Tending settler-colonial innocence: Pioneer garden exhibits and colonial grammars of conservation in Toronto
Bibliographic record
Abstract
In open-air museums and restored historic sites in Toronto, Canada, the pioneer garden exhibit is an integral part of creating a “pioneer setting” and attracting visitors. Since the 1960s, following a boost in public funding for heritage projects to celebrate the Canadian Centennial, groups and conservation authorities in Toronto have devoted time and resources to researching, implementing, and maintaining these garden exhibits. Taking for granted that the pioneer garden is a non-innocent site that was not only crucial to colonization, but continues to produce and maintain settler ecologies, this paper asks what work the pioneer garden exhibit does today. Using the analytic of “colonial grammars” and paying special attention to the history of settler colonial gardening, ongoing claims to settler innocence, erasures of settler complicity in ecological crises, and attempts to invoke contemporary ecological sensibilities, this paper describes how the pioneer garden exhibit re-narrativizes colonial planting in a way that territorializes white, settler-colonial belonging on contested Indigenous lands. This paper builds on work in political ecology, anti-colonial geography, and Black and Indigenous feminisms that clarifies the insidiousness and everydayness of white supremacist landscapes in settler-colonial places.
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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 | 0.001 | 0.002 |
| Science and technology studies | 0.019 | 0.023 |
| Scholarly communication | 0.006 | 0.002 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".