An analysis of the task force on museums and first peoples : the changing representation of aboriginal histories in museums
Bibliographic record
Abstract
Debate erupted in the Canadian museum world of the mid-1980s in response to a contentious exhibition of Aboriginal art and artefacts, The Spirit Sings: Artistic Traditions of Canada's First Peoples (1988), presented by the Glenbow Museum in Calgary. In order to address some of the issues circulating around the representation of Aboriginal peoples within museums in Canada, the Canadian Museums Association and the Assembly of First Nations jointly organized the Task Force on Museums and First Peoples. The Task Force consisted of arts professionals and scholars, Native and non-Native, along with concerned community members and elders. The group published a report, Turning the Page: Forging New Partnerships Between Museums and First Peoples (1992), which provided guidelines for better understanding between museums and Aboriginal Canadians. This thesis examines the history and development of the Task Force on Museums and First Peoples, as well as an in-depth look at its report and recommendations. I consider the McCord Museum of Canadian History in Montreal as a case study for the implementation of the Task Force recommendations. It is my premise throughout this thesis that the Task Force report has influenced museum practices across Canada and that, more than a decade after the appearance of the report, museums, scholars, and Aboriginal communities are continually striving to cooperate and compromise to develop an acceptable framework for the presentation of Aboriginal arts, cultures, and histories in Canadian 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 | 0.024 | 0.043 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.009 | 0.014 |
| Science and technology studies | 0.035 | 0.016 |
| Scholarly communication | 0.011 | 0.003 |
| Open science | 0.003 | 0.007 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.003 | 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".