all (and disregarding the “in toto”), here it suggests that vocabulary is part of a practice. In other words, “an angry infantryman swears by making reference to his aching feet,” because of the experience of “aching feet,” and “the cavalryman may mention his horse’s backside,” again because of his experience with horses. Without their role-specific language, the infantryman would still be able to perceive “aching feet” and the cavalryman would know a “horse’s backside.” On the contrary, these terms are meaningful to them—and useful as metaphors—because of their experiences, rather than vice versa.

For this to be the case, however, we must reject the notion that, without socialization (as the internalization of language), perception would amount to “one great blooming, buzzing confusion.” Rather, reality has order without interpretation and we can directly experience it as such. Even infants perceive a world that is pre-clumped, and early concept formation precedes language acquisition and follows perceptual differentiation (Mandler 2008:209):

…between 7 and 11 months (and perhaps starting earlier) infants develop a number of [highly schematic] concepts like animal, furniture, plant, and container… ‘basic-level’ artifact concepts such as cup, pan, bed and so on are not well-established until the middle of the second year, and natural kind concepts such as dog and tree tend to be even later… Needless to say, this is long after infants are fully capable of distinguishing these categories on a perceptual basis.

Labels likely play a greater role later on in the process of socialization (perhaps especially during second socialization). In already linguistically-competent people, labels can be used to select certain features of perceived objects and downplay others, exacerbate differences between similar objects, or group perceptually distinct objects into one category (Taylor, Stoltz, and McDonnell 2019). However, this does not mean that labels alone literally “filter” our perception—indeed evidence shows (Alilović et al. 2018; Mandler 2008) adults and infants perceive the world first through an unfiltered sweep, and after perceiving, we “curate” the information through automatic or deliberate prediction and attention. Language may make it faster, easier, and therefore more likely to think about some things over others, but this does not render something unthinkable or imperceptible (Boroditsky 2001). Likewise, it is unlikely that naming something is necessary and sufficient to make a thing “a thing.”

References

Alilović, Josipa, Bart Timmermans, Leon C. Reteig, Simon van Gaal, and Heleen A. Slagter. 2018. “No Evidence That Predictions and Attention Modulate the First Feedforward Sweep of Cortical Information Processing.” bioRxiv 351965.

Berger, Peter L. [1967] 2011. The Sacred Canopy: Elements of a Sociological Theory of Religion. Open Road Media.

Berger, Peter L., and Thomas Luckmann. [1966] 1991. The Social Construction of Reality: A Treatise in the Sociology of Knowledge. Penguin.

Boroditsky, L. 2001. “Does Language Shape Thought? Mandarin and English Speakers’ Conceptions of Time.” Cognitive Psychology 43(1):1–22.

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

James, W. 1890. The Principles of Psychology, Vol 1. Henry Holt.

Mandler, J. M. 2008. “On the Birth and Growth of Concepts.” Philosophical Psychology.

Martin, John Levi. 2011. The Explanation of Social Action. Oxford University Press, USA.

Taylor, Marshall A., Dustin S. Stoltz, and Terence E. McDonnell. 2019. “Binding Significance to Form: Cultural Objects, Neural Binding, and Cultural Change.” Poetics Volume 73:1-16

Zerubavel, Eviatar. 1996. “Lumping and Splitting: Notes on Social Classification.” Sociological Forum 11(3):421–33.

Theory Diagrams of Motley Kinds

Over at The Junkjard, Felipe De Brigard has a very nice summary of work from the Imagination and Modal Cognition lab on the phenomenon of episodic counterfactual thinking (eCFT). The post is well worth reading, so will not get into a lot of details here (it is based on a relatively longer piece forthcoming at Psychological Science). However, some aspects of the post dovetails with some recent discussions we have had here, especially on thinking about representing “motley” kinds (such as cultural kinds).

In essence, motley kinds are natural kinds that decompose into sub-kinds each endowed with distinct (but possibly overlapping) properties. In the case of cultural kinds, this is what I have referred to as compositional pluralism; namely, the claim that cultural kinds come in different flavors and that it is important to both distinguish between the different flavors but also come up with a way to represent what they have in common.

It is clear that one of the consequences of more fully incorporating neuroscience into the cognitive social science manifold has been the discovery that a lot of things that were treated as unitary (non-motley) kinds, have turned out to be motley. This happened pretty early on with memory, so that today it is completely uncontroversial to speak of memory as a motley kind composed of distinct types, such as declarative versus non-declarative memory .

The same (and this will be the subject of a future post) happened to concepts, which were traditionally treated as unitary kinds in philosophy and even the first wave of psychological research initiated by the pioneering work of Eleanor Rosch and Carolyn Mervis. However, as most forcefully argued by the philosopher Edouard Machery (2009) in Doing without Concepts, the weight of the evidence in cognitive psychology points to the conclusion that concepts are a motley kind, and come in at least three flavors: Prototypes, exemplars, and theories, each endowed with distinct (but possibly overlapping) properties and causal powers.

Some people are distraught when something they thought of as a unitary kind is shown to be a motley kind. This distress sometimes takes the form of accusations of “conceptual incoherence”—a common occurrence in the case of cultural kinds (e.g., Smith 2016)—or (e.g., in the case of Machery with regard to concepts) calls for elimination of the kind on account of its very motleyness.

Although I will not get into a detailed defense of this argument, my own position is that both of these reactions are unwarranted. The first one puts the cart before the horse, focusing on an epistemic problem (“conceptual incoherence”) as if it was an issue of having faulty beliefs about the world. But if a given kind is in fact motley (a feature of the world not our representations) then conceptual “incoherence” is actually more faithful to the structure of the world than ersatz or artificially imposed conceptual “coherence.”

The call to elimination on the other hand, as has already been noted by others (e.g., Taylor and Vickers 2017; Weiskopf 2008) is surely an overreaction. Especially given the fact that a whole lot of kinds that have been thought of as unitary (in both the natural and special sciences) are turning out to be, upon further reflection, motley. In that respect following the heuristic “eliminate a kind if it turns out to be motley” would result in the disposal of most of the core phenomena across a number of scientific disciplines. So perhaps the problem is not with the world, but with philosophical theories of natural kinds that impose unity by fiat.

Another consideration against elimination is simply that the discovery of motley kinds in other fields (such as the cognitive neuropsychology of memory) has actually resulted in an efflorescence of research and clarification of how basic processes work and how core phenomena are generated. In other words, we have better accounts of memory and how it works now that we recognize it as a motley kind. This recognition has not resulted in “conceptual incoherence,” confusion, or cacophony. Although Machery (2009) does mount a strong case favoring the conclusion that confusion and cacophony have ruled the study the study of concepts in psychology historically, this outcome is not fore-ordained nor can it directly be laid at the steps of the facts that concepts are a motley kind.

Additionally, as noted in De Brigard’s post and in a previous post, when it comes to memory we are now discovering, in a fractal-like sense, that some of the sub-kinds (such as episodic memory) that were thought of as unitary are themselves motley! Such, that as Rubin (2017) notes in a recent contribution, we may be looking at a multiplicity of different things that have varying levels of resemblance to what we typically mean by (traditional) episodic memory.

De Brigard’s work fits into this approach, noting that the notion of (mnemonic) mental simulation is most likely a motley kind, which includes traditionally considered episodic memory (mentally simulating personal events from the past that actually occurred), but also episodic future thinking (mentally simulating personal events in the future that could occur) and semantic counterfactual thinking (thinking about non-actual but possible events or states of affairs not connected to personal experience). De Brigard argues for the importance of episodical counterfactual thinking (eCFT), mentally simulating events in the past that could have occurred, as its distinct kind of memory/simulation phenomenon.

Theoretically, the payoff of this type of motley decomposition is that it allows to both distinguish but also theoretically unify some key phenomena (e.g., remembering and simulating) while recasting things that were previously thought of as oppositions or discrete categories (e.g., “semantic” versus “episodic”) as ends in a bipolar continuum. This expands the range of theory in that a dimensional representation can accommodate “quirky” types of memory phenomena (e.g., déjà vu) by placing them in a multidimensional property space that disaggregates properties (e.g., explicitness and self-reference) that would otherwise be run together (Rubin 2017).

