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Record W1577501047 · doi:10.1111/jaac.12170

Aesthetic Experts, Guides to Value

2015· article· en· W1577501047 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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueJournal of Aesthetics and Art Criticism · 2015
Typearticle
Languageen
FieldNeuroscience
TopicAesthetic Perception and Analysis
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsPleasureAesthetic valueAestheticsEmpiricismValue (mathematics)Aesthetic theoryAesthetic experiencePsychologyEpistemologyPhilosophyComputer science

Abstract

fetched live from OpenAlex

A theory of aesthetic value should explain the performance of aesthetic experts, for aesthetic experts are agents who track aesthetic value. Aesthetic empiricism, the theory that an item's aesthetic value is its power to yield aesthetic pleasure, suggests that aesthetic experts are best at locating aesthetic pleasure, especially given aesthetic internalism, the view that aesthetic reasons always have motivating force. Problems with empiricism and internalism open the door to an alternative. Aesthetic experts perform a range of actions not aimed at pleasure. Yet their reasons for acting are aesthetic. Since aesthetic values figure in aesthetic reasons, we can read a nonempiricist theory of aesthetic value off aesthetic experts’ reasons for acting.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.655
Threshold uncertainty score0.496

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.063
GPT teacher head0.320
Teacher spread0.256 · 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