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:

  1. 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’.

  1. 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.

Beyond Good Old-Fashioned Ideology Theory, Part Two

In part one, I examined two recent frameworks for understanding ideology (Jost and Martin) and explained how both serve as alternatives to the good old-fashioned ideology theory (GOFIT). Ultimately, I concluded that Martin’s (2015) model has specific advantages over Jost’s (2006) model, though the connection between ideology and “practical mastery of ideologically-relevant social relations” needs to be fleshed out. This is particularly true because any strong concentration on social relations seems to preclude any serious attention to cognition. But without it, the argument is vulnerable to crying foul over reductionism.

In this post, I sketch a model of cognition that checks the boxes of GOFIT ideology: distorting, invested with power, supports unequal social relations. But it is different for reasons I specify below. To do this, I use a famous experiment in neuroscience—Michael Gazzaniga’s “split-brain” hypothesis— and draw an analogue between it and a possible non-GOFIT ideology.

Galanter, Gerstenhaber … and Geertz

But before doing that, it seems reasonable to ask about the purpose of even attempting a non-GOFIT ideology. Is GOFIT a strawman? Why is it problematic? To answer these questions, and to indicate why a holistic revision of ideology away from GOFIT seems to be in order, consider Clifford Geertz and his essay (1973) “Ideology as a cultural system,” which presents what is to date arguably the most influential, non-Marxist approach to ideology in the social sciences. Geertz’s burden is to make ideology relevant by providing it with a “nonevaluative” form. And the way he does this, using modular or computational cognition, is what I want to focus on.

Ideology here is not tantamount to oversimplified, inaccurate, “fake news” style distortion that is, above all and categorically, what science is not. But if it isn’t to be censured like this, then for Geertz ideology must be a symbolic phenomenon that has something to do with how “symbolic systems” make meaning in the world, and in turn serve to guide action  (e.g. “models of, models for”). To make this argument, he does, in fact, make ideology cognitive by drawing from a psychological model: Eugene Galanter and Murray Gerstenhaber’s [1956] “On Thought: The Extrinsic Theory.”

As Geertz summarizes:

thought consists of the construction and manipulation of symbol systems, which are employed as models of other systems, physical, organic, social, psychological, and so forth, in such a way that the structure of these other systems– and, in the favorable ease, how they may therefore be expected to behave–is, as we say “understood.” Thinking, conceptualization, formulation, comprehension, understanding, or what-have-you, consists not of ghostly happenings in the head but of a matching of the states and processes of symbolic models against the states and processes of the wider world … (214)

Geertz returns to this same argument in arguably his most thorough approach to the culture concept (“The Growth of Culture and the Evolution of Mind”). Importantly, there too he does not conceive of culture or symbols absent a psychological referent, which he consistently draws from Galanter and Gerstenhaber.

Whatever their other differences, both so-called cognitive and so-called expressive symbols or symbol-systems have, then, at least one thing in common: they are extrinsic sources of information in terms of which human life can be patterned–extrapersonal mechanisms for the perception, understanding, judgment, and manipulation of the world. Culture patterns–religious, philosophical, aesthetic, scientific, ideological–are “programs”; they provide a template or blueprint for the organization of social and psychological processes, much as genetic systems provide such a template for the organization of organic processes (Geertz, 216)

How does this apply to ideology? It makes ideology a symbolic system for building an internal model. Geertz is distinctively not anti-psychological here but instead seems to double down on the “extrinsic theory of thought” to define culture as a symbol system through which agents construct models of and for some system out in the world, effectively programming their response to that system. Ideology refers to the symbol system that does this for the political system:

The function of ideology is to make an autonomous politics possible by providing the authoritative concepts that render it meaningful, the suasive images by means of which it can be sensibly grasped … Whatever else ideologies may be–projections of unacknowledged fears, disguises for ulterior motives, phatic expressions of group solidarity–they are, most distinctively, maps of problematic social reality and matrices for the creation of collective conscience (Geertz, 218, 220)

Geertz mentions the example of the Taft-Hartley Act (restricting labor unionizing) that carries the ideological label the “slave labor act.” Geertz emphasizes how ideology works according to how well or how poorly the model (“slave labor act”) “symbolically coerces … the discordant meanings [of its object] into a unitary conceptual framework” (210-211).

