Metaphor – Culture, Cognition, and Action (culturecog)

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.

What’s Cultural About Analogical Mapping?

Analogical mapping is a cognitive process whereby a particular target is understood by analogizing from a particular source. For example, Lakoff and Johnson (1999) have observed that people often reason about love metaphorically as a journey. In a previous post I discussed some experimental evidence supporting the claim that activating a particular metaphor over another may be consequential for reasoning by encouraging certain outcomes over others (for an excellent review of this literature, see Thibodeau et al. (2017)). For a cultural sociologist, these findings may well be interesting but may seem somewhat esoteric. In this post, I make the case that analogical mapping (this term is used interchangeably with “conceptual metaphor”) is an inherently cultural phenomenon relevant for cultural analysis.

Analogical mapping is cultural in at least two senses. First, analogical mapping is cultural because knowledge of sources is learned. While many sources may be universal or near-universal because they are learned through universal experiences, others may be more idiosyncratic. For example, in this clip from Cloudy With A Chance of Meatballs, sardine fisherman Tim Lockwood tries to comfort his young son with a fishing metaphor, with poor results.

The uneven distribution of source domain knowledge opens important questions for cultural analysis. For example, how do analogical mappings from rare or privileged sources affect the formation, perpetuation, or dissolution of interpersonal ties? Does analogical mapping sometimes facilitate group solidarity and boundary-making? In the sitcom Brooklyn 99, for example, the police captain Raymond Holt becomes familiar with the sitcom Sex and the City in order to quickly win the trust of a certain aficionado of the series. When meeting this person, Holt casually discloses, “I’m such a Samantha,” conveying a wealth of information about himself to his interlocutor and instantly creating rapport. In such cases, metaphorical usage may convey worlds of meaning because the chosen source domain suggests certain background experiences.

via GIPHY

Cultural analysts might also investigate if/how the uneven distribution of source domain knowledge contributes to inequality. It is possible, for example, that there are certain metaphors whose meaning is clear among certain classes because of a shared familiarity with the source domain, but which might be obscure to those in other classes. If these metaphors are located at crucial points, they could be consequential for the meting out of rewards.

Second, analogical mapping is cultural because the mapping of a particular source to a particular target is learned, such that a person may be predisposed to a particular source-target mapping over another when a particular situation arises. These metaphorical predispositions can have far-reaching consequences. For example, Johnson (1987) argues that a medical revolution was brought about by changing the metaphor used for thinking about the body. The old metaphor, which he calls THE BODY IS A MACHINE, structured medical diagnosis and practice through its various entailments. If the body is a machine, then “the body consists of distinct, though interconnected parts… breakdowns occur at specific points or junctures in the mechanism… diagnosis requires that we locate these malfunctioning units” and “repair (treatment) may involve replacement, mending, alteration of parts, and so forth.” Johnson elaborates: “The key point in all of this is that the BODY AS MACHINE metaphor was not merely an isolated belief; rather, it was a massive experiential structuring that involved values, interests, goals, practices, and theorizing. What we see is that such metaphorical structurings of experience have very definite systematically related entailments” (p. 130).

The key cultural revolution in medical practice entailed developing a new metaphor, which Johnson calls THE BODY IS A HOMEOSTATIC ORGANISM. The medical researcher Hans Selye developed this new metaphor in response to the machine model’s inability to explain why different stressors triggered the same bodily reaction. Following the old model, symptoms were specific and traceable to particular breakdowns, and treatment entailed localized repairing of the faulty part(s). Within the HOMEOSTATIC metaphor, however, disease was understood as “not just suffering, but a fight to maintain the homeostatic balance of our tissues, despite damage” (p. 134). For more examples of shared mappings and their consequences, see Shore (1996) on foundational schemas.

Recognition of these two cultural dimensions of analogical mapping leads to an important theoretical observation: cultural variation can result from mapping universal building blocks (i.e. universally shared knowledge of sources) differentially to particular targets. There is a difference between not being able to understand a metaphor because you are not familiar with the source, and finding a novel metaphor surprising or unusual, but perfectly understandable. Much of what may count as cultural variation in conceptual thought may result from different mappings from the same universal stock of sources (i.e. image schemas), rather than differential mapping rooted in idiosyncratic, group-specific sources. It is an empirical question, but we need not assume that because people are using different sources, they are indecipherable to one another.

