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Aesthetics and Cognitive Science

2009· article· en· W2107411810 on OpenAlexaff
Dustin Stokes

Bibliographic record

VenuePhilosophy Compass · 2009
Typearticle
Languageen
FieldNeuroscience
TopicAesthetic Perception and Analysis
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsCognitionRelation (database)Action (physics)PerceptionPsychologyRational analysisRepresentation (politics)Cognitive scienceCognitive neuroscienceAestheticsSociologyEpistemologyCognitive psychologyPhilosophyComputer science

Abstract

fetched live from OpenAlex

Abstract Experiences of art involve exercise of ordinary cognitive and perceptual capacities but in unique ways. These two features of experiences of art imply the mutual importance of aesthetics and cognitive science. Cognitive science provides empirical and theoretical analysis of the relevant cognitive capacities. Aesthetics thus does well to incorporate cognitive scientific research. Aesthetics also offers philosophical analysis of the uniqueness of the experience of art. Thus, cognitive science does well to incorporate the explanations of aesthetics. This paper explores this general framework of expansionism : a research strategy that suggests that the explanatory goals and resources of both aesthetics and cognitive science should expand to include those of the other. Two relations are considered. First, what is the relation between aesthetics and more traditional cognitive science? Second, what is the relation between aesthetics and new developments in cognitive science that de‐emphasize mental representation and emphasize body and action?

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.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.005
Threshold uncertainty score0.020

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0010.027
Scholarly communication0.0040.004
Open science0.0010.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0050.000

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 head0.050
GPT teacher head0.307
Teacher spread0.257 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
Domainnot available
GenreEmpirical

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".

Quick stats

Citations15
Published2009
Admission routes1
Has abstractyes

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