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.

Thinking with Theory Diagrams

A recent book by Kate Raworth entitled Doughnut Economics (2017) has garnered a lot of attention. The goal of the book is revolutionary in spirit: to move economists to think more about basic social and ecological well-being. While this aim will certainly resonate with sociologists, the means of getting there may surprise you: a doughnut. Raworth argues that what is needed are new models, new theoretical diagrams to facilitate this major change in the way economists should think about the economic world. Her major diagrammatic innovation, the doughnut, helps economists think not just about growth, but a world that promotes and produces basic social needs and ecological responsibility:

This is a major diagrammatic shift. One of its most striking ambitions is to move economists away from the conception of growth as indiscriminately good. Below is a diagram of what GDP growth in economics might look like:

What kinds of thinking are embedded within diagrams like this? As Raworth notes, this exponential growth curve fits perfectly with how people metaphorically understand progress – as ‘up’ and ‘forward’. This observation is in line with the influential work of Lakoff and Johnson (2008) who show how ubiquitous the orientational metaphors ‘GOOD IS UP’ and ‘GOOD IS FORWARD’ are in Western culture; for example, ‘things are looking up’, and ‘I’m moving forward with my life’. However, metaphors are not purely linguistic phenomena. For one, as embodied cognition research has shown, these kinds of metaphors are actually grounded in ‘image-schemas’ connected to our bodies and our physical experiences (Barsalou, 2008; Lakoff and Johnson, 2008 – see Wood et al., for a sociological discussion). Secondly, these conceptual metaphors are also embedded in diagrams and are a part of how we think with and through them (Reed, 2013). In some sense then, it is likely that we are drawn to this kind of diagrammatic view of economics because it ‘resonates’ (McDonnell, Bail, and Tavory, 2017) or fits so neatly with the way we think, act, and orient ourselves to the world more generally.

Raworth (2017) argues that a basic set of core diagrams– the curves, parabolas, lines, and circles that proliferate economics articles and books – linger in the back of most economists’ minds when thinking about a given economic issue, providing them with major assumptions about economic theory. They are indelibly etched in their minds, providing consequential ‘intellectual baggage’. More controversially, she argues that many of the most iconic of these diagrams are “out of date, blinkered, or downright wrong” (pg. 21).

Accordingly, she aims to provide a new type of diagram to encourage a new type of thinking: to see the economy as embedded in society and the environment and to strive not simply for growth, but as an ecologically safe and socially just space for human flourishing. In the Doughnut, we must be careful not to ‘overshoot’ beyond the ecological ceiling, meaning that any growth that produces environmental degradation is bad. ‘Up’ and ‘forward’ are no longer indiscriminately ‘good’ as it was with the metaphorical underpinnings of the exponential growth curve diagram; instead, there is a ‘sweet spot’ within the doughnut to which economists should aim.

So why do we need diagrams to spur this kind of intellectual revolution? Why do they matter so much? A lot can be said here, but I’d like to focus on three interrelated points: First, human beings are wired for visuals; because visualization plays such a major role in cognition, we perform mental tasks like image recognition, pattern recognition, and meaning attachment with incredible speed and ease (Thorpe et al., 1996). Moreover, images, unlike non-visual ideas and concepts, go directly into our long-term memory, leaving a lasting impression with a surprising level of detail (Brady et al., 2008). Secondly, we know that a number of disciplines rely heavily on diagrams to produce new knowledge and facilitate new discoveries (Coopmans et al. 2014; Knorr Cetina 2003; Tversky, 2011).

