Comments on “The ethnomethodological flip”

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Flipping by conceptual metaphor

Nick Hay's picture

I came at this flip from a different angle, the core of which I think was reading about the conceptual metaphors of mathematics in Lakoff and Núñez’s Where Mathematics Comes From. I read this starting from a rationalist/Bayesian mindset with the AI goal of figuring out how one might implement a (ideally eventually superintelligent!) system that could do mathematics and logical reasoning, including handling tricky problems like shifting ontologies. The hope was seeing how humans did it would give some insight. But there was something irritating/compelling with how humans did things in this different, messy, biological way….

Interestingly, conceptual metaphor like ethnomethodology is also a study of reasoning in practice, but using a cognitive linguistics lens.

Ethnomethodology, the 5th E

Yes, Lakoff’s work is compelling. I haven’t read his book with Núñez (and intend to).

Generally ethnomethodology is compatible with “4E” cognitive science (although the work process is quite different). One of the Es is “embodied,” which Lakoff understood earlier than almost anyone else in the field.

4E and ethnomethodology are both historically rooted in early 20th-century phenomenology, although by somewhat different paths.

Rationality as game-based

Rationality developed as a collection of tools for reasoning better in certain sorts of difficult situations in which people typically think badly. Naturally, rationalism focuses its explanations on those situation types. It takes them as prototypical, and marginalizes and silently passes more typical sorts of situations and patterns of thinking and acting. This emphasis tends to make rationality seem universally effective.

Gambling games and board games are fun partly because humans are inherently bad at them, and yet we can get better with practice. They are fun also because they are fair, so we can accurately compare skill levels. Making games learnable and fair requires engineering out nebulosity: uncontrolled extraneous factors that are “not part of the game.” That also makes games particularly easy to analyze formally. Much of technical rationality was invented either specifically to play formal games, or by taking formal games as conceptual models for other activities.

Formal games are a tiny part of what most people spend most of their time doing. They are also misleading prototypes for most other things we do, which intimately involve nebulosity.

This seems like a very important insight. I would also add that there seems to be a thing where rationalist formalizations of real-world situations are initially very counter-intuitive and hard to learn exactly because they require stripping away the reasonableness that people usually use for thinking about problems… and after one has learned to think in the way that the rationalist framework requires, one may dismiss objections of its unsuitability on the basis of “yes, it was unintuitive to me too at first, but you’ll get it eventually”. (Some resemblance to Kegan 4 mistaking K5 for a K3, there.)

I’m also somewhat reminded of this bit from Jo Boaler’s “The Role of Contexts in the Mathematics Classroom”:

One difficulty in creating perceptions of reality occurs when students are required to engage partly as though a task were real whilst simultaneously ignoring factors that would be pertinent in the “real life version” of the task. As Adda [1989] suggests, we may offer student tasks involving the price of sweets but students must remember that “it would be dangerous to answer (them) by referring to the price of the sweets bought this morning” [1989, p 150]. Wiliam [1990] cites a well known investigation which asks students to imagine a city with streets forming a square grid where police can see anyone within 100m of them; each policeman being able to watch 400m of street. Students are required to work out the minimum number of police needed for different-sized grids. This task requires students to enter into a fantasy world in which all policemen see in discrete units of 100m and “for many students, the idea that someone can see 100 metres but not 110 metres is plainly absurd” [Wiliam, 1990; p30]. Students do however become trained and skilful at engaging in the make-believe of school mathematics questions at exactly the “right” level. They believe what they are told within the confines of the task and do not question its distance from reality. This probably contributes to students’ dichotomous view of situations as requiring either school mathematics or their own methods. Contexts such as the above, intended to give mathematics a real life dimension, merely perpetuate the mysterious image of school mathematics. Evidence that students often fail to engage in the “real world” aspects of mathematics problems as intended is provided by the US Third National Assessment of Educational Progress. In a question which asked the number of buses needed to carry 1128 soldiers, each bus holding 36 soldiers, the most frequent response was 31 remainder 12 [Schoenfeld, 1987; p37]. Maier [1991] explains this sort of response by suggesting that such problems have little in common with those faced in life: “they are school problems, coated with a thin veneer of “real world” associations”.

Developing from reasonableness to rationality to metarationality

rationalist formalizations of real-world situations are initially very counter-intuitive and hard to learn exactly because they require stripping away the reasonableness that people usually use for thinking about problems… and after one has learned to think in the way that the rationalist framework requires, one may dismiss objections of its unsuitability on the basis of “yes, it was unintuitive to me too at first, but you’ll get it eventually”. (Some resemblance to Kegan 4 mistaking K5 for a K3, there.)

Yes to both parts of this!

Part Three takes a partly cognitive-developmental approach to explaining rationality. We learn to do rationality by learning how to strip contextual interpretation, which requires learning to suppress reasonableness. That is difficult and actually painful at first. “Word problems” like the bus one are supposed to help you do this, but empirical evidence suggests they don’t work well.

There’s a “J-curve” to the developmental trajectory. First you learn to strip context in order to reliably carry out purely formal procedures (such as factoring a polynomial). Ideally you master that late in high school or early in undergraduate education. Then gradually you learn to add context back in, which is required in relating the formalism to reality. If you are lucky, you get some ability to do that by the end of the undergraduate period, and develop it further either in graduate school or in professional work.

It’s a “J” curve because as you develop from advanced rationality into meta-rationality, you gain a broader perspective than mere reasonableness is capable of, and can take much larger contexts into account in your reasoning.

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