De Brigard thus assimilates eCFT into memory’s motley crew by placing it in a multidimensional property space distinguish a “Future/Past” dimension from an “Episodic/Semantic” one, overlaid with a third “modal” continuum anchored at “impossible” on the one end (a giant squid falling from the sky on New York City) to the actual on the other end, with the mere possible in the middle. We can thus define eCFT as the type of memory phenomenon combining high levels of “pastness” and “episodicness” but located in the “possible” region of the modality dimension. This is represented using the following diagram:

Which bears some resemblance to Rubin’s dimensional diagram of memory phenomena:

The main difference is that Rubin is selecting on De Brigard’s “pastness” pole and decomposes the “episodic” dimension into a self-reference plus “eventness.” The details of the relationships between these two representations are not as important (since De Brigard is subsuming memory under the larger category of simulation phenomena) as the fact that both De Brigard and Rubin, after acknowledging the motley nature of the phenomena they are dealing with, have to also then come up with a way to represent such motleyness, and both resort to using what Gordon Brett has referred to in a previous post as “theory diagrams.”

Which (finally) brings me to my point. Insofar (as already noted) as, both cognitive scientists studying memory and social scientists studying culture come to terms with (and make peace with) the motley nature of the particular kinds they study (e.g., memory and culture) then these types of diagrammatic representations go from being a mere addendum to pivotal tools with which to engage in theorizing. The reason for this is that, as noted in a previous post, the choice of diagrammatic representation (e.g., hierarchical versus dimensional) encodes substantive (but implicit) theoretical assumption about how the different subkinds relate to one another and whether they are conceived as having disjoint or partially overlapping properties. Theory diagrams, as Brett noted, encode thinking.

In addition, as noted by the difference between Rubin and De Brigard’s theory diagram, different ways of representing dimensions may also lead different insights or accommodate finer grained distinction. Rubin’s more conventional way of representing dimensions (as orthogonal Cartesian axes) tops out at three dimensions (in terms of visual representation). De Brigard innovates by rendering the third dimension as a “penumbra” (Dustin Stoltz‘s preferred term) like continuum spread within the Cartesian plane. This type of representation is particularly useful to represent dimensions with very fine gradation. In particular, as noted in previous posts, a lot of cultural kinds do differ along the “distribution” dimension and such a property fits very well with a De Brigard style representation.

Following this lead, and transforming my initial Rubin-like three-dimensional diagram of cultural kinds into a De Brigard diagram for cultural kinds looks like this:

There are several advantages to this type of representation. First the property of distribution is represented with a visual image-schema that most closely correspond to its fine-grained continuous nature. Second, the insertion of the distribution dimension into the center of the diagram “frees up” a cultural dimension, so that we could think of a taxonomy of cultural kind that would combine this representation with the previous Rubin-like one by including a third dimension thus allowing us to “up the motley” if such a thing were to be required. Overall, thinking seriously about the motley nature of cultural and other kinds, underscores the importance of having illuminating ways of representing such diversity. The work of representation and taxonomic ordering itself then can serve as a way to theorize the kind in question in ways that may lead to novel insights.

References

Machery, Edouard. 2009. Doing without Concepts. Oxford University Press.

Rubin, David C. 2019. “Placing Autobiographical Memory in a General Memory Organization.” Pp. 6–27 in The organization and structure of autobiographical memory, edited by J. Mace. Oxford University Press.

Smith, Christian. 2016. “The Conceptual Incoherence of ‘Culture’ in American Sociology.” The American Sociologist 47(4):388–415.

Taylor, Henry and Peter Vickers. 2017. “Conceptual Fragmentation and the Rise of Eliminativism.” European Journal for Philosophy of Science 7(1):17–40.

Weiskopf, Daniel Aaron. 2008. “The Plurality of Concepts.” Synthese 169(1):145.

Habitus and Learning to Learn: Part III

Language, Habitus, and Cultural Cognition

The recasting of habitus as a neuro-cognitive structure conducive to learning opens up promising avenues otherwise foreclosed in traditional cultural theory (see here and here for previous discussion). However, it also opens up some analytical difficulties, especially when it comes to the role of language and linguistic symbols in cultural cognition. Two observations deserve to be made in this respect.

First, language (and linguistic symbols) are the products of habitus; yet, the underlying procedural capacities productive of language (as practice) and linguistic symbols (as objectified products) cannot themselves be linguistic. This is actually a good thing. If external linguistic symbols were the product of a set of internal structures that also had the status of language-like symbols, we would get ourselves into an infinite regress, as we would have to ask what establishes the meaning of those symbols. This is a version of Harnad’s (1990) “symbol grounding” problem, as this is known in cognitive science and artificial intelligence.

As both Wittgenstein and Searle have proposed in different ways, the only way to forestall this regress is to posit a non-representational, non-symbolic “background” where the buck stops. This backgground is then generative of structures that end up having representational and symbolic properties (such as linguistic symbols). I propose that the neuro-cognitive habitus is such a “background” (Hutto 2012), as it was precisely to deal with this problem in the sociology of knowledge that led Bourdieu to resort to this (ironically scholastic) construct (Lizardo 2013).

Do We Think “With” Language?

Second, it appears to us (phenomenologically) that we think using (or via the medium) of language. That is, thought presents itself as a sort of “internal conversation” happening using internal linguistic symbols which may even have the same dialogical structure of dyadic or interactive conversations we have with others (Archer 2003). In fact, in the symbolic interactionist/pragmatist tradition of Mead and in the “activity theory” of Vygotsky, interactive or dialogic conversation comes first, and internal conversations with ourselves later. From this perspective, the origins of the self (conceived as a symbolic representation the agent constructs of themselves) are both dialogic, linguistic, and even “semiotic” (Wiley 1994).

Insofar as the habitus makes possible our direct, embodied engagement with the world, then it is the locus of thinking or at least a type of thinking that allows for practice, action, and problem-solving. The problem is that the kind of thinking that happens via language does not seem to have the properties required for the “online” control of action and practical engagement with the world (Jeannerod 2001). If habitus engages a particular type of thinking, and even if there is a type of “cultural-cognition” happenning via habitus, then it has tobe a sort of non-linguistic cultural cognition.

This means we need to make conceptual space for a type of cognition that still deserves the label of thinking, that is affected by culture and experience, but that is not linguistic in its essence or mode of functioning. The basic proposal is that this is the base-level non-linguistic cultural cognition is made possible by habitus, and that the most substantial cultural effects on the way we think happen because culture affects this non-declarative procedural type of thinking (Cohen and Leung 2009).

From the perspective of traditional lines of cultural theory having long roots in sociology and anthropology, suggesting the existence of a type of thinking that does not rely on language, and much less making this type of thinking more basic than the linguistic one, is an odd proposal (Bloch 1986). In the standard approach, culture is equated with language, thinking is equated with language use, and cultural effects on cognition are reduced to the impact of cultural patterns in the way we use language to make sense of the world and to talk to ourselves, and others (Biernacki 2000).

A neural recasting of habitus reminds us that, while culture also affects the way that we use language to think (Boroditsky 2001), insofar linguistic cognition is grounded on non-linguistic cognition, equating the entirety of culture’s effects on thinking to its impact on the way we use language to think “offline” when decoupled from action in the world would be an analytic mistake.

Two Ways of Engaging the World

As now well-established by work in the dual-process framework in social and cognitive psychology (Lizardo et al. 2016), we can distinguish between two ways in which culture-driven cognition (or “culture in thinking”) operates. One relies on the use and manipulation of explicit symbolic tokens that can be combined in a linear order into higher-order structures, such as the sentences of a natural language. These linguistic symbols have the potential to stand in arbitrary relations to the things that they represent. This type of cognition is serial, slow, and in many ways, “cognitively costly” (Whitehouse 2004:55).

The habitus does not typically rely on this type of linguistic, sentential processing to “get action” in the world (Glenberg 1997). Insofar as the habitus shapes and produces culture, the role of linguistic symbols in cultural analysis has to be rethought (Lizardo et al. 2019). One premise that is undoubtedly on the wrong track is that personal culture embodied in habitus is, in its essence, linguistic or is primarily symbolic in a quasi-linguistic sense (Lizardo 2012).