While we tend to think of theory figures as useful tools for teaching (Baldamus, 1992), they are important tools for explanation, elaboration, clarification, analysis, critique, and intellectual creativity (Lynch, 1991; Silver, 2018; Swedberg, 2016; Turner, 2010; see also Mills, 1959, pg. 213). Lastly, diagrams do not simply support our intellectual work, but they actively shape and direct it (Silver, 2018; Turner, 2014). Diagrams are both ‘servants’ and ‘guides’ – useful for both problem-finding and problem-solving (Humphrey, 1996). They are often imbued with theoretical assumptions (e.g. Owens, 2012), can shape the kinds of questions we ask and how we interpret our findings (e.g. Lennewick, 2010) and promote certain kinds of thinking over others (Tversky, 2011). The metaphorical underpinning of the exponential growth curve is a perfect example of that.

Sociologists also work with diagrams, and so it is natural to ask ourselves about what kind of theoretical diagrams linger in the back of the minds of sociologists, and how they shape the kind of work we do. Of course, we have some iconic theory diagrams that have inspired a lot of research: Coleman’s boat/bathtub, Burgess’ ‘concentric-zone model’, or Parsons’ various AGIL schemes. We also use popular, more conventionalized diagrammatic forms: cross-classification, Venn, cartesian coordinates and more. But while a few sociologists have studied theory diagrams in sociology (Lynch, 1991; Silver, 2018; Swedberg, 2016; Turner, 2010) none have produced any data demonstrating which diagrams are most commonly used.

A paper in progress I co-authored with Daniel Silver (presented at this year’s ASA conference in Philadelphia) on some of the practical considerations of theory visualization, addresses this issue. We took a random sample (40 articles per journal) from some of the leading journals of sociological theory in North America and Europe (Sociological Theory, Theory and Society, Theory, Culture, and Society, European Journal of Social Theory) as well as some of the leading generalist journals that often include theoretical work (American Journal of Sociology, American Sociological Review, European Journal of Sociology).

We found that, of the theory diagrams in our sample (figures without data), of all of the conventionalized diagrammatic forms the path diagram was the most commonly used – making up around 20% of the theory diagrams in our sample. This likely does not come as a surprise to most sociologists: I always seem to come across path-like diagrams in my reading, both with and without data, and can think of multiple times a professor had recommended using a path diagram to think and make sense of a research project. If path diagrams are so popular in sociology, and at least some professors generically prescribe them to struggling graduate students, it is worth asking: what does it mean to see the social world through a path diagram, like the one below?

Like with the exponential growth curve model, we can learn a lot here by unpacking the basic cognitive elements embedded within the diagram. While this appears to be somewhat reductive, all concepts, even abstract theoretical concepts in sociology, are grounded in a similar structure (Lizardo, 2013). Path diagrams may be viewed as an integrated or compound image-schema (Kimmel, 2005) with two main imagistic bases:

Variables as ‘containers’

First, the path diagram asks us to visualize variables as static entities that are ‘contained’ within a bounded space. Again, this fits with another one of the most fundamental metaphors identified by Lakoff and Johnson – the ‘container’ metaphor (for example, when we say ‘I’ve lived a full life’). This is an ontological metaphor, that tells us that there is an ‘inside’ and an ‘outside’ – and in this case anything ‘inside’ the circle is understood as contained within its ‘boundary’.

Source-path-goal

The source-path-goal schema is one of the most important sense-making structures people have; it structures our conception of ‘journey’ (a starting point – trajectory – and a destination), ‘story’ (a beginning – middle – end) , or ‘purposeful life’ (initial problem or ambition – action – solution or achievement) (Forceville, 2006).

Visually, we can see these structures in most conventional path diagrams:

But do all sociologists see social phenomena as bounded entities with relationships moving from a starting point, along a path, towards a given outcome? Interestingly, while many sociologists certainly think this way, ‘relational sociology’ (see Abbott, 2004; Emirbayer, 1997) explicitly rejects this line of thinking. Rather than treating phenomena as static ‘things’, relational sociologists conceive the social world as dynamic relations and processes. For them, boundary specification becomes a far more difficult and contentious question. For example, where do we end webs of social relations in a network, and when do sets of relations count as a ‘thing’? Or how do we fix a particular group if its membership, the frequency, and intensity of its relationships, its definition, aims etc. are continuously changing?

