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Record W391281231

Shine a light : surgir de l'ombre : CDN biennial : la biennale CND : 2014

2014· book· fr· W391281231 on OpenAlexaboutno aff
David Armstrong Six, Shuvinai Ashoona, Nicolas Baier

Bibliographic record

VenueNational Gallery of Canada eBooks · 2014
Typebook
Languagefr
FieldSocial Sciences
TopicCultural Industries and Urban Development
Canadian institutionsnot available
Fundersnot available
KeywordsArtVisual artsSculpturePaintingDiversity (politics)Art galleryIndigenousArt historyExhibitionSociologyAnthropology
DOInot available

Abstract

fetched live from OpenAlex

This is a superbly illustrated exploration of the current state of Canadian art. With its active approach to collecting works by both acclaimed and emerging artists, the National Gallery of Canada has amassed an enormous holding of contemporary art by Canadian artists. Since the last Biennial in 2012, the Gallery has increased its collection by nearly 300 works from more than 90 artists. From this collection, over 80 works by 26 artists have been selected for the 2014 edition. Showcasing work by Indigenous artists, anglophone and francophone artists, and new Canadian artists - all of different backgrounds and generations - this superbly illustrated publication features film and video installations, sculptures, paintings, drawings and photographs. Shine a Light also documents the efforts of Gallery curators to build a representative national collection that focuses on innovation and diversity. An introductory essay is accompanied by 26 individual presentations and dozens of colour plates.

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)0.000
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: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.241
Threshold uncertainty score0.807

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.003
Science and technology studies0.0050.001
Scholarly communication0.0070.002
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.2410.074

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 head0.021
GPT teacher head0.241
Teacher spread0.220 · 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".

Quick stats

Citations0
Published2014
Admission routes1
Has abstractyes

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