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An Ontology of Multiple Artworks

2024· book· en· W4393061691 on OpenAlexaff
David Davies

Bibliographic record

Venuenot available
Typebook
Languageen
FieldNeuroscience
TopicAesthetic Perception and Analysis
Canadian institutionsMcGill University
Fundersnot available
KeywordsOntologyComputer scienceLinguisticsEpistemologyPhilosophy

Abstract

fetched live from OpenAlex

Abstract An Ontology of Multiple Artworks is the first book-length critical analytic treatment in over forty years of the metaphysical issues relating to the different kinds of ‘multiple’ artworks. Multiple artworks are works that can have multiple ‘instances’: for example, there can be multiple copies of a novel, or multiple performances of a musical work. This book takes an adequate ontology of multiple artworks to be reflectively accountable to the kinds of considerations to which authors have appealed in arguing for ontological understandings of works, in particular multiple art forms. Nine such ‘explananda’ structure the discussion. After clarifying what ‘multiplicity’ in the arts amounts to, it critically assesses the ‘Platonist’ idea that multiple artworks must be abstract entities of some sort existing independently of our creative and appreciative practices. It measures Platonism against the different explananda and also ‘weights’ the explananda themselves. It also reflects upon the methodological constraints that should govern this kind of philosophical inquiry. It argues that Platonism about multiple artworks is seriously compromised, and considers different non-Platonist options. It further argues that the account that best explains the weighted explananda is the ‘Wollheimian-type’ theory according to which multiple artworks are performances essentially embedded in artistic practices. Finally, it assesses sceptical challenges to the very idea that there are such things as multiple artworks.

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)0.002
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 score0.007
Threshold uncertainty score0.045

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0020.002
Science and technology studies0.0040.029
Scholarly communication0.0070.011
Open science0.0020.005
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.0070.001

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 head0.039
GPT teacher head0.302
Teacher spread0.263 · 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

Citations8
Published2024
Admission routes1
Has abstractyes

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