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Record W2796741371 · doi:10.1093/aesthj/ayy009

Fake Views—or Why Concepts are Bad Guides to Art’s Ontology

2018· article· en· W2796741371 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

VenueThe British Journal of Aesthetics · 2018
Typearticle
Languageen
FieldNeuroscience
TopicAesthetic Perception and Analysis
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsOntologyAestheticsComputer scienceEpistemologyArtPhilosophy

Abstract

fetched live from OpenAlex

It is often thought that the boundaries and properties of art-kinds are determined by the things we say and think about them. More recently, this tendency has manifested itself as concept-descriptivism, the view that the reference of art-kind terms is fixed by the ontological properties explicitly or implicitly ascribed to art and art-kinds by competent users of those terms. Competent users are therefore immune from radical error in their ascriptions; the result is that the ontology of art must begin and end with conceptual analysis. Against this tendency towards concept-driven ontology, I offer a trio of objections derived from: (1) the cultural and temporal variability of concepts of art, (2) the systematic tendency, on the part of would-be ontological assessors, to err on the side of familiar categories or, conversely, to exaggerate minor differences between familiar and unfamiliar practices, and (3) the influence artworld precedents exert over expert and folk concepts alike. These considerations, I argue, mandate an epistemic humility that is simply unavailable to the concept-descriptivist.

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
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 score0.392
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.001

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.

Opus teacher head0.069
GPT teacher head0.343
Teacher spread0.274 · 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