In its place, I propose that habitus operates at a non-linguistic level. But what exactly does this entail? In contrast to the linguistic theory of internalized personal culture, the habitus relies on cognitive resources that aer imagistic, perceptual and “analog.” The neural structures constitutive of habitus learn (and thus “internalize” culture) by extracting higher-order patterns from the world that are meaningful at a direct experiential level. The linkages between these patterns are not arbitrary but are constrained to be directly tied to previous experience, so that they can be used to deal successfully with subsequent experiences sharing similar structure (Bar 2007).

In this last respect, the habitus recognizes connections between practical symbolic structures when these are compatible with its experiential history. Habitus uses the structural features of previous experience, directly linked to our status as embodied, spatial and temporal creatures, to bring order, predictability, and regularity to the most diverse action domains (Bourdieu 1990a).

The (Emergence of) the Scholastic Point of View

In a neural reconceptualization of habitus, language, linguistic structures and linguaform modes of expression are put in their place as supported by analog structures derived from experience. In fact, as shown in modern cognitive linguistics, most of the features of spoken language usually thought of as being endowed with some sort of mysterious, autonomous and ineffable “linguistic” or “semiologic” quality are grounded in the type of embodied, directly perceptual encoding and processing of meanings that is characteristic of habitus (Langacker 1991).

The status of modes of cognitive processing highly reliant on language in the cognitive economy of the social agent and the cultural economy of the social world has been overblown in social and cultural theory (using the misleading imprimatur of Ferdinand De Saussure). A neural recasting of habitus as a learning to learn structure reminds us that the foundations of meaning and culture are non-linguistic, non-propositional, non-sentential, and in a strong sense not symbolic, since they retain an intuitive, easily recoverable perceptual logic grounded in non-discursive forms of thinking, perception, and activity (Bloch 1991).

How Habitus Keeps Track of Experience

Following a connectionist rethinking of the notion of mental representation proposed in the previous post, I propose that the habitus “stores” experiential traces in terms of what has been referred to as what the philosopher Andy Clark has referred to as “super-positional storage; “[t]he basic idea of superposition is straightforward. Two representations are superposed if the resources used to represent item 1 are [at least partially] coextensive with those used to represent item 2” (Clark 1993: 17).

This observation carries an important analytical consequence, insofar as the dominant theory of culture today—the linguistic or semiotic theory—tacitly presupposes that the way in which cultural information is stored by persons resembles and is constrained to match those modes of storage and representation that are characteristic of linguistic symbols. This includes, amodality (the non-analogic nature of representational vehicles) and partial separability of the conceptual resources that are devoted to represent different slices of experience. For instance, under the standard model there is little (if no) overlap between the underlying conceptual resources used to represent the (more abstract) notion of “agency” and the (more concrete) notion of “movement.”

But if habitus uses overlapping resources to capture the structure of experience, then it must encode similarities in experiential content directly and thus arbitrariness is ruled out as a plausible encoding strategy: “[t]he semantic…similarity between representational contents is echoed as a similarity between representational vehicles. Within such a scheme, the representations of individual items is nonarbitrary” (Clark 1993: 19). This means that the habitus will attempt to deal with more abstract categories removed from experience and linked to seemingly arbitrary non-linguistic symbols by mapping them to less arbitrary categories linked to experience. In this respect, there will be substantial overlap between the conceptualization of freedom and movement, with the latter serving as the ground providing semantic support for our thinking about the former (Glenberg 1997).

This means that whatever strategic (from a cognitive viewpoint) structural signatures are found in the relevant experiential domain, will have an analogue in the structural representation of that domain that comes to be encoded in the neural structure of habitus. Here, the structure of the underlying neural representation is determined by experience. In the traditional account, the experience is “neutral” and some exogenous cultural grid, with no necessary relation to experience is imposed on this sensory “flux.” This is what Martin (2011) has referred as “the grid of perception” theory of culture.

The neural recasting of habitus offered here provides an alternative to this approach, which highlights the primary role experience without subordinating it to a “higher” order set of cultural categories, standing above (and apart) from experience.

Natural Born Categories

As noted, the habitus stores traces of long-term procedural knowledge in the synaptic weights coding for the correlated features of the objects, events and persons repeatedly encountered in our everyday dealings. The ability of habitus to extract the relevant structural and statistical features from experience (and only these), along with the super-positional encoding of experiential information, leads naturally to the notion of habitus as a categorizing engine, in which categories take prototype structure, with central (exemplar) members (sharing most of the relevant features) toward the center and less prototypical members in the periphery. The extraction of prototype-based categories via habitus allows us to understand and act upon experiential domains sharing similar structural features using overlapping cognitive resources.

In addition, whenever a given slice of experience comes to recurrently present the agent with the same set of underlying regularities, a general “category” will be extracted by the habitus. This category, comprising both entity (object) and event (process) prototypes, will be composed of contextually embodied features corresponding to those given by experience. At the same time they are capable of being transferred (“transposed”) to domains of experience that share similar structural features. “Schematic transposition” is thus a natural consequence of the way habitus is transformed by, and subsequently organizes, experience.

References

Archer, M. S. 2003. Structure, Agency and the Internal Conversation. Cambridge University Press.

Bar, M. (2007). The proactive brain: using analogies and associations to generate predictions. Trends in cognitive sciences, 11(7), 280-289.

Biernacki, Richard. 2000. “Language and the Shift from Signs to Practices in Cultural Inquiry.” History and Theory 39(3):289–310.

Bloch, Maurice. 1986. “From Cognition to Ideology.” Pp. 21–48. in Knowledge and Power: Anthropological and Sociological Approaches, edited by R. Fardon. Edinburgh: Scottish University Press.

Bloch, Maurice. 1991. “Language, Anthropology and Cognitive Science.” Man 26(2):183–98.

Bourdieu, Pierre. 1990a. The Logic of Practice. Stanford University Press.

Bourdieu, Pierre. 1990b. “The Scholastic Point of View.” Cultural Anthropology: Journal of the Society for Cultural Anthropology 5(4):380–91.

Clark, Andy. 1993. Associative Engines: Connectionism, Concepts, and Representational Change. MIT Press.

Cohen, Dov and Angela K. Y. Leung. 2009. “The Hard Embodiment of Culture.” European Journal of Social Psychology 39(7):1278–89.

Glenberg, Arthur M. 1997. “What Memory Is for: Creating Meaning in the Service of Action.” The Behavioral and Brain Sciences 20(01):41–50.

Harnad, Stevan. 1990. “The Symbol Grounding Problem.” Physica D. Nonlinear Phenomena 42(1):335–46.

Hutto, Daniel D. 2012. “Exposing the Background: Deep and Local.” Pp. 37–56 in Knowing without Thinking: Mind, Action, Cognition and the Phenomenon of the Background, edited by Z. Radman. London: Palgrave Macmillan UK.

Jeannerod, M. 2001. “Neural Simulation of Action: A Unifying Mechanism for Motor Cognition.” NeuroImage 14(1 Pt 2):S103–9.

Joas, Hans. 1996. The Creativity of Action. University of Chicago Press.

Langacker, R. W. 1991. Foundations of Cognitive Grammar: Descriptive Application. Vol. 2. Stanford: Stanford University Press.

Lizardo, O. 2012. “Embodied Culture as Procedure: Cognitive Science and the Link between Subjective and Objective Culture.” Habits, Culture and Practice: Paths to Sustainable.

Lizardo, Omar. 2013. “Habitus.” In Encyclopedia of Philosophy and the Social Sciences, edited by Byron Kaldis, 405–7. Thousand Oaks: Sage.

Lizardo, O. 2016. “Cultural Symbols and Cultural Power.” Qualitative Sociology. https://link.springer.com/content/pdf/10.1007/s11133-016-9329-4.pdf.

Lizardo, Omar, Robert Mowry, Brandon Sepulvado, Dustin S. Stoltz, Marshall A. Taylor, Justin Van Ness, and Michael Wood. 2016. “What Are Dual Process Models? Implications for Cultural Analysis in Sociology.” Sociological Theory 34(4):287–310.

Lizardo, Omar, Brandon Sepulvado, Dustin S. Stoltz, and Marshall A. Taylor. 2019. “What Can Cognitive Neuroscience Do for Cultural Sociology?” American Journal of Cultural Sociology 1–26.

