Bibliographic record
Abstract
Philosophical exploration of individualism and externalism in the cognitive sciences most recently has been focused on general evaluations of these two views (Adams & Aizawa 2008, Rupert 2008, Wilson 2004, Clark 2008). Here we return to broaden an earlier phase of the debate between individualists and externalists about cognition, one that considered in detail particular theories, such as those in developmental psychology (Patterson 1991) and the computational theory of vision (Burge 1986, Segal 1989). Music cognition is an area in the cognitive sciences that has received little attention from philosophers, though it has relatively recently been thrown into the externalist spotlight (Cochrane 2008, Kruger 2014, Kersten forthcoming). Given that individualism can be thought of as a kind of paradigm for research on cognition, we provide a brief overview of the field of music cognition and individualistic tendencies within the field (sections 2 and 3) before turning to consider externalist alternatives to individualistic paradigms (section 4-5) and then arguing for a qualified form of externalism about music cognition (section 6).
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.017 |
| Scholarly communication | 0.006 | 0.005 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".