MétaCan
Menu
Back to cohort
Record W3108555960 · doi:10.4000/critiquedart.54426

Kirsty Robertson, Tear Gas Epiphanies: Protest, Culture, Museums

2019· article· fr· W3108555960 on OpenAlexaboutno aff
Johanna Renard

Bibliographic record

VenueCritique d’art · 2019
Typearticle
Languagefr
FieldSocial Sciences
TopicJapanese History and Culture
Canadian institutionsnot available
Fundersnot available
KeywordsArtVisual arts

Abstract

fetched live from OpenAlex

A mille lieues du musée-temple ou du musée-cimetière, la riche étude de Kirsty Robertson dresse le portrait d’une institution traversée et interpellée par les frictions politiques et les luttes sociales. Enseignante-chercheuse en arts visuels à l’Université Western de London dans l’Ontario, spécialisée en art contemporain, en muséologie et en études curatoriales, l’auteure se penche sur la place complexe du musée dans les mouvements contestataires canadiens du début du XXe siècle jusqu’à aujo...

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)0.004
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: none
Teacher disagreement score0.183
Threshold uncertainty score0.364

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0140.014
Scholarly communication0.0080.006
Open science0.0010.003
Research integrity0.0030.003
Insufficient payload (model declined to judge)0.0080.001

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 head0.012
GPT teacher head0.269
Teacher spread0.257 · 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
Published2019
Admission routes1
Has abstractyes

Explore more

Same venueCritique d’artSame topicJapanese History and CultureFrench-language works237,207