Lizardo, Omar and Michael Strand. 2010. “Skills, Toolkits, Contexts and Institutions: Clarifying the Relationship between Different Approaches to Cognition in Cultural Sociology.” Poetics 38(2):205–28.

Martin, John Levi. 2011. The Explanation of Social Action. Oxford University Press.

Whitehouse, Harvey. 2004. Modes of Religiosity: A Cognitive Theory of Religious Transmission. New York: AltaMira Press.

Wiley, Norbert. 1994. The Semiotic Self. Chicago: University of Chicago Press.

Categories, Part III: Expert Categories and the Scholastic Fallacy

There’s a story — probably a myth — about Pythagoras killing one of the members of his math cult because this member discovered irrational numbers (Choike 1980). (He also either despised or revered beans).

Screenshot from 2019-05-20 08-40-04.png — “Oh no, fava beans.” ~Pythagoras (Wikimedia Commons)

The Greeks spent a lot of time arguing about arche, or the primary “stuff.” Empedocles argued that it was the four elements. Anaximenes thought it was just air. Thales thought it was water. Pythagoras and his followers figured it was numbers (Klein 1992, page 64):

They saw the true grounds of the things in this world in their countableness, inasmuch as the condition of being a “world” is primarily determined by the presence of an “ordered arrangement” — [which] rests on the fact that the things ordered are delimited with respect to one another and so become countable.

For the Pythagoreans the clean, crisp integers were sacred because they conveyed a harmony — an orderedness — and there is an undeniable allure to this precision. (Indeed, such an allure that Pythagoras and his followers were driven to do some very strange things.)

Looking at even simple arithmetic, it does seem obvious that classical categories do in fact exists: there is a set of integers, a set of odd numbers, a set of even numbers, and so on. If we continue to follow this line of thought to pure mathematics in general, there is an almost mystical, quality of the “objects” of this discipline.

When thinking about mathematical objects like geometric forms, however, there is a fundamental difference between squares or circles or triangles as understood in our daily life (i.e. as having graded similarities to certain exemplar shapes we likely learned about in grade school) and the kind of perfectly precise shapes in theoretical geometry. That is, as far as we know, a perfect circle does not exist in nature (even though an electron’s spin and neutron stars are pretty damn close), nor has humankind been able to manufacture a perfect shape.

And this is the main point: precision is weird. If “crispness” is really only found in mathematics (and pure mathematics at that), then we should be skeptical of the analytical traditions’ use of discrete units as an analogy for knowledge in general.

But, sometimes, thinking with classical categories is useful.

Property Spaces

While we can be skeptical of the Chomskyan program presuming syntactical units must necessarily be classical categories, this does not mean we can never proceed as if phenomena could be divided into crisp sets.

Theorists commonly make something like “n by n” tables, typologies, or more technically, property spaces — for the classic statement see Lazarsfeld (1937) and Barton (1955), but this is elaborated in (Ragin 2000, page 76-85), Becker (Becker 2008, page 173-215), and most extensively in chapters 4, 5, and 6 of Karlsson and Bergman (2016). In this procedure, the analyst outlines a few dimensions that account for the most variation in their empirical observations. This is essentially “dimension reduction,” as we take the inherent heterogeneity (and particularity) of social experience and simplify this into the patterns that are the most explanatory (if only ideal-typical).

For example, Alejandro Portes and Julia Sensenbrenner (1993) tell us that there are four sources of social capital (each deriving conveniently from the work of Durkheim, Simmel, Weber, and Marx and Engels, respectively). These four sources are then grouped into those that come from “consummatory” (or principled) motivations and those that come from “instrumental” motivations. Thus the “motivation” is the single dimension that divides our Social Capital property space into a Set A and a Set B: either resources are exchanged because of the actor’s own self-interest, or not. More often, however, these basic property spaces based on simple categorical distinctions are the starting point for more complex (or “fitted”) property spaces.

Consider Aliza Luft’s excellent “Toward a Dynamic Theory of Action at the Micro Level of Genocide: Killing, Desistance, and Saving in 1994 Rwanda.” Luft begins with a critique of prior categorical thinking: “Research on genocide tends to pregroup actors—as perpetrators, victims, or bystanders—and to study each as a coherent collectivity (often identified by their ethnic category)” (Luft 2015, page 148). Previously, analysts explained participation in genocide in one of four ways: (1) members of the perpetrating group were obedient to an authority, (2) responding to intergroup antagonism, (3) succumbing to intragroup norms or peer pressure, (4) and finally, ingroup members dehumanize the outgroup. While all are useful theories, she explains, they are complicated by the empirical presence of behavioral variation. That is, not everyone associated with a perpetrating group engages in violence at the same time or consistently throughout a conflict (and may even save members of the victimized group).

What she does to meet this challenge is to add dimensions to a binary property space which previously consisted of a group committing murder and a group being murdered. Focusing on the former, she notes that (1) not everyone in that group does actually participate, (2) some of those who did (or did not) participate eventual cease (or begin) participating, (3) some of those who did not participate not only desisted but also actively saved members of the outgroup. Taking this together, we arrive at a property space that can be presented by the spanning tree shown above. Luft then outlines four mechanisms that explain “behavioral boundary crossing.”

In this case, previous expert categories lead to an insufficient explanation for the perpetration of genocide, and elaboration proved necessary. Attempting to create classical categories — with rules for inclusion and exclusion and the presumption of mutual exclusivity in which all members are equally representative — is likely a necessary step in the theorizing process. Much of the work of developing theory, however, is not just showing that these categories are insufficient (because, of course, they are), but rather pointing out where this slippage is leading to problems in our explanations, and how they can be mended, as Luft does.

The Scholastic Fallacy

Treating data or theory as if they can be cleanly divided into crisp sets is like the saying “all models are wrong, but some models are useful.” But taking for granted these distinctions can also lead analysts to commit the “scholastic fallacy.”

This is when the researcher “project[s] his theoretical thinking into the heads of acting agents…” (Bourdieu 2000, page 51). This, according to Bourdieu, was a key folly of structuralism: “[Levi-Strauss] built formal systems that, though they account for practices, in no way provide the raison d’etre of practices” (Bourdieu 2000, page 384). This seems especially obvious for categories, as discussed in my previous two posts. It is one thing to say people can be divided into X group and Y group for Z reasons, and it is another to say people do divide other people in X group and Y group for Z reasons (see Martin 2001, or more generally Martin 2011)

Categorizing for the “acting agent” is not a matter of first learning rules and then applying them to demarcate the world into mutually exclusive clusters. It is, for the most part, a matter of simply “knowing it when I see it” — a skill of identifying and grouping that we have built up through the accrued experience of redundant patterns encountered in mundane practices. Generally, rules, if they are used, are produced in post hoc justifications of our intuitive judgment about group memberships. It is here, however, where expert discourse is likely to play the largest role in lay categorizing: as a means to justify what we already believe to be the case.

This is not to say “non-experts” cannot or do not engage in this kind of theoretical thinking about categories. But, again Bourdieu points out, most people do not have the “leisure (or the desire) to withdraw from [the world]” so as to think about it in this way (Bourdieu 2000, page 51). More importantly, relying on expert categories for most of the tasks in our everyday lives would not be very useful because categorizing is foremost about reducing the cognitive demands of engaging with an always particular and continuously evolving reality.

References

Barton, Allen H. 1955. “The Concept of Property-Space in Social Research.” The Language of Social Research 40–53.

Becker, Howard S. 2008. Tricks of the Trade: How to Think about Your Research While You’re Doing It. University of Chicago Press.

Bourdieu, P. 2000. Pascalian Meditations. Stanford University Press.

Choike, James R. 1980. “The Pentagram and the Discovery of an Irrational Number.” The Two-Year College Mathematics Journal 11(5):312–16.

Karlsson, Jan Ch and Ann Bergman. 2016. Methods for Social Theory: Analytical Tools for Theorizing and Writing. Routledge.

Klein, Jacob. 1992. Greek Mathematical Thought and the Origin of Algebra. Courier Corporation.

Lazarsfeld, Paul F. 1937. “Some Remarks on the Typological Procedures in Social Research.” Zeitschrift Für Sozialforschung 6(1):119–39.

