Small museums on Vancouver Island as agents of change
Bibliographic record
Abstract
This study explored how workers in two small museums on Vancouver Island were responding curatorially and pedagogically to the social issues of our times. It was inspired from my own work in a small museum, as well as the idea that museums can be agents of change in our deeply troubled world. Specifically, I investigated how these small museum workers integrated new critical and creative practices into their daily work and the challenges and constraints they faced. Adopting institutional ethnography as inquiry, I used interviews, participant observation and focus groups to explore how the study participants navigated community relations, historical discourses, exclusions and institutional restrictions. My findings show the participants tackling issues of power and privilege by enacting cultural democracy through shared curatorial authority; actively engaging with a diversity of communities; integrating women’s lives and issues in the exhibits; using the archives to share lesser-known histories; and employing a variety of aesthetic and embodied practices to raise awareness and engage community. While some visitors and members were resistant to the changes, my study suggests that most welcomed the new stories and practices, which speaks to how the participants mobilisd pedagogies of challenge and care. Challenges remained in the forms of a gendered bureaucracy; lack of funding; and job precarity. I conclude this study with recommendations for how small museums might be further supported in this important curatorial and pedagogical work. These include the development of regional and collaborative learning frameworks; the re-imagining of governance; and the adoption of ‘decent work’ principles in these institutions.
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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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.024 | 0.013 |
| Scholarly communication | 0.011 | 0.002 |
| Open science | 0.002 | 0.011 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.010 | 0.001 |
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.
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".