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Record W4404582899 · doi:10.3138/chr-2023-0026

Chained to the Gallery: 1970s Protest, Nationalism, and Anti-Racism at the Art Gallery of Ontario

2024· article· en· W4404582899 on OpenAlexaffvenueabout
Kirsty Robertson

Bibliographic record

VenueCanadian Historical Review · 2024
Typearticle
Languageen
FieldArts and Humanities
TopicArtistic and Creative Research
Canadian institutionsWestern University
Fundersnot available
KeywordsNationalismInstitutionNarrativeStatus quoMedia studiesGender studiesSociologyHistoryPolitical scienceLawArtPoliticsSocial scienceLiterature

Abstract

fetched live from OpenAlex

This article details research into an archival fonds at the Art Gallery of Ontario (ago) chronicling protests that took place at the institution in the 1970s. The archive, assembled by the institution’s registrar, was either lost or stolen in the late 1970s and then re-collected. The re-assembled archive captures two major actions in 1972 and 1974 that coalesced around artist-activist fear of the cultural imperialism of the United States and anger at the ago’s unwillingness to support local artists. The narrative of cultural nationalism that underlies the two actions is challenged by four decontextualized photographs of an anti-racist picket at the gallery in 1974, found in the same archive but for which no further information was discovered. The article introduces the term “settling activism” to describe a phenomenon wherein radical actions that appear to challenge the status quo might ultimately contribute to its continuance. Using the four photographs to unsettle both the original protests and the author’s own positionality as a beneficiary of past activism, the article illuminates the complex interplay between activism, institutional response, and historical memory and suggests that anti-racist action and intervention have a much longer history in the world of Canadian museums than has been remembered.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
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 score0.729
Threshold uncertainty score0.993

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.059
GPT teacher head0.275
Teacher spread0.216 · 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 teacher head, not a consensus.

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

Citations1
Published2024
Admission routes3
Has abstractyes

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