The same can be said for the source-path-goal schema: Can we commit to one causal story, one fixed set of relationships between entities? Ontologically, both the ‘container’ and ‘source-path-goal’ schemas appear incompatible with relational sociology; rather than fixed, bounded entities and static, linear relationships, relational sociologists see the social world as process—expanding and contracting, appearing and disappearing, merging and dividing, and so on. While path diagrams have been extremely useful and productive in sociology, if one’s aims are relational in nature, path diagrams may not be useful for thinking through or representing them.

Given this, one can speculate about what this may mean for the discipline. If diagrams are as influential as many suggest, and path diagrams are a go-to way to visualize theoretical ideas, could this be operating as a kind of visual roadblock to some forms of theory development? Could the way sociologists think and represent their ideas visually be stifling the development of relational theory? Can relational sociologists create a small revolution of their own, as Raworth (2017) has, by inventing or promoting alternative diagrammatic forms? For now, I can only speculate – but it seems to me that we have yet to explore how our visual language may be shaping the trajectory of the field as a whole.

Works Cited

Baldamus, W. (1992). Understanding Habermas’s methods of reasoning. History of the human sciences, 5(2), 97-115.

Barsalou, L. W. (2008). Grounded cognition. Annu. Rev. Psychol., 59, 617-645.

Brady, T. F., Konkle, T., Alvarez, G. A., & Oliva, A. (2008). Visual long-term memory has a massive storage capacity for object details. Proceedings of the National Academy of Sciences, 105(38), 14325-14329.

Coopmans, C., Vertesi, J., Lynch, M. E., & Woolgar, S. (2014). Representation in scientific practice revisited. MIT Press.

Forceville, C. (2006). The source–path–goal schema in the autobiographical journey documentary: McElwee, van der Keuken, Cole. New Review of Film and Television Studies, 4(3), 241-261.

Humphrey, T. M., & Line, P. (1996). The early history of the box diagram.

Kimmel, M. (2005). From Metaphor to the” Mental Sketchpad”: Literary Macrostructure and Compound Image Schemas in Heart of Darkness. Metaphor and Symbol, 20(3), 199-238.

Knorr-Cetina, K. (2003). From pipes to scopes: The flow architecture of financial markets. Distinktion: Scandinavian Journal of Social Theory, 4(2), 7-23.

Lakoff, G., & Johnson, M. (2008). Metaphors we live by. University of Chicago press.

Latour, B. (1986). Visualization and cognition. Knowledge and society, 6(1), 1-40.

Lewinnek, E. (2010). Mapping Chicago, imagining metropolises: reconsidering the zonal model of urban growth. Journal of Urban History, 36(2), 197-225.

Lizardo, O. (2013). Re‐conceptualizing Abstract Conceptualization in Social Theory: The Case of the “Structure” Concept. Journal for the Theory of Social Behaviour, 43(2), 155-180.

Lynch, M. (1991). Pictures of nothing? Visual construals in social theory. Sociological Theory, 1-21.

McDonnell, T. E., Bail, C. A., & Tavory, I. (2017). A theory of resonance. Sociological Theory, 35(1), 1-14.

Mills, C. Wright. “The social imagination.” New York: Oxford University Pres (1959).

Owens, B. R. (2012). Mapping the city: Innovation and continuity in the Chicago School of Sociology, 1920–1934. The American Sociologist, 43(3), 264-293.

Raworth, K. (2017). Doughnut economics: seven ways to think like a 21st-century economist. Chelsea Green Publishing.

Reed, S. K. (2013). Thinking visually. Psychology Press.

Silver, D. (2018). Figure It Out!. Sociological Methods & Research, 0049124118769089.

Swedberg, R. (2016). Can You Visualize Theory? On the Use of Visual Thinking in Theory Pictures, Theorizing Diagrams, and Visual Sketches. Sociological Theory, 34(3), 250-275.

