You reap what you sow: exploring gardens as a (in)fertile space for the inclusion of indigenous women’s narratives in living history museums
Bibliographic record
Abstract
Our paper explores the experiences of three museum practitioners as they worked to address complex historical and contemporary intersections of gender and power at Fort Edmonton Park, a living history museum in Edmonton, Alberta, Canada. In our case study, we detail a narrative of changes to a Métis woman’s (Emma McDonald) garden, arguing that the interpretive space is a pedagogical site where a project of gender justice was enacted and redacted. Throughout the article, we traverse the garden demonstrating how the space and its interpretation originally reinforced settler-colonial projects, including the erasure of Indigenous women’s narratives. Then, we focus on the changing narrative of the garden and how it began to refute these settler-colonial projects by becoming a space that allowed for the interpretation of Métis knowledge through the planting of native plant species and medicines. Finally, we explore how this narrative was further complicated as we witnessed the garden transition back into a settler-colonial space, once again erasing the voice of a Métis woman and practices of Indigenous ways of knowing.
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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 | 0.006 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.024 | 0.037 |
| Scholarly communication | 0.009 | 0.005 |
| Open science | 0.002 | 0.012 |
| Research integrity | 0.002 | 0.003 |
| 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".