Luft, Aliza. 2015. “Toward a Dynamic Theory of Action at the Micro Level of Genocide: Killing, Desistance, and Saving in 1994 Rwanda.” Sociological Theory 33(2):148–72.

Martin, John Levi. 2001. “On the Limits of Sociological Theory.” Philosophy of the Social Sciences 31(2):187–223.

Martin, John Levi. 2011. The Explanation of Social Action. Oxford University Press, USA.

Portes, A. and J. Sensenbrenner. 1993. “Embeddedness and Immigration: Notes on the Social Determinants of Economic Action.” The American Journal of Sociology.

Ragin, Charles C. 2000. Fuzzy-Set Social Science. University of Chicago Press.

Categories, Part II: Prototypes, Fuzzy Sets, and Other Non-Classical Theories

A few years ago The Economist published “Lil Jon, Grammaticaliser.” “Lil Jon’s track ‘What You Gonna Do’ got me thinking,” the author tells us, “of all things, the progressive grammaticalisation of the word shit.” In it, Lil Jon repeats “What they gon’ do? Shit” and in this lyric, shit doesn’t mean “shit” it means “nothing.”

As the author goes on to explain, things that are either trivial, devalued or demeaning are commonly used to mean “nothing”: I haven’t eaten a bite, I don’t give a rat’s ass, I won’t hurt a fly, he doesn’t know shit. More examples are given in Hoeksema’s “On the Grammaticalization of Negative Polarity Items.” This is difficult to account for in Chomsky’s (Extended or Revised Extended) Standard Theory because the meaning of terms makes them candidates for specific kinds of syntactic functions (Traugott and Heine 1991:8):

What we find in language after language is that for any given grammatical domain, there is only a restrictive set of… sources. For example, case markers, including prepositions and postpositions, typically derive from terms for body parts or verbs of motion; tense and aspect markers typically derive from specific spatial configurations; modals from terms from possession, or desire; middles from reflexives, etc.

Grammaticalization involves the extension of term until its meaning is “bleached” and becomes more generic and encompassing (Sweetser 1988). For example, the modal word “will,” as in “I will finish that review,” comes from the Old English term willan meaning to “want” or “wish,” and, of course, it still carries that connotation: “I willed it into being.” This relates to a second difficulty for Chomskian Theory: grammaticalization is a graded process. It’s not always easy to decide whether a particular lexical item should be categorized as one or another syntactical unit and therefore we cannot know precisely which rules apply when.

Logical Weakness of the Classical Theory

It may be that the classical theory doesn’t work well for linguistics, but that might not be reason to abandon it elsewhere. In fact, there is a certain sensibleness to the approach: categories are about splitting the world up, so why shouldn’t everything fall into mutually exclusive containers? To summarize the various weaknesses as described by Taylor (2003):

Provided we know (innately or otherwise) what features grant membership in a category, we must still verify that a token has all the features granting it membership, rendering categories pointless.
Perhaps we could allow an authority to assure us a token has all the features, but then we are no longer relying on the classical conditions to categorize.
Features might also be kinds of categories, e.g., if cars must have wheels, what defines inclusion in the category “wheels,” which leads to infinite regress (unless, of course, we can find genuine primitives).
Finally, it seems that a lot of features are defined circularly by reference to their category, e.g., cars have doors, but what kind of doors other than the doors cars tend to have?

The rejection of this classical theory is foreshadowed by, among others, Wittgenstein. The younger Wittgenstein was interested in philosophy and mathematics, and after being encouraged by Frege, he more or less forced Bertrand Russell to take him on as a student in 1911. His first major work the Tractatus Logico-Philosophicus, was published in 1921, which went on to inspire the founding of the Vienna Circle of Logical Empiricism—which, even though living in Vienna at the time, did not include Wittgenstein, who seemed to hate everyone. (At the same time, it bears noting, Roman Jakobson was a couple hundred miles away founding the Prague Circle of Linguistics).

After several years worth reading about, the received story goes, Wittgenstein does an about face on his own argument in the Tractatus in the course of trying to find the “atoms” of formal logic. In his later writings beginning in the late 1920s and continuing until his death in 1951, we get, among other things, the notion of defining words not be a list of necessary and sufficient conditions but by looking at how words are used. The most well-known example being, after reviewing a few different ways the word “game” is used, he states “we can go through many, many other groups of games in the same way, can see how similarities crop up and disappear…I can think of no better expression to characterize these similarities than ‘family resemblances’” (Wittgenstein [1953] 2009 para. 66-67).

Beyond Family Resemblances

Screenshot from 2019-04-27 11-45-20 — From the The Atlas of the Munsell Color System, by Albert H. Munsell

Prototype Theory and Basic Level Categories

One pillar of the classical theory is that, if membership is granted based on having certain attributes, than it follows that no member should be a better or worse example of that category. A second pillar is that, category criteria should be independent of who or what is doing the categorizing. Eleanor Rosch’s early work toppled both pillars.

Rosch graduated from Reed College, completing her senior thesis on Wittgenstein (who she says “cured her of philosophy”) — specifically his discussion of pain and “private language.” She went on to complete graduate work in psychology at the famed Harvard Department of Social Relations, under the direction of Roger Brown (who was an expert in the psychology of language). She conducted research in New Guinea on Dani color and form categories, as well as child rearing practices (Rosch Heider 1971), and in late 1971, she joined the psychology department at UC, Berkeley.

In a 1973 publication, “Natural Categories,” Rosch critiqued existing studies of category formation because it relied on categories that subjects had already formed. For example, “American college sophomores have long since learned the concepts ‘red’ and ‘square’” To meet this challenge, she studied the Dani who had only two color terms, which divided color on the basis of brightness, rather than hue. Rosch hypothesized (Rosch 1973:330):

…there are colors and forms which are more perceptually salient than other stimuli in their domains…salient colors are those areas of the color space previously found to be most exemplary of basic color names in many different languages… and that salient forms are the “good forms” of Gestalt psychology (circle, square, etc.). Such colors and forms more readily attract attention than other stimuli… are more easily remembered than less salient stimuli…

She ultimately found “the salience and memorability of certain areas of the color space…can influence the formation of linguistic categories” (the classical citation for cross-cultural color categorization being Berlin and Kay 1991; see also Gibson et al. 2017). As categories form around salient prototypes, potential members of this category are judged on a graded basis.

In addition to building categories around salient exemplars, Rosch also found that, and aligning with ecological psychology, such salience relates to the usefulness for, and capacities of, the observer. For example, there tends to be the most cross-cultural agreement as to how any given token is categorized at the “basic level.” That is, although different groups of people may differ in terms of what the prototypical “dog” is — is it a golden retriever or a bulldog? — when people see a dog, any dog, they will probably categorize it at the basic level of “dog,” as opposed to generically as animal or mammal or specifically as a golden retriever-bulldog mix. And it is at this basic level where there is the most interpersonal (and cross-cultural) similarities.

Berkeley and the West Coast Cognitive Revolution

In a previous post, I discussed all the interesting things happening in anthropology and artificial intelligence at UC, San Diego and Stanford during the 70 and 80s, and we can add UC, Berkeley to this list of strongholds for West Coast Cognitive Revolutionaries.

Lakoff left MIT for Berkeley in 1972, and shortly thereafter he was confronted with kinds of utterances neither generative semantics nor generative grammar could account for, e.g., “John invited you’ll never guess how many people to the party” in which a clause splits another clause, sometimes called “center embedding.” Faced with this, Lakoff got an NSF grant to invite people from linguistics, psychology, logic, and artificial intelligence for a summer seminar in 1975, which ballooned into roughly 190 attendees (de Mendoza Ibáñez 1997). Among the lectures was Rosch on basic-level categories and how category prototypes can be represented in motor-systems (the seedling of the embodied mind), Charles Fillmore’s discussion of “Frame Semantics” which inspired the cognitive anthropologists, and Leonard Talmy (a recent Berkeley PhD) on how physical embodiment creates universal “cognitive topologies” which map onto words, like “in” and “out.”