Thorpe, S., Fize, D., & Marlot, C. (1996). Speed of processing in the human visual system. nature, 381(6582), 520.

Turner, C. (2010). Investigating sociological theory. Sage Publications.

Turner, C. (2014). Travels without a donkey: The adventures of Bruno Latour. History of the Human Sciences, 28(1), 118-138.

Tversky, B. (2011). Visualizing thought. Topics in Cognitive Science, 3(3), 499-535.

Wood, M. L., Stoltz, D. S., Van Ness, J., & Taylor, M. A. (2018). Schemas and Frames.

Ascription Practices: The Very Idea

How do we know what others believe? The answer to this question may seem clear but as we will see it has some interesting hidden complexities. Some of these bear directly on some established policies in social-scientific method.

One obvious answer is that if we want to know what others believe, and these others are language using creatures like ourselves is that we ask them: “Do you believe P?” If the person verbally reports believing P, then we are on safe grounds in ascribing belief P.

So far so good. But let us say a person assents to P but acts in other ways that seem counter to the content of that belief. What to do then? Cases of this sort have become popular grist for reflection in recent work in the philosophy of belief. Spurred by a series of papers by Tamar Gendler (Gendler, 2008a, 2008b), a lively literature has developed on what to ascribe when belief “sayings” (usually referred to as “judgments”) come apart from “doings” (for a sampling see Albahari, 2014; Kriegel, 2012; Mandelbaum, 2013; Schwitzgebel, 2010; Zimmerman, 2007). Some cases are stock in trade and involve people who verbally commit to a belief or attitude but act in contrary ways.

Of most interest for social and behavioral scientists are cases of what are called dissociations between “explicit” or more accurately, direct, measures of a construct (such as a belief or an attitude), which usually rely on self report, and so-called “implicit,” or more accurately, indirect measures of the same construct (Gawronski, Peters, & LeBel, 2008). While the so-called “implicit attitude test” is the most familiar indirect measure, there is an entire family composed of dozens of distinct indirect measurement strategies (Nosek, Hawkins, & Frazier, 2011). The key point is, however, that indirect measures usually rely not on verbal reports but on observations of rapid-fire action or behavioral responses that are assumed not to be under voluntary control.

Dissociations between direct and indirect measures are usually good examples of “sayings” and “doings” coming apart. If these are as common as the literature suggests, then belief (or attitude) ascription problems are also more common than we realize.

So let’s say we observe someone who fits the profile of “Chris the implicit racist.” Chris is a white high school teacher who professes the belief(s) that black people in the United States are no more or less intelligent, violent, or hardworking than white people. Yet systematically in their unguarded behavior (observed via ethnographic classroom observation or via indirect measures of implicit bias collected in the lab) Chris shows a preference for white people (e.g. they discipline black students more harshly for similar offenses; they are more likely to call on white students, etc.) and implicitly associates people with dark skin with a host of negative concepts, including lack of intelligence, proneness to violence, and a weaker work ethic.

What does Chris believe? Considerations of dissociative cases like this lead in two interesting directions. The first is that actions, practices, and behaviors have a non-negligible weight in our belief ascription practices. So judgments aren’t everything. This is important because, in polite company, our everyday practices of belief ascription follow folk cartesianism: That is, belief ascription is fixed by explicit reports of what people say they believe and people have incorrigible knowledge about those personal judgments. We cannot ascribe a belief to a person they profess not to have (alternatively people have veto power over second-person ascription practices).

In philosophy, this is called the “pro-judgment” view on ascription. This stance holds we can only ascribe the belief that P if a person reports they believe P. The actions inconsistent with P (e.g. for Chris, the automatic association of Black people with violence, or their penchant to send black students to detention for minor offenses) are acknowledged to exist but they are just not a kind of belief. They are something else. Gendler (2008a) has proposed that given the recalcitrant existence of these types of counter-doxastic behaviors, we should add a new mental category to our lexicon: “aliefs.” So we can say Chris “believes” blacks are no more violent than whites (as given by their self-report), but “alieves” they are more violent (as given by their performance on indirect attitude measures and their avoiding walking in certain predominantly black neighborhoods).

