Dreaming of an Eighth Fire Museum Practice: Indigenous voices in the Canadian Museum of History and Te Papa
Bibliographic record
Abstract
Museums and Indigenous peoples have long had a complicated relationship. Though this difficult relationship is well documented, the experiences of individual Indigenous museum practitioners have not been closely examined. Instead, the literature tends to focus on decolonising museums, collections management and repatriation, and museum practice more generally. Studies do not specifically engage with the experiences of individual Indigenous museum practitioners, nor do they delve too deeply into the question of what happens to their voices in museums. Through an exploration of the ways in which Indigenous museum practitioners’ voices appear in the Canadian Museum of History (CMH) and Te Papa, this thesis addresses that gap in the literature. I ask about the connections between Indigenous voices in the museum and the experiences of contemporary Indigenous museum practitioners. Through a framework based on the Anishinaabe Seven Fires Prophecy, this research goes on to revise and expand the field of museum studies by asking what a different future might look like for Indigenous museum practitioners. This research was conducted using qualitative methods. Semi-structured interviews explored questions about the experiences of Indigenous museum practitioners and focused on the ways their voices appear in each museum, as well as their dreams and aspirations for the future of museums and museum practice. Interviews were supplemented with observational research in exhibition spaces. This research is theoretically grounded in critical Indigenous methodologies including Kaupapa Māori, and research as relations and reconciliation. I also employed autoethnography and ethnography to reflect my non-objective role in this research, and action research in order to reflect the research’s forward-looking, change-making nature. I found that Indigenous peoples see their voices appearing in front of house spaces via language, as well as objects and their arrangement. Their voices also influence the operation of these museums through their unique perspectives as Indigenous people. Though they are making differences in museums, Indigenous museum practitioners still have to fight to be heard in many instances. The most poignant finding is that their dreams have positive change-making potential. Based on their dreams, I make recommendations for changes to current professional practice in the sector and contribute academically to the museum studies and Indigenous studies research landscapes through the use of the Seven Fires Prophecy as a framework.
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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 | 0.004 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.043 | 0.024 |
| Scholarly communication | 0.008 | 0.004 |
| Open science | 0.003 | 0.007 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.004 | 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".