If GOFIT is a set of assumptions widely held about ideology, then we probably find little to disagree with in Geertz’s argument, at least at first glance. Much of it should ring true. If we object to anything it might be the heavy-handed language that Geertz uses that evokes modular or computational cognition (e.g. “programs”). But maybe Geertz himself is not responsible for this. His sources, Galanter and Gerstenhaber, were explicit in making these assumptions about cognition, and this I want to argue is important for a specific reason.

To Galanter and Gerstenhaber, “model” clearly meant the sort of three-dimensional scale models that scientists construct in order to understand large-scale physical phenomena. In this sense, they solved the “problem of human thinking” by defining it as a lesser version of idealized scientific thinking. And they were not alone in that pursuit. At least initially, cognition was presented as antithetical to behaviorism in psychology by allying itself with resources that were quite deliberate and quite reflexive: “[mid-century] cognitive scientists … looked for human nature by holding an image of what they were looking for in their [own] minds. The image they held was none other than their own self-image … ‘good academic thinking’ [became the] model of human thinking” (Cohen-Cole 2005).

This is not only the context for Geertz’s theory of ideology. His understanding of “symbol systems” writ large cannot be removed from this specific gloss on and an extension of “good academic thinking.” For our purposes, this should beg the question of whether using symbol systems to form internal models about the external world and  to manipulate and creatively construe those models as equivalent to “symbolic action” should be the template or basis for defining ideology on nonevaluative grounds, that is to say, for defining ideology in the way that Geertz himself does: as cognitive. 

Ideology and the Split-Brain

What I will try to do now, after this long preamble, is sketch a different possible cognitive basis for a theory of ideology, one that I think is compatible with Martin’s (2015) field-theoretic approach to ideology discussed in part one of this post. It develops a cognitive interpretation of what “practically mastery of ideologically relevant social relations” might mean. It also situates Marx as the contrary of Geertz by making social relations a necessary condition for ideology as a cognitive phenomenon, not something that needs to be bracketed (or pigeonholed as “strain” or “interest”) for ideology to be cognitive.

This different basis is Gazzaniga’s research (1967; 1998; Gazzaniga and Ledoux 1978) on the split-brain and the process of confabulation of meaning on the basis of incomplete visual input. It is important to mention that I use the split-brain as an analogue (in “good academic thinking” terms) to convey what ideology might mean as a cognitive phenomenon if it is not a symbol system. I do not imply that ideology requires a split-brain as a physical input.

For Gazzaniga, the two sides of the brain effectively constituted two separate spheres of consciousness, but this could only be truly appreciated when the corpus callosum was severed (what used to be a procedure for epileptic patients) and the two sides of the brain were rendered independent from each other. When this happened, the visual field was bissected as the brain stopped communicating information together that came through the right and left visual fields (hereafter RVF and LVF). What was observable in the RVF was received independently from what was observable in the LVF. As Gazzaniga found, the brain is multi-modal. The left hemisphere is the center of language about visual input. So when a word or image was flashed to the RVF and the information was received by the left hemisphere, the patient could provide an accurate report. When a word or image was flashed to the LVF, the patient could only confabulate because the non-integrated brain could not combine the visual information with the language functions of the left hemisphere. The split-brain patient effectively “didn’t see anything,” even though she could still connect visual cues to related pictures on command.

When visual information is presented to a split-brain, the mystery is how the verbal left hemisphere attempts to make sense of what the non-verbal right hemisphere is doing. This is the recipe for confabulations or “false memories” as Gazzaniga (1998) puts it, because here we witness the effects of the “interpreter mechanism.”

Thus, when the RVF and LVF of a split-brain patient were shown pictures of a house in the snow and a chicken’s claw, and the patient was asked to point to relevant pictures based on these visual cues, she pointed to a snow shovel and a chicken head respectively. Here is the interesting part:

the right hemisphere—that is, the left hand—correctly picked the shovel for the snowstorm; the right hand, controlled by the left hemisphere, correctly picked the chicken to go with the bird’s foot. Then we asked the patient why the left hand— or right hemisphere—was pointing to the shovel. Because only the left hemisphere retains the ability to talk, it answered. But because it could not know why the right hemisphere was doing what it was doing, it made up a story about what it could see—namely, the chicken. It said the right hemisphere chose the shovel to clean out a chicken shed (Gazzaniga 1998: 53; emphasis added).

