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Record W4398138442 · doi:10.1093/aesthj/ayad036

Distant Dinosaurs and the Aesthetics of Remote Art

2024· article· en· W4398138442 on OpenAlexaff
Michel‐Antoine Xhignesse

Bibliographic record

VenueThe British Journal of Aesthetics · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicGeographies of human-animal interactions
Canadian institutionsCapilano University
Fundersnot available
KeywordsAestheticsArtVisual arts

Abstract

fetched live from OpenAlex

Abstract Francis Sparshott introduced the term ‘remote art’ in his 1982 presidential address to the American Society for Aesthetics. The concept has not drawn much notice since—although individual remote arts, such as palaeolithic art and the artistic practices of subaltern cultures, have enjoyed their fair share of attention from aestheticians. This paper explores what unites some artistic practices under the banner of remote art, arguing that remoteness is primarily a matter of some audience’s epistemic distance from a work’s context of creation. I introduce palaeoart—the depiction of extinct prehistoric fauna and flora, especially from the Mesozoic—as a paradigmatic case of remote art, showing that its remoteness is secured both by the deceptively rich cognitive load required for its creation and appreciation, and by its existence at the margins of the institutional artworld, which ensures that this cognitive loading is largely obscured. Too often, remote art is not just inscrutable, it is invisible to us.

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)0.001
metaresearch head score (Gemma)0.001
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 score0.012
Threshold uncertainty score0.039

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0050.030
Scholarly communication0.0050.002
Open science0.0000.004
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0120.000

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 head0.016
GPT teacher head0.291
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

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

Citations1
Published2024
Admission routes1
Has abstractyes

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