The potential for Indigenous-led conservation in urbanized landscapes in Canada
Bibliographic record
Abstract
Indigenous Protected and Conserved Areas (IPCAs) are an important pathway and governance system for area-based conservation led by Indigenous Peoples. While IPCAs have been established across rural and northern regions of Canada, they have received little attention in urbanized landscapes, even though all of Canada’s urban areas coincide with First Nations, Inuit, and Métis territory (and thereby underlying Indigenous jurisdiction) and the majority of Indigenous Peoples in the country live in urban centers. Canada’s federal government is in the process of establishing six new urban national parks and has committed to working with local Indigenous governments and organizations in parks planning. This study examined the potential for strengthening Indigenous participation in urban parks planning, governance, and management, including the establishment of new urban Indigenous Protected and Conserved Areas (UIPCAs). The results of spatial analyses of urban Indigenous territory, a review of relevant domestic and international policy and interviews with local Indigenous conservation leaders illuminate the potential for new forms of urban conservation governance that are grounded in Indigenous rights and responsibilities and reflective of Indigenous knowledge systems and biocultural priorities. However, it remains to be seen how urban Indigenous-led conservation, such as UIPCAs, can fit and operate within proposed government urban conservation initiatives, such as Canada’s Urban National Parks Program, which do not currently foreground Indigenous-led conservation in the governance of urban green space.
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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 | 0.002 | 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 | 0.015 | 0.008 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.000 | 0.001 |
| 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".