In sum, analogical mapping is not just a cognitive process; it is inescapably cultural. Source knowledge and source-target mappings are socially learned, and because of this, we have reason to believe that in at least some cases, analogical mapping is consequential for the organization of social life.

References

Johnson, Mark. 1987. The Body in the Mind: The Bodily Basis of Meaning, Imagination, and Reason. University of Chicago Press.

Lakoff, George and Mark Johnson. 1999. Philosophy In The Flesh. Basic Books.

Shore, Bradd. 1996. Culture in Mind: Cognition, Culture, and the Problem of Meaning. Oxford University Press.

Thibodeau, Paul H., Rose K. Hendricks, and Lera Boroditsky. 2017. “How Linguistic Metaphor Scaffolds Reasoning.” Trends in Cognitive Sciences 21(11):852–63.

The Evocation Model of Framing

In a forthcoming article, my coauthors and I outline what we call an “evocation model” of framing by which a frame, understood as a situated assemblage of material objects and settings (i.e., a form of public culture), activates schemas, understood as flexible, multimodal memory structures (i.e., a form of personal culture), evoking embodied responses (Wood et al. 2018). In this post, I will discuss several empirical examples from conceptual metaphor research that are consistent with our model and which expand it in promising ways.

Conceptual Metaphor Theory

Conceptual Metaphor Theory (CMT) asserts that much of our reasoning about abstract concepts is based on analogical mapping, whereby some more familiar source is used to understand and make inferences about some less familiar target. For example, Lakoff (2008:383) argues that people typically understand anger metaphorically as a hot fluid in a container. Following this metaphorical mapping, the body is understood as a container for emotions, emotions are understood as substances, and anger itself is understood as heated substance. This metaphorical mapping is manifest linguistically in phrases such as “you got my blood boiling,” “she was fuming,” and “he’s really steamed up.” It is also often manifest visually in similar ways. Consider, for example, the depiction of anger in the movie, Inside Out: Anger is red, boxlike, and at times, literally exploding with fire. This particular conceptual metaphor is extremely common across different cultures (Talebi-Dastenaei 2015).

via GIPHY

Metaphors and Schemas

The mapping of a source onto a target in CMT may be also described as the activation of a particular schema in relation to a task. In some cases, such as describing the experience of anger, there is one dominant schematic network guiding meaning construction. In other cases, there are multiple accessible schemas–multiple sources–which could easily be activated for a specified task. In our paper, we argue that framing is the process by which a frame (understood as an assemblage of material objects that may include anything tactile such as text, sounds, visible objects, smells, etc.) activates schemas, and this activation evokes a particular response. A quickly-expanding field of experimental research on CMT supports this model.

Schematic Activation and Reasoning about Crime

Thibodeau and Boroditsky (2011) find that activating particular schemas over others when describing a social problem affects the kinds of solutions people propose to address the problem. In one experiment they told two groups of participants about increasing crime rates in the fictional city of Addison, gave relevant statistics, and asked for possible solutions. They described crime in Addison metaphorically as a beast preying on the city to the first group, and as a virus infecting the city to the second group. Remarkably, despite having the same crime statistics, individuals in the different groups clustered around different solutions: “When crime was framed metaphorically as a virus, participants proposed investigating the root causes and treating the problem by enacting social reform to inoculate the community, with emphasis on eradicating poverty and improving education. When crime was framed metaphorically as a beast, participants proposed catching and jailing criminals and enacting harsher enforcement laws.” Additionally, Thibodeau and Boroditsky found that participants were unaware of the role of the metaphorical framing on their own thinking–both groups believed their solutions were rooted solely in the available data–suggesting that the framing effect was covert.

These findings suggest that when multiple schemas may be fittingly activated to support reasoning, the schema that is activated may in large part determine the result people come to. Recent sociological work on schematic understandings of poverty reaches a similar conclusion (Homan, Valentino, and Weed 2017).