So, Lakoff recalls, “in the face of all this evidence, in the summer of 1975, I realized that both transformational grammar and formal logic were hopelessly inadequate and I stopped doing Generative Semantics” (de Mendoza Ibáñez 1997). It is also in 1975 that he published “Hedges: A Study in Meaning Criteria and the Logic of Fuzzy Concepts,” incorporating ideas from Rosch, as well as another Berkeley Professor Lotfi Zadeh. In this paper Lakoff argued: “For me, some of the most interesting questions are raised by the study of words whose meaning implicitly involves fuzziness- words whose job is to make things fuzzier or less fuzzy. I will refer to such words as ‘hedges’.” In addition to referring to Rosch’s then-unpublished paper “On the Internal Structure of Perceptual and Semantic Categories,” Lakoff acknowledges “Professor Zadeh has been kind enough to discuss this paper with me often and at great length and many of the ideas in it have come from those discussions.”

Zadeh was born in Baku, Azerbaijan, then studied at the University of Tehran before completing his master’s at MIT, and doctorate in electrical engineering at Columbia University in 1949. He eventually landed at UC, Berkeley in 1959 where he slowly began to develop “fuzzy” methods. In 1965 he published the paradigm-shifting piece, “Fuzzy Sets,” which he began writing during the summer of ‘64 while working at Rand Corporation, and exists as the report “Abstraction and Pattern Classification.” In essence, Zadeh realized many objects in the world did not have clear boundaries to allow discrete classification, but rather allowed for graded membership (he used the example of “tall man” and “very tall man”). He then demonstrates that classical “crisp” set theory was simply a special case of “fuzzy” set theory.

Zadeh would quickly expand the notion of fuzzy methods into a plethora of subfields, including information systems and computer science, but also linguistics beginning in the 1970s, an early example being, “A Fuzzy-Set-Theoretic Interpretation of Linguistic Hedges.” However, whether fuzzy logic explains the normal process of human categorization (i.e. whether humans are actually following the procedures of fuzzy logic in the task of categorizing) continues to be a debated topic. Rosch (e.g. Rosch 1999), in particular, is skeptical, precisely because the process of categorizing is not about applying decontextualized “rules.” Rather, as Mike argued in his recent post, we can think of categorizing as more like finding, than seeking.

References

Berlin, Brent and Paul Kay. 1991. Basic Color Terms: Their Universality and Evolution. University of California Press.

Gibson, Edward, Richard Futrell, Julian Jara-Ettinger, Kyle Mahowald, Leon Bergen, Sivalogeswaran Ratnasingam, Mitchell Gibson, Steven T. Piantadosi, and Bevil R. Conway. 2017. “Color Naming across Languages Reflects Color Use.” Proceedings of the National Academy of Sciences of the United States of America 114(40):10785–90.

de Mendoza Ibáñez, Francisco José Ruiz. 1997. “An Interview with George Lakoff.” Cuadernos de Filología Inglesa 6(2):33–52.

Rosch, E. 1999. “Reclaiming Concepts.” Journal of Consciousness Studies 6(11-12):61–77.

Rosch, Eleanor H. 1973. “Natural Categories.” Cognitive Psychology 4(3):328–50.

Rosch Heider, Eleanor. 1971. “Style and Accuracy of Verbal Communications within and between Social Classes.” Journal of Personality and Social Psychology 18(1):33.

Sweetser, Eve E. 1988. “Grammaticalization and Semantic Bleaching.” Pp. 389–405 in Annual Meeting of the Berkeley Linguistics Society. Vol. 14..

Taylor, John R. 2003. Linguistic Categorization. OUP Oxford.

Traugott, Elizabeth Closs and Bernd Heine. 1991. Approaches to Grammaticalization: Volume II. Types of Grammatical Markers. John Benjamins Publishing.

Wittgenstein, Ludwig. [1953] 2009. Philosophical Investigations. Blackwell.

Categories, Part I: The Fall of the Classical Theory

In a “monster of the week” episode of the The X-Files, Mulder and Scully encounter a genie, Jenn. She tells Mulder — who has three wishes — “Everyone I come in contact with asks for the wrong things…” Thinking the trick is to ask for something altruistic, Mulder wishes for “peace on earth.” Jenn grants his wish by vanishing all humans except Mulder. Distraught, Mulder uses his second wish to undo his first wish. He then decides the problem is that the wish was not specific enough, and we see him writing a lengthy “contract” in a word processor. In the end he wishes Jenn to be free, but if he were able to ask for this really specific contractual wish, things probably still wouldn’t have went as he intended. This is because there will probably always be “wiggle room” when Jenn begins to interpret the wish — she could find a loophole. As we know from Durkheim, “the contract is not sufficient by itself…”

If we think of a contract as a set of explicit rules allowing some things and baring others, then a perfect contract is what we would call a classical category. For example, the category “world peace” describes certain states of affairs, which includes some things (like people are to be calm) and excludes others (like people are not to be fighting). This used to be the dominant way philosophers, psychologists, and most other disciplines were thinking about categories, and it continues to pop up as a kind of “Good Old-Fashioned Category Theory” — or, we might say, GOLFCAT — even in sociology.

What are “Classical” Categories?

John Taylor, in Linguistic Categorization (Chapter 2) and George Lakoff in Women, Fire, and Dangerous Things (Chapter 1), provide great overviews of this theory of categories. In short, this theory is based on a metaphor (Lakoff [1987] 2008:6):

They were assumed to be abstract containers, with things either inside or outside the category. Things were assumed to be in the same category if and only if they had certain properties in common. And the properties they had in common were taken as deﬁning the category.

To put this more formally, Taylor (2003:21) offers the following four conditions:

Categories are defined in terms of a conjunction of necessary and sufficient features.
Features are binary.
Categories have clear boundaries.
All members of a category have equal status.

One can easily see this view of categories as built into the early 20th century approach to phonology — which often conforms well to the folk theory of phonology today. Basically, speaking is a linear sequence of discrete sounds. A single language has a finite set of discrete sounds. More formally, these sounds are defined by distinguishing features that correspond to how they are produced in the mouth and throat — e.g., /m/ as in “mom” is found in almost every language, and is a “voiced bilabial nasal” because it is produced with both lips (pressed together) and by blocking the airflow and redirecting it through the nasal cavity, and it is voiced because the vocal cords vibrate. Furthermore these features are said to be “binary” in that they can either be present or absent (either the vocal cords vibrate or they do not: think of /th/ in thee compared to thy). This was the theory championed by the incomparable Roman Jakobson. Take this example (published in the same year Jakobson arrived at Harvard):

Our basic assumption is that every language operates with a strictly limited number of underlying ultimate distinctions which form a set of binary oppositions (Jakobson and Lotz 1949:151)

This theory was more fully elaborated in the book Preliminaries to Speech Analysis: The Distinctive Features and Their Correlates. Later, two MIT linguistic professors, Noam Chomsky (who, while a doctoral student at Penn supervised by Zellig Harris, conducted research at Harvard as a member of the Society of Fellows) and Morris Halle (a doctoral student of Jakobson’s at Harvard) would write in The Sound Pattern of English (1968:297):

In the view of the fact that phonological features are classificatory devices, they are binary… for the natural way of indicating whether or not an item belongs to a particular category is by means of binary features.

Chomsky, of course, did not stop with phonology but continued down this path intending to discover the simple categories of syntax, which could explain all the regularity and variance in human languages. Surveying these developments in linguistics, Taylor offers three common additional conditions:

Features are primitive (i.e. irreducible to any other features)
Features are universal (i.e. there is an all-encompassing feature inventory)
Feature are abstract (features do not directly correspond to any particular case)

Finally, and both famously and controversially, this classical category theory as applied to language is extended by Chomsky et al. much further, forming the basis of the “nativist-generative-transformational” theory (Taylor 2003:26):

Features are innate

The Beginning of the Fall (in Linguistics)

Chomsky published Aspects of the Theory of Syntax in 1965, and it quickly became a kind of sacred text for the nascent MIT linguistics department. In it, he lays out the basic task of the “Standard Theory,” as discovering “generative grammar” which “must be a system of rules that can iterate to generate an indefinitely large number of structures” (Chomsky 2014 [1965]: 15-16).

One strong assumption built into his program is that there are “grammatically” correct sentences, and that lexical units could be adequately arranged in either-or categories (e.g., noun, verb etc…). A second assumption built into is that the highly variant “surface structure” of given utterances can be reduced into constituent categories or a “deep structure,” and a set of rules of composition and transformation. Finally, Chomsky felt there was clear and necessary boundaries between phonology, semantics, and syntax — and syntax was the real goal of linguistics (see Chapter 2 in Syntactic Structures in particular).