An alternative view, called the “anti-judgment” view says actions speak louder than words. Or, as indicated by the title of a recent entry in a book review symposium dedicated to Arlie Hochschild’s Strangers in Their Own Land, anti-judgment people say “who cares what they think?” (Shapira, 2017). If Chris walks like P, and quacks like P, then Chris believes P.

I should note that this belief ascription strategy is not that bizarre and that it exists as a “second option” in our commonsense arsenal, even if our first option is folk cartesianism. This should alert you that ascription practices may be very much a matter of socio-cultural tradition and regulation as they are a matter of the usual canons of rationality.

This matters if these same ascription practices are followed mindlessly in social science research. This would be a case of folk practices dictating what should be a matter of social scientific consideration. In this sense, social scientists should care very much if they are pro-judgment folk cartesians, anti-judgment, or something else, as this will bear directly on their conclusions. But we are getting ahead of ourselves. The point is that “trumping” a person’s cartesian incorrigibility by pointing to their inconsistent actions is an available move (both in social science and everyday life) but it is also one that should seldom be undertaken lightly.

Note that the pro-judgment and anti-judgment views are not the only available ones. To fill out the space of options: We may ascribe both P and ~P beliefs (the contradictory belief view). Or we may ascribe a mixture of the inconsistent beliefs (the “in-between” belief view). Or we may say Chris believes neither P nor ~P, but that they vacillate inconsistently between the two depending on circumstances (the shifting view) (Albahari, 2014).

And this is the second thing that inconsistency between sayings and doings highlight. Rather than focusing on goings-on trapped within each person’s cartesian theater, we can now see that beliefs are very much a matter of both actions and practices, both in terms of the believer and the ascriber. In this respect, two consideraations come to the fore.

First, there are the “belief proclamation” practices we are used to (e.g. people verbally saying they believe thus and so) but also the myriad of behaviors and actions that other people monitor and that they use to ascribe beliefs to others. It is these belief ascription practices I wanted to highlight in this post. As noted, they are both a matter of everyday interpersonal interaction, and for my purposes, they are a standard, but seldom commented upon, aspect of every social scientific practice. After all, social scientists (especially those who do qualitative work) constantly ask people what they believe about a host of things (e.g. Edin & Kefalas, 2011; Young, 2006), and are thus confronted with self-reports of people claiming to believe things. These same social scientists may also sometimes have the opportunity to observe these people in ecologically natural settings, which allows them to compare self-reports to doings (Jerolmack & Khan, 2014).

In this post, I will not try to adjudicate or argue for what the best ascription strategy is. I will leave that for a future post. Here I note two things. First, it is clear certain ascription practices have elective affinities with certain conceptions of what beliefs are. For instance, “pro-judgment” views have an affinity with the “pictures in the head” conception of belief. As such, pro-judgment views assume all of the things that such a conception assumes, such as representationalism, the relevance of the truth/falsity criterion and so on. “Anti-judgment” views focusing on action, may be said to be more consonant with some forms of practice theory, as can some other (e.g. “in-between” or “contradictory” views).

Second, belief ascription practices have the familiar duality of being both possible “topics” and “resource” for sociological analysis that fascinated early ethnomethodology. We can be “neutral” about their import for sociological research and study belief ascription practices as a topic. We may ask questions such as under what circumstances people default to folk cartesianism, when they prefer anti-judgment views, when they go “in between” or “contradictory” and so on.

Alternatively we may examine the issue by considering the role of belief ascription practices as a resource for sociological explanation. Are pro-judgment views always effective? Should we go anti-judgment and ignore what people say in favor of their behavior? These are some issues I hope to tackle in future posts.

