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Record W4387779920 · doi:10.1111/mila.12486

Kinds in the cognitive sciences: Reply to Weiskopf, Sullivan, and Robins

2023· article· en· W4387779920 on OpenAlex

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.

fundA Canadian funder is recorded on the work.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueMind & Language · 2023
Typearticle
Languageen
FieldNeuroscience
TopicEmbodied and Extended Cognition
Canadian institutionsnot available
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsCognitionCognitive sciencePsychologyContrast (vision)OntologyEpistemologyCognitive psychologyComputer sciencePhilosophyArtificial intelligence

Abstract

fetched live from OpenAlex

In this response to three critiques of my book, Cognitive ontology , I expand on some of its main themes. First, I demarcate the domain of cognition to support my claim that it is properly investigated from Marr's computational level. Then, I defend the claim that cognitive kinds ought to be individuated externalistically, by contrast with neural kinds, which are often individuated internalistically. This implies that the relationship between the cognitive sciences is one of delivering mutual constraints, which is a more productive research strategy than the search for “neural correlates” of cognitive constructs.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.346
Threshold uncertainty score0.561

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.065
GPT teacher head0.340
Teacher spread0.275 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it