For all these reasons, he was skeptical that descriptive and statistical studies could reveal the underlying structure and offered a now infamous example:

Colorless green ideas sleep furiously.
*Furiously sleep ideas green colorless.

According to Chomsky, “It is fair to assume that neither sentence…ever occurred in an English discourse… Hence, in any statistical model for grammaticalness, these sentences will be ruled out on identical grounds as equally ‘remote’ from English.” Even though, according to Chomsky, a reasonable person could tell that sentence (1) is syntactically correct, while (2) is not. (Although, one paper (Pereira 2000:1245) does test this assertion and finds that sentence (1) is about 200,000 times more probable than sentence (2), and thus Chomsky’s assertion is either naive or in bad faith.)

Harsh Words for the Master

George Lakoff was an undergrad at MIT, majoring in mathematics and poetry when Noam Chomsky founded the Department of Linguistics in 1961. As part of the founding, Chomsky invited Jakobson from Harvard to teach a class. As Lakoff describes it:

So my advisor in the English Department said: “Roman Jakobson is coming to teach poetics, you’re interested in poetry, you should take this course, but if you’re going to do it, you should know all your linguistics, so also take Morris Halle’s Introduction to Linguistics”

In the 1960s, Chomskyan generative linguistics had become hegemonic, superseding the Bloomfieldian paradigm, and after his first years studying English at Indiana University, Lakoff intended to contribute to this new project. He returned to Cambridge in the summer of 1963 to marry Robin (Tolmach) Lakoff — a linguistics PhD student at Harvard at the time who, among other things, would go on to found the study of gender and language with Language and Woman’s Place.

While there, Lakoff found a job on an early machine translation project at MIT, where he met several others who would oppose Chomsky in the “linguistics wars.” When he returned to Indiana, he decided to turn to linguistics, and studied under Fred Householder, who famously published an early critique of Chomsky and Halle’s theory of phonology in 1965. In his final year, Lakoff returned to Cambridge, where Paul Postal directed his dissertation, and he also worked closely with Haj Ross and James McCawley.

Together, Lakoff, Ross, McCawley and Postal each explored cases that didn’t seem to fit Chomsky’s Standard Theory, and attempted to offer “patches” that would adequately account for these anomalies. In fact, Lakoff’s dissertation was “On the nature of syntactic irregularity.” This resulted in Extended Standard Theory.

In there exploration of exceptions, however, they soon landed on the kernel of an idea that would force a break with the Standard Theory entirely and form the basis of what they called generative semantics: “syntax should not be determining semantics, semantics should be determining syntax” (Harris 1995:104). In other words, “the deeper syntax got the closer it came to meaning” (Harris 1995:128). The result was something of a tempestuous counter-revolution, as Lakoff put it in a New York Times article, “Former Chomsky Disciples Hurl Harsh Words at the Master”:

Since Chomsky’s syntax does not and cannot admit context, he can’t even account, for the word ‘please’…Nor can he handle hesitations like ‘oh’ and ‘eh,’ But it’s virtually impossible to talk to Chomsky about these things. He’s a genius, and he fights dirty when he argues.

As John Searle observed, “…the author of the revolution now occupied a minority position in the movement he created. Most of the active people in generative grammar regard Chomsky’s position as having been rendered obsolete” (Searle 1972:20). (Interestingly, it appears that the groundswell of interest in the alternative approach at MIT coincided with Chomsky leaving on sabbatical to Berkeley.)

In the end, as the boundary between semantics and syntax began to blur, these counter-revolutionaries would soon need to grapple with theories of meaning found outside of linguistics. This would ultimately, but not immediately, lead them to engage with non-classical theories of categorization. In my next post, I will discuss the logical weaknesses of the classical theory and the alternative approach.

References

Chomsky, Noam. 2014. Aspects of the Theory of Syntax. MIT Press.

Chomsky, Noam and Morris Halle. 1968. The Sound Pattern of English. Harper & Row.

Harris, Randy Allen. 1995. The Linguistics Wars. Oxford University Press.

Jakobson, R. and J. Lotz. 1949. “Notes on the French Phonemic Pattern.” Word & World 5(2):151–58.

Lakoff, George. [1987] 2008. Women, Fire, and Dangerous Things. University of Chicago Press.

Pereira, F. 2000. “Formal Grammar and Information Theory: Together Again?” Transactions of the Royal Society of London ….

Searle, John R. 1972. “A Special Supplement: Chomsky’s Revolution in Linguistics.” The New York Review of Books. Retrieved April 16, 2019 (https://www.nybooks.com/articles/1972/06/29/a-special-supplement-chomskys-revolution-in-lingui/).

Taylor, John R. 2003. Linguistic Categorization. OUP Oxford.

Limits of innateness: Are we born to see faces?

Sociologists tend to be skeptical of claims individuals are consistent across situations, as a recent exchange on Twitter exemplifies. This exchange was partially spurred by revelations that the famous Stanford Prison Experiment (which supposedly showed people will quickly engage in behaviors commensurate with their assigned roles even if it means being cruel to others), was even more problematic than previously thought.

The question of individual “durability” is sometimes framed as “nature vs nurture,” and this is certainly a part of the matter. In sociology, however, this skepticism of “durability” often goes much further than innateness, and sometimes leads sociologists to suggest individuals are inchoate blobs until situations come along to construct us (or interlocutors may resort to obfuscation by touting the truism that humans are always in a situation). If pushed on the topic, however, even the staunchest situationalist would likely concede that humans are born with some qualities, and the real question is what are the limits of such innateness? What kinds of qualities of people can be innate? To what extent are these innate qualities human universals? And, if we are “born with it” can “it” change and how and to what extent? In Stephen Turner’s new Cognitive Science and the Social, he puts the matter succinctly:

“…children quickly acquire the ability to speak grammatically. This seems to imply that they already had this ability in some form, such as a universal set of rules of language stored in the brain. If one begins with this problem, one wants a model of the brain as “language ready.” But why stop there? Why think that only grammatical rules are innate? One can expand this notion to the idea of the “culture-ready” brain, one that is poised and equipped to acquire a culture” (2018:44–45).

As I’ve previously discussed, the search for either the universal rules or specialized module for language has, thus far, failed. Nevertheless, most humans must be “language-ready” in the minimal sense of having the ability to acquire the ability to speak and understand speech. But, answering the question of where innateness ends and enculturation begins is not easy. Even for those without the disciplinary inclination toward strongly situationalist arguments.

Are we born to see faces?

How we identify faces is a good place to explore this difficulty: Do we learn to identify faces or are we born to see faces? And, if we are born to see faces, is this ability refined through use and to what extent? Enter: the fusiform face area (FFA). Just like language, the FFA is often used as evidence for the more general arguments of functional localization and domain specificity. This argument goes: facial recognition is produced not by generic cognitive processes involved in vision (or other generic processes), but rather an inborn special-purpose module.

One reason why faces are an even better candidate for grappling with the question of innateness than is language is that the human fetus is exposed to language while in the womb. Human fetuses gain some sense of prosody, tonality, and as a result, a basic sense of grammar in the course of development in utero. There is no comparable exposure to faces, however. Another reason is, as the Gestalt psychologists argued, faces have an irreducible structure such that they are perceived as complete wholes even when viewing only a part — “the whole is something else than the sum of its parts, because summing is a meaningless procedure, whereas the whole-part relationship is meaningful” (Koffka 1935:176).

Facial recognition encompasses two related functions: distinguishing faces from non-face objects and distinguishing among faces. The key debate within this area of cognitive neuroscience is whether there is a module that is specialized for one or both of these processes (Kanwisher, McDermott, and Chun 1997; Kanwisher and Yovel 2006), as opposed to a distributed and generic cognitive process (Haxby et al. 2001). This debate goes back to the observation that humans struggle to recognize and remember faces that are upside down, which seemed to be the case for faces more so than any other non-face object (Diamond and Carey 1986) — suggesting something about faces made them unique. The proposal facial recognition was the result of a specialized module, however, begins with a relatively recent paper by Kanwisher et al. (1997). Using functional magnetic resonance imaging (which I’ve discussed in detail in previous posts), 15 subjects were shown various common objects as well as faces. They found in 12 of those subjects a specific area of the brain was more active when they saw faces than when they saw non-face objects. On its face, it seems like reasonable evidence humans are born with a module necessary for identifying faces.

