The answer to Tuesday's yesterday's riddle (which was inspired by Thomas Presskorn's comment) is that models are to theories what norms are to practices. That is,
Models determine the meaning of a "mere" perception as an empirical fact.
That wasn't actually a very good sentence, but it was enough to suggest a solution to the puzzle.
The etymology of "norm" was helpful: '"standard, pattern, model," 1821, from French norme, from Latin norma "carpenter's square, rule, pattern".' When we turn to "model", things get even better: 'from Latin modulus "a small measure, standard," diminutive of modus "manner, measure"'. A norm is essentially an ethical standard, just as a model is an epistemic one.
It's interesting here to recall Kuhn's reflections in his post-script to The Structure of Scientific Revolutions:
...along the spectrum from heuristic to ontological models, all models have similar functions. Among other things they supply the group with preferred or permissible analogies and metaphors. By doing so they help determine what will be accepted as an explanation and as a puzzle-solution; conversely, they assist in the determination of the roster of unsolved puzzles and in the evaluation of the importance of each. (246)
Notice here the strong influence that models are said to have on what I've been talking about this month as imagination. By setting up "permissible analogies and metaphors", as well as defining relevant puzzles and acceptable solutions to them, they ultimately tell us what is to count as a "fact" in a particular area of research. [And facts are what the imagination makes us pictures of.] That's why Kuhn is right to talk about them as both "heuristic" and "metaphysical" components of paradigms. After all, what we find puzzling is the state of the facts, and only the discovery of new facts will dispel our puzzlement in a satisfying way. Models discipline the imagination.
Riffing on the etymology again, I think we can usefully think of norms as patterns in human action. It is those patterns that make our actions meaningful. And it's interesting to look at models precisely as "manners": they are are ways to experience things. Facts are really patterns in our data. And we notice some patterns and not others according the models we have been trained to use as guides ("carpenter's squares") in our analyses of our perceptions. Just as acts conform to, or push against, or even break with our norms, facts conform to, or push against, or break with our models. It's that relationship that makes them what they are.
(Notice the value of this kind of analogical reasoning. Thinking about the general features of norms, and tracing the etymology back to the Latin for a carpenter's square and pattern, we can apply these images to our understanding of models. Basically, we are noticing the "normative" aspect of models: how they influence our perceptions. We are also noticing the way norms constitute "model behavior", e.g., how the "normal" is constructed by appeal to "role models".)
The social sciences have to keep in mind that while they are, like all other sciences, primarily interested in the facts, which they derive from their perceptions according to their models, the relevance of their inquiries depends on the actions the facts bear upon. And those actions are meaningful, i.e., they become proper, socially sanctioned "acts", by virtue of the norms that are in force in a particular culture at a particular time.
11 comments:
The obvious Kantian answer to the riddle is of course the notion of a schema... Historically (if not quite etymologically) it is remarkable in relation to your answer that the modern notion of a model within physics (through the work of Hertz and Helmholtz)was derived from the Kantian notion of a schema.
(See Steen Brocks quite brilliant doctorate in philosophy: "Niels Bohr's Philosophy of Quantum Physics in the Light of the Helmholtzian Tradition of Theoretical Physics")
Yes, a case can be made that a model is the theoretical aspect of the schematism, while a norm is its practical aspect. (It may also be that Kan't "schema" is always theoretical and that we need a pangrammatical supplement for it.) In any case, I've invoked Kant's schematism before, both on my other blog, and here at RSL.
Yes, indeed schematism is the starting point of Composure (Basbøll 2014)...
It already takes an act of interpretation to decide what the relevant facts are. The facts are not simply given.
No, but the facts do simply obtain. (I.e., independently of our observation of them. That's what facts are.) Only the data are given (that's what data are) and we interpret the data to discern the facts (as patterns in the data). But maybe I'm missing the thrust of your comment?
No, the data are not given, they are collected. Someone gathers data, but first has to make a decision about what data to go out and look for, and what counts as relevant. It is only after a data-set is collected that it "obtains." Yes, facts do exist independent of our perception of then, but numerous other facts that are not in the scope of our vision also obtain, but are not counted as part of the data in the first place. Even the definite article in the phrase "the facts" is tendentious. You could say "facts" or "some facts" or "some of [the] potentially relevant facts."
For example, if I were studying the relation between television and violence, but I neglected to also study a third variable and a fourth variable that I didn't think was relevant.
Think of the model of data collection in Geertz's "thick description" vs. the model in one-to-one correlation studies. In the first, the assumption is that you need enough detail to figure out what's going on. In the second, it is assumed you can isolate two factors and study how they correlate.
You could see those two models as interpretive frameworks for deciding what "the" facts are. The model of "here are the facts" and then "let's interpret the data" is too simple, for my way of thinking. Instead it's, "Here's something we want to find out. Here's why we want to know the answer to this question. What data could potentially tell us the answer to this? How can we find this data and figure out if it is reliable? What relevant data might we be overlooking?" etc...
Sorry for the too-long comment.
... and, to carry forward your theme of imagination: the data set itself is an act of imagining. It is an imaginary relation to actual things, to paraphrase WCW.
The status of "data" in ethnography is a complicated issue. (It's my view that we should stop talking about data in many cases where it has become fashionable to do so. This is precisely because the so-called data is not really given, or in so far as it is, is completely detached from the facts it is supposed to serve as evidence for.) What I mean by "data" derives from how it's used in correlation studies.
Consider the psi research paradigm in which intention is correlated with the result of a random number generator. The subject intends a 1 and the RNG produces a 0, the subject intends a 0 and the RNG produces a 0, the subject intends a 1, and the RNG produces a 1 ... etc.
That data is a clearly just "given". If the intention correlates significantly with the result of the RNG, then it would seem that the subject has been able to "influence" the machine. If the correlation is just what you'd expect from chance, then the subject has, apparently, had no influence.
Whether or not the subject influenced the process is a fact. And the data can be interpreted as evidence for that fact. But the data (a thousand intentions, duly noted, and a thousand randomly generated 0's and 1's) are just "given".
Once you've decide how you're going to collect it and how much you'll gather, you just "scoop it up".
Social science is rarely that "clean" in its definition of what the data are. You are positing a case in which you know what the cause and effect are, but often there is ambiguity even about that.
Yes, but that's my point. Social science often pretends to have data in cases where none is possible. This has been forcefully argued by Richard Biernacki in cultural sociology.
The ambiguity is really between "facts" and "meanings". I'd prefer that we stopped talking about data in cases where we're trying to understand what people mean (by saying and doing things), and that we stop pretending that we have an especially "scientific" approach to the facts.
That said, there are less ambiguous cases, and its in those cases that I believe terms like data, fact, method and theory have meaning.
Yes, I understood in the beginning that that's what you were doing. I just got carried away. I saw the Biernacki reference before. Very interesting.
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