References

Albahari, M. (2014). Alief or belief? A contextual approach to belief ascription. Philosophical Studies, 167(3), 701–720.

Edin, K., & Kefalas, M. (2011). Promises I Can Keep: Why Poor Women Put Motherhood before Marriage. University of California Press.

Gawronski, B., Peters, K. R., & LeBel, E. P. (2008). What Makes Mental Associations Personal or Extra-Personal? Conceptual Issues in the Methodological Debate about Implicit Attitude Measures. Social and Personality Psychology Compass, 2(2), 1002–1023.

Gendler, T. S. (2008a). Alief and Belief. The Journal of Philosophy, 105(10), 634–663.

Gendler, T. S. (2008b). Alief in Action (and Reaction). Mind & Language, 23(5), 552–585.

Jerolmack, C., & Khan, S. (2014). Talk Is Cheap: Ethnography and the Attitudinal Fallacy. Sociological Methods & Research. https://doi.org/10.1177/0049124114523396

Kriegel, U. (2012). Moral Motivation, Moral Phenomenology, And The Alief/Belief Distinction. Australasian Journal of Philosophy, 90(3), 469–486.

Mandelbaum, E. (2013). Against alief. Philosophical Studies, 165(1), 197–211.

Nosek, B. A., Hawkins, C. B., & Frazier, R. S. (2011). Implicit social cognition: from measures to mechanisms. Trends in Cognitive Sciences, 15(4), 152–159.

Schwitzgebel, E. (2010). Acting contrary to our professed beliefs or the gulf between occurrent judgment and dispositional belief. Pacific Philosophical Quarterly, 91(4), 531–553.

Shapira, H. (2017). Who Cares What They Think? Going About the Right the Wrong Way. Contemporary Sociology, 46(5), 512–517.

Young, A. A. (2006). The Minds of Marginalized Black Men: Making Sense of Mobility, Opportunity, and Future Life Chances. Princeton University Press.

Zimmerman, A. (2007). The Nature of Belief. Journal of Consciousness Studies, 14(11), 61–82.

Are Beliefs Pictures in the Head?

In a recently published piece (Strand & Lizardo, 2015) Mike and I argued that the notion of “belief” if it is to do a more adequate job as a category of analysis in social-scientific research, can best be thought of as a species of habit. I refer the interested reader to the paper for the more detail “exegetical” argumentation excavating the origins of this notion in American pragmatism (mostly in the work of Peirce and Dewey) and European practice theory (mostly in the work of Bourdieu). Here I would like to explore some reasons this proposal may seem to be so counterintuitive given our traditional conceptions of belief.

The fear, to some well-founded, is that substituting the usual notion for the habit notion would cause a net loss, and thus an inability to account for things that would like to account for (e.g. patterns of action that are driven by ideas or thoughts in the head) adequately.

What is the standard notion of belief that the “habit” notion displaces (if not replaces)? The easiest way to think of it is as one in which beliefs are thought to be little “pictures” in the head that people carry around. But what are beliefs pictures of? After all, pictures (even in modern art) usually depict something, however faint. The answer is that they are supposed to be pictures of the world that somehow the person uses to get by.

Because the beliefs are “pictures” (in cognitive science sometimes the word representation is used in this context) they have the representational properties usual pictures have. For instance, they portray the world in a certain way (e.g. under a particular description). In addition, because they are pictures, beliefs have content. That is a belief is always about something (in some philosophical segments, the word “intentionality” is usually brought up here (Searle, 1983)). In this way, some beliefs may be directed at the same state of affairs in the world, but “picture it” in different ways (Hutto, 2013). Finally, and building in on this last distinction, just like pictures claim to depict the world as it is (or at least have a resemblance to it), beliefs can be true (if they portray the world as it is) or they can be false (if the description does not match the world). This truth/falsity relation between the pictures in the head and the world turns out to be crucial for their indispensable job in “explaining” action.