Schematic Activation and Creative Thinking

In some cases, schematic activation influences cognitive performance more than predisposing someone to one outcome over another. For example, Leung et al. (2012) identify several metaphors which express creative thinking–considering a problem “on one hand, and then the other,” “thinking outside the box,” and “putting two and two together”–and ask whether physically embodying these metaphors actually makes people more creative. In a series of studies, Leung et al. have participants perform different tasks measuring convergent thinking (“the search for the best answer or the most creative solution to a problem”) or divergent thinking (“the generation of many ideas about and alternative solutions to a problem”) while being in either a controlled or experimental condition. Participants in the experimental condition for the “thinking on one hand, and then the other” metaphor were asked to generate ideas for using a campus building while physically holding out one hand and pointing to a wall, then switching hands and pointing to the other wall and generate more ideas. Leung et al. found that participants in the experimental condition generated more ideas (evidence of higher divergent thinking) than those in the control conditions.

To test the “thinking outside the box” metaphor, participants were assigned to perform a convergent thinking task in one of three conditions: sitting inside a 5×5 foot box constructed with pvc pipe and cardboard, sitting outside the 5×5 foot box, or sitting in a room without a box present. Leung et. al found that participants in the outside-the-box condition generated more correct answers than either two conditions–literally thinking outside the box seems to have helped them think outside the box metaphorically. In a related study, they had other participants perform a divergent thinking task while either walking freely, walking in a fixed, rectangular path, or not walking at all. Here they found that participants who walked freely generated more new ideas.

Together, these findings highlight the subtle influence of one’s environment on cognitive performance. While framing in sociology is typically understood as influencing what people think, it may be beneficial to also consider how certain frames facilitate or inhibit particular cognitive tasks.

Schematic Matching and Evaluating Drug Effectiveness

Keefer et al (2014) demonstrate an extension of our framework with their theory of “metaphoric fit.” The authors argue that when people evaluate the effectiveness of an abstract solution to an abstract problem, people are more likely to positively evaluate the effectiveness of the solution if the problem and the solution are understood via the same metaphors (i.e. the same schemas are activated in relation to both). They test this specifically with a series of experiments about a fictional drug proposed to treat depression. In one experiment, they described to participants the drug “Liftix” (the solution) with vertical metaphors: (e.g., “has been shown to lift mood”; “patients everywhere have reported feeling uplifted”). Two groups were given this same description of Liftix, but each group received a different description of depression (the problem). In one condition, participants were given a description of depression that activated the same verticality schema: “(“Depressed individuals feel that while other people’s lives have both ups and downs, their life has considerably more downs”). In the other condition, depression was described more literally: (“Depressed individuals feel that while other people’s lives have both positive and negative periods, their life has considerably more negative periods”). Both groups then rated how effective they thought Liftix would be. Participants in the metaphor-matching condition were more likely to give Liftix a higher rating. The authors replicated the experiment by activating LIGHT/DARK rather than UP/DOWN and found the same results. They also replicated the experiment by activating these schemas visually rather than linguistically, and again saw the same outcomes.

This study suggests that the evocation of a particular response may not be the result of activating a particular schema alone, but the interrelations of activated schemas. As such, it offers an intriguing expansion to our model and suggests that a more relational schematic analysis may sometimes be necessary.

Conclusion

A growing body of experimental research supports the core of our evocation model of framing. In various ways, the physical environment may be manipulated to activate particular schemas or combinations of schemas, and this activation evokes particular responses. In some cases, this activation may affect what people think, and in other cases, how well they think.

Although each of the studies I cited here is experimental, I note that the analysis of schemas, frames, and framing need not be limited to experiments. For example, a researcher might wish to know the variety of ways people schematically understand a concept before constructing an experiment, as Homan et al. (2017) do in their study of poverty. Alternatively, a researcher may lean on established experimental results to make inferences about the consequences of observed frames “in the wild.” Beyond this, research may focus also on the development and diffusion of particular models of frames, as we discuss in the forthcoming paper. The bottom line is that experimental work has been helpful for giving empirical support for the basic theoretical framework, but researchers should consider experimental research as just one piece of a larger puzzle.