Who's in and who's out of the cognitive kinding game? Comments on Muhammad Ali Khalidi's <i>Cognitive ontology: Taxonomic practices in the mind‐brain sciences</i>
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Muhammad Ali Khalidi contends that because cognitive science casts a wider net than neuroscience in searching for the causes of cognition, it is in the superior position to discover “real” cognitive kinds. I argue that while Khalidi identifies appropriate norms for individuating cognitive kinds, these norms ground his characterization of taxonomic practices in cognitive science, rather than the other way around. If we instead treat Khalidi's norms not as descriptively accurate characterizations of taxonomic practices in cognitive science, but as a set of best practices for kinding cognition, is cognitive science in and neuroscience definitively out of the cognitive kinding game?
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 it