For instance, if somebody opens a refrigerator, grabs a sandwich from it, and eats it, and an outside observer can “explain” the pattern by ascribing a belief to the person. So the person opened the fridge door because they thought (believed) there was a sandwich there. We usually complete this belief-based explanation by adding some kind of motive or desire as a jointly sufficient cause (“they believed there was a sandwich in the fridge and they were hungry”).

But suppose we were to see the same person open the fridge, look around and then go back to the couch empty-handed. This is a different behavioral pattern as before. However, note we can also “explain” this behavior using the same “sandwich” belief mechanism as before. The trick is simply to ascribe a false belief to the person: The imputed picture in the head does not match the actual state of the world. So we can now say, “Sam opened the fridge because they believed there was a sandwich in there and they were hungry.” We attach one more disclaimer: “But Sam was wrong, there was no sandwich.”

This flexibility makes belief-based explanations fairly powerful (they can account for a wide range of behavioral patterns). However, flexibility is also a double-edged sword: Become too flexible and you risk vacuity, explaining everything and thus nothing (see Strand & Lizardo, 2015, pp. 47–48).

Because the belief-desire combo is so flexible (and so pervasive even in our “folk” accounting of each other’s action) some people have argued that it is inevitable. So inevitable it may be the only game in town for explaining action. This would make the “pictures in the head” version of the notion of belief essentially a non-negotiable part of our explanatory vocabulary. One of the main goals of our paper was to argue that there are other options even if they seem weird at first sight.

The alternative we championed was to think of belief as a species of habit. This requires both a revision of our implicit classification of mental concepts and a revision of what we mean by “belief.” In terms of the first aspect, the usual way to think of belief and habit is to see them as distinct categories in our mental vocabulary. A habit is a “thoughtless” activity, while an action driven by belief requires “thought” to be involved. So they are two sets of mental categories, but they are as a distinct as a frog is from a zebra (even if both are a species of animal). In our proposal, however, the overarching category in mental life (for both human and nonhuman animals) is habit, and belief is a subcategory of habit. This does violence to the standard classification so it may take time to get used to.

In this respect, note that the “picture” theory of belief seems to be important in how people differentiate belief from habit. Both can be involved in action, but when action is driven by belief, the picture inside the head is on the driver’s seat and is thus an important (but always presumed) component of the action. In fact, the picture is such an important component we attribute causal force to it. Sam got up from the couch and walked to the fridge because they thought there was a sandwich in there (and they were hungry).

One last observation about the pictures in the head account of action. When the observer imputes the belief “sandwich in the fridge” to Sam and selects this belief as the “cause” of the action, by what criteria is this selection made? I bring this up only to note that there are actually a bunch of other “beliefs” that the observer could have imputed to Sam, and which could be argued to be implicated in the action, but somehow didn’t. For instance, the observer could have said one of the beliefs accounting for Sam’s action is that “there was a fridge in the room.” Or that “the fridge was plugged in” or that “the floor could sustain their weight,” and so on.

This is not just a trivial “philosophical” issue. We could impute an infinity of little world pictures in the head to Sam. In fact, as many as there are “states of affairs” about the world that make it possible for Sam to get up and check the fridge, inclusive of purely hypothetical or even “negative” pictures (e.g. the belief that “there’s not a bomb in the fridge which will be triggered to detonate when the door is opened.”). Yet, we do not (sometimes this is referred to as the “frame problem” (Dennett, 2006) in artificial intelligence circles). This means that belief imputation practices following the picture version are necessarily selective, but the criteria for selection remain obscure. This kind of obscurity should be suspicious for those who want to recruit these types of explanations as scientific accounts of action.

But we are getting ahead of ourselves. The main point of this post is simply to warm you up to the intuition that maybe the pictures in the head version of belief is not as intuitive as you may have thought nor as unproblematic or non-negotiable as it is sometimes depicted. In a future post we I will introduce the alternative conception of belief as habit and see whether it is not subject to these issues.