“It made up a story” refers here to the verbal left hemisphere attempting to make sense of why right hemisphere had been directed toward a shovel. Flashing a picture to right hemisphere lacked any narrative ability, and yet the split-brain patient could still point at a relevant image even though this did not “pass through” language.

The argument here is that this serves as a good analogue for a theory of ideology that does not make computational or modular commitments. The important point is that confabulation is not just some made up story, but what the split-brain patient believes because his brain has filled in the blank (e.g. “I chose the shovel because I need to shovel out the chicken coop”). Ideology as a cognitive phenomenon does not, in this sense, mean programming the political system according to an extrinsic symbol system; in other words, building an internal model (a three-dimensional one) of that system and drawing entailments from it, as any good scientist would do. To be “in ideology” means filling in the blank as the normal way to cognitively cope with disconnected inputs, some with a “phonological representation,” others that are “nonspeaking.”

The Split-Brain and Social Relations

We can theorize that where practical mastery of social relations becomes important, in particular, social relations that are “ideologically-relevant,” it is because they generate an equivalent of a split-brain effect and its “interpreter mechanism.” In social relations arranged as fields, practical mastery consists of the “felt motivation of impulsion … to attach impulsion … to positions … [and have] the ethical or imperative nature of such motivations [be] akin to a social object, external and (locally) intersubjectively valid, that is, valid conditional on position and history” (Martin 2011: 312).

Fields refer to one type of social relation conducive to ideological effects, particularly if they are organized on quasi-Schmittian grounds of opponents and allies (Martin 2015). Marx is clear that other types of social relation (like capital) are specifically resistant to influence by any sort of cognitive mediation. Still, he achieves some understanding of those social relations by examining their “being thought … [through] abstractions” (see Marx 1973: 143). For instance,  the commodity fetish can be seen as analogous to a split-brain effect: the “social relation between things” is an LVF interpretation, while the “social relation between people” is equivalent to an RVF input. A split-brain is an analogue of mental structures that correspond to these objective (social) structures.

Taking the split-brain as the basis (not the “extrinsic theory”) for ideology as a (non-GOFIT) cognitive phenomenon, then, we can speculate that only certain social relations (fields, capital) have an ideological effect. The ideological effect they do have is because they generate a split-brain scenario with disconnected inputs. Agents are subject to social relations in which they do not have direct access (RVF). They fill in the blank of the effect of those inputs through “abstractions,” i.e. explicit endorsements or propositional attitudes that take linguistic form, often mistaken on their own terms as ideology (LVF).

To be continued … [note: Zizek (2017: 119ff) also finds the split-brain useful for thinking about ideology, though his argument confounds and mystifies with Pokemon Go]



Cohen-Cole, Jamie. (2005). “The Reflexivity of Cognitive Science: The Scientist as a Model of Human Nature.” History of the Human Sciences 18: 107-139.

Galanter, Eugene and Murray Gerstenhaber. (1956). “On Thought: The Extrinsic Theory.” Psychological Review 63: 218-227.

Gazzaniga, Michael. (1967). “The Split-Brain in Man.” Scientific American 217: 24-29.

_____. (1998). “The Split-Brain Revisited.” Scientific American 279: 51-55.

Gazzaniga, Michael and Joseph LeDoux. (1978). The Integrated Mind. Plenum Press.

Geertz, Clifford. (1973). “Ideology as a Cultural System.” in Interpretation of Cultures.

Jost, John. (2006). “The End of the End of Ideology.” American Psychologist 61: 651-670.

Martin, John Levi. (2015). “What is Ideology?” Sociologica 77: 9-31.

_____. (2011). The Explanation of Social Action. Oxford.

Marx, Karl. (1973). The Grundrisse. Penguin.

Zizek, Slavoj. (2017). Incontinence of the Void. MIT


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