The inferential path between the fMRI instrument and anything meaningful is extraordinarily long, complex, and tenuous. Just at the front end it involves several stages of statistically torturing the distorted and noisy data to get some stable signal out of it.
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I would guess few psychiatrists can follow details of fMRI data processing methods, so their faith in it has another basis. Confronted with the extreme nebulosity of human mental dysfunction, having SOME authoritative knowledge source must be reassuring?
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This tweet thread prompted by the analogy with upset responses whenever I say “deep learning stuff is mostly nonsense.” Those seem to come mostly not from actual AI researchers, but AI fans. Personal and non-professional community identities depend on belief in AI progress.
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“Quasiscience” may be a useful term for a field somewhere between science and pseudoscience. The foundations are dubious and the whole thing may be nonsense. There well may be some real stuff there, but it’s impossible to sort out which, given the methods used.
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Quasisciences address problems everyone wants answers for, but for which no good methods are available. Practitioners collude to obscure the foundational problems. Funders want answers and choose to overlook doubts. Identity communities form around the field’s outputs.
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If a quasiscience addresses its foundational problems, it can progress into a real science. Everyone wants to understand individual differences and how to relate better to each other, which makes personality & social psychology interesting, but much of it was nonsense…
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The credibility revolution in personality & social psychology aims to fix the fundamental methodological problems and turn it into a real science. Some participants wonder whether, when the dust clears, anything will be left. But, so far, so good! A model for other fields.
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Replying to @Meaningness
My sense is that a good deal of work around the five-factor model and general intelligence will survive. A great deal else will not.
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Replying to @StephenPiment
Dunno. Yes, both of these seem to get at *something*. Big Five just falls out of PCA, though, & whenever it contradicts data people disassemble it into “facets.” There’s no good mechanistic story, so I won’t be surprised if it turns out not to be real. Also not surprised if real.
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Replying to @Meaningness
Yes, agree, Big Five has these issues. But I would expect more rigorous scrubbing to produce a revised/refined version, not to throw it all out.
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Tentatively, I would agree.
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