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Record W4285067833 · doi:10.7202/1089650ar

Devenir-destination et photographies (en ligne) de quelques œuvres d'art

2021· article· fr· W4285067833 on OpenAlexvenueno aff
Christelle Proulx, Suzanne Paquet

Bibliographic record

VenueSens public · 2021
Typearticle
Languagefr
FieldComputer Science
TopicCultural Insights and Digital Impacts
Canadian institutionsnot available
Fundersnot available
KeywordsHumanitiesArtLignePublicsArt historyPolitical science

Abstract

fetched live from OpenAlex

Dans le cadre des travaux de recherche du projet « Art urbain, art public et cultures numériques : des publics, des sites, des trajets », nous étudions les actions concrètes des publics sur l’art, en observant la circulation de photographies d’œuvres d’art en ligne et les gestes des amateurs qui en découlent. Nos observations s’amorcent avec la publication de photographies d’œuvres d’art sur Flickr, ce qui nous permet d’analyser la visibilité des images et d’encourager leurs réutilisations, pour ensuite retracer ces photographies reproduites ailleurs avec un outil automatisant la recherche par image de Google. Les images se retrouvent sur divers sites web que nous géolocalisons afin de les cartographier. Pour cet article, nous menons l’enquête sur les vies en ligne de photographies d’œuvres de land art de Nancy Holt, Walter de Maria et Robert Smithson. Entre la fixité des œuvres ancrées dans le paysage, la mobilité des photographies en ligne et les déplacements des publics voyageurs qui publient à leur tour sur Instagram, nous assistons assurément à un devenir-destination de ces œuvres. L’utilisation d’outils et de théorisations du numérique nous permet de renouveler la pensée sur les logiques circulaires de production, de propagation et de validation de l’art.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.041
Threshold uncertainty score0.137

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0050.003
Scholarly communication0.0060.005
Open science0.0010.003
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0410.006

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 head0.145
GPT teacher head0.312
Teacher spread0.167 · 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 designNot applicable
Domainnot available
GenreOther

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".

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Citations0
Published2021
Admission routes1
Has abstractyes

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