However, when one squares this claim with the underlying logic of fMRI—it is used to (a) measure relative activation, not an on/off process, and (b) voxel and temporal resolution is far too coarse to conclude a region is homogeneously activated—the claim that the FFA is a functionally specialized module for facial recognition weakens considerably. These areas are not entirely inactive when viewing non-face objects. Indeed, relative to baseline activation, subsequent research found the FFA is significantly more active when viewing various objects (Grill-Spector, Sayres, and Ress 2006). Specifically, the level of specificity of the stimulus (e.g. faces tend to be individuals whereas chairs tend to be generic) and the participants level of expertise with the stimulus (e.g. car and bird enthusiasts) predicted greater relative activation (Gauthier et al. 2000; Rhodes et al. 2004).

Finally, if we are born to distinguish faces from non-faces, the ability to distinguish among faces is considerably trained by early socialization, and such socialization introduces a lot of variation among people. For example, one of the earliest attempts to measure facial recognition concluded, “that women are perhaps superior to men in the test; that salespeople are superior to students and farm people; that fraternity people are perhaps superior to non-fraternity people…” (Howells 1938:127).

Subsequent research in this vein found individuals are better at distinguishing among their racial/ethnic ingroups than their outgroups. In an early study of black and white students from a predominantly black university and a predominantly white university, researchers found participants more easily discriminated among faces of their own race. They also found “white faces were found more discriminable” overall, which they suggest may be the result of “the distribution of social experience is such that both black persons and white persons will have had more exposure to white faces than black faces in public media…” (Malpass and Kravitz 1969:332). Summarizing more recent work, Kubota et al. (2012) state “participants process outgroup members primarily at the category level (race group) at the expense of encoding individuating information because of differences in category expertise or motivated ingroup attention.”

Why should sociologists care?

To summarize, the claim that facial recognition emerges from an innate functionally-specialized cognitive module is weakened in three ways: the FFA responds to more generic features faces share with other objects; the FFA is implicated in a distributed neural network rather than solely a discrete module; the FFA is used for non-facial recognition functions; and finally, facial recognition is trained by our (social) experience. Why should sociologists care? I think there are three reasons. First, innateness is not deterministic or specific but rather constraining and generic. Second, these constraints ripple throughout our social experience, forming the contours of cultural tropes, but are not immutable. Third, limited innateness does not mean individuals are not durable across situations, even (near) universally so.

A dispositional and distributed theory of cognition and action accounts for object recognition by its use: “information about salient properties of an object—such as what it looks like, how it moves, and how it is used—is stored in sensory and motor systems active when that information was acquired” (Martin 2007:25). This is commensurate with the broad approach many of the posts on this blog have been working with. Perhaps, however, there is a special class of objects for which this is not exactly the case. In other words, the admittedly weak innateness of distinguishing unfamiliar faces from non-face objects is, perhaps, the evidence we are “born with” some forms of nondeclarative knowledge (Lizardo 2017).

Such nondeclarative knowledge, however, may be re-purposed for cultural ends. Following the logic of neural exaption, discussed in a previous post, humans can be born with predispositions, especially related to very generic cognitive processes, which are further trained, refined, and recycled for novel uses, novel uses which are nevertheless constrained in a way that yields testable predictions. A fascinating example related to facial perception is anthropomorphization. If rudimentary facial recognition is innate (and therefore, probably evolutionarily old), this inherently social-cognitive process is being reused for non-social purposes (i.e. non-social in the restricted sense of interpersonal interaction). This facial recognition network—together with other neuronal networks—is used to identify people and predict their behavior, and this may be adapted to non-human animate and inanimate objects, like natural forces, as well as anonymous social structures, like financial markets.

What this means, following the logic of neural reuse and conceptual metaphor theory, is that the target domain (e.g. derivative markets, earthquakes) is “contaminated” by predispositions which originally dealt with the source domain (here, interpersonal interaction). This means attempting to imagine the intentions of thousands of unknown traders as if inferring the intentions of an interlocutor may lead traders to “ride” financial bubbles (De Martino et al. 2013). Therefore, what is and is not innate is a messy question to answer — even by those without a disciplinary distrust of innateness claims. Although cognitive neuroscientists are making headway, it remains an empirical question which objects are recognized innately and the extent to which the object recognition is robust to enculturation and neural recycling.

More importantly, the question of individual durability across situations should not be reduced solely to “nature vs nurture.” That is, we must grapple with the question of once these processes are so trained in an individual (during “primary socialization”), how easily can they be re-trained, if at all? In John Levi Martin’s Thinking Through Theory (2014:249), the third of his “Newest Rules of Sociological Method” is pessimistic in this regard: “Most of what people think of as cultural change is actually changes in the compositions of populations.” That is, even if we were to bar the possibility of innateness in any strong sense, once individuals reach a certain age they are likely to be fairly consistent across situations, with little chance of altering in fundamental ways.

REFERENCES

De Martino, Benedetto, John P. O’Doherty, Debajyoti Ray, Peter Bossaerts, and Colin Camerer. 2013. “In the Mind of the Market: Theory of Mind Biases Value Computation during Financial Bubbles.” Neuron 79(6):1222–31.

Diamond, Rhea and Susan Carey. 1986. “Why Faces Are and Are Not Special: An Effect of Expertise.” Journal of Experimental Psychology. General 115(2):107.

Gauthier, I., P. Skudlarski, J. C. Gore, and A. W. Anderson. 2000. “Expertise for Cars and Birds Recruits Brain Areas Involved in Face Recognition.” Nature Neuroscience 3(2):191–97.

Grill-Spector, Kalanit, Rory Sayres, and David Ress. 2006. “High-Resolution Imaging Reveals Highly Selective Nonface Clusters in the Fusiform Face Area.” Nature Neuroscience 9(9):1177–85.

Haxby, J. V., M. I. Gobbini, M. L. Furey, A. Ishai, J. L. Schouten, and P. Pietrini. 2001. “Distributed and Overlapping Representations of Faces and Objects in Ventral Temporal Cortex.” Science 293(5539):2425–30.

Howells, Thomas H. 1938. “A Study of Ability to Recognize Faces.” Journal of Abnormal and Social Psychology 33(1):124.

Kanwisher, Nancy and Galit Yovel. 2006. “The Fusiform Face Area: A Cortical Region Specialized for the Perception of Faces.” Philosophical Transactions of the Royal Society of London. Series B, Biological Sciences 361(1476):2109–28.

Kanwisher, N., J. McDermott, and M. M. Chun. 1997. “The Fusiform Face Area: A Module in Human Extrastriate Cortex Specialized for Face Perception.” The Journal of Neuroscience: The Official Journal of the Society for Neuroscience 17(11):4302–11.

Koffka, Kurt. 1935. Principles of Gestalt Psychology. New York: Harcourt, Brace.Kubota, Jennifer T., Mahzarin R. Banaji, and Elizabeth A. Phelps. 2012. “The Neuroscience of Race.” Nature Neuroscience 15(7):940–48.

Lizardo, Omar. 2017. “Improving Cultural Analysis Considering Personal Culture in Its Declarative and Nondeclarative Modes.” American Sociological Review 0003122416675175.

Malpass, R. S. and J. Kravitz. 1969. “Recognition for Faces of Own and Other Race.” Journal of Personality and Social Psychology 13(4):330–34.

Martin, Alex. 2007. “The Representation of Object Concepts in the Brain.” Annual Review of Psychology 58(1):25–45.

Martin, John Levi. 2014. Thinking Through Theory. W. W. Norton, Incorporated.

Rhodes, Gillian, Graham Byatt, Patricia T. Michie, and Aina Puce. 2004. “Is the Fusiform Face Area Specialized for Faces, Individuation, or Expert Individuation?” Journal of Cognitive Neuroscience 16(2):189–203.

Turner, Stephen P. 2018. Cognitive Science and the Social: A Primer. Routledge.