Collections and Inclusion: A Portrait of Museum Initiatives in Quebec and Ontario
Bibliographic record
Abstract
Abstract Today's museums seek to be more representative of the social diversity of the communities they serve. Their intention is reflected not only in the exhibitions and public programs they offer, but also in the development of their collections and their uses. The colonial origins of the collections and the gaps in the major art historical narratives that have provided their primary interpretations are more widely recognized. Several recent initiatives are revisiting, for inclusion purposes, the principles of exemplarity, uniqueness, internal organization, and material integrity on which acquisition and its valorization were until recently based. This chapter considers current initiatives undertaken over the past 10 years by the Musée d'art contemporain de Montréal, the Montreal Museum of Fine Arts, the National Gallery of Canada, and the Musée national des beaux-arts du Québec, in the development and use of their collections. It is done by taking as support three strategies established by Maura Reilly (2018) to foster inclusion in exhibitions. These three strategies – areas of study, revisionism, polylogue – are loosely adapted for collections. The four museums were selected for (1) the interest of their initiatives, (2) the complementarity of these institutions, in terms of collecting scope (contemporary, national, or “encyclopedic”), institutional status (major museums, two provincial, one federal, one nonprofit) and location (in major cities, metropolis, or capital city), and their partnership in the “New Uses of Collections in Art Museums” Partnership (SSHRC 2021–2028) of the CIÉCO Research and Inquiry Group. This portrait, through the collections of four institutions, is paradigmatic of a fundamental transformation in Canadian art museums.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.011 |
| Science and technology studies | 0.024 | 0.007 |
| Scholarly communication | 0.007 | 0.002 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".