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Record W2905671978 · doi:10.7202/1054385ar

No Small Matter: Micromuseums as Critical Institutions

2018· article· fr· W2905671978 on OpenAlexaffvenueabout
Helen Gregory, Kirsty Robertson

Bibliographic record

VenueRACAR Revue d art canadienne · 2018
Typearticle
Languagefr
FieldSocial Sciences
TopicCultural Industries and Urban Development
Canadian institutionsWestern University
Fundersnot available
KeywordsHumanitiesPolitical scienceArtSociology

Abstract

fetched live from OpenAlex

En se concentrant sur trois micro-institutions canadiennes, aux mandats spécifiquement difficiles et/ou politiquement chargés, cet article examine le potentiel critique des petits espaces et musées. Il analyse comment, en raison de financement et d’espace limités, la Feminist Art Gallery de Toronto, le STAG Project Space, une galerie et résidence d’artistes de Vancouver (aujourd’hui fermée), et le Musée de la peur et des merveilles de Bergen en Alberta, convoquent de façon inventive la communauté, la marginalité, l’intervention radicale et les stratégies commissariales. Chacun de ces espaces remet en question les normes de financement, d’accueil et d’exposition, en réimaginant le commissariat à partir de la base. En soulignant les limites des stratégies commissariales bâties sur un investissement personnel (soit-il d’argent ou de temps) et opérant en dehors des structures traditionnelles de financement, nous examinons la position de l’artiste-commissaire comme agent de changement social, ainsi que l’impact potentiel du commissariat à petite échelle.

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)0.005
metaresearch head score (Gemma)0.008
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: Empirical · Consensus signal: none
Teacher disagreement score0.036
Threshold uncertainty score0.160

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.008
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0160.078
Scholarly communication0.0160.011
Open science0.0020.012
Research integrity0.0030.004
Insufficient payload (model declined to judge)0.0090.001

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 head0.060
GPT teacher head0.288
Teacher spread0.228 · 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
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

Citations2
Published2018
Admission routes3
Has abstractyes

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Same venueRACAR Revue d art canadienneSame topicCultural Industries and Urban DevelopmentFrench-language works237,207