Indigenous and Settler Perspectives of Risks and Rewards on Toronto Island
Bibliographic record
Abstract
Indigenous and Settler Perspectives of Risks and Rewards on Toronto Island is a study of land and water relationships in the places we now know as Toronto and Toronto Island. The study draws on the true understanding of treaties and treaty rights from an Indigenous perspective. It shows how some consultation practices that colonial governance frameworks use today have incorporated Indigenous Knowledges but they still have a far way to go before truly recognizing Indigenous self-determination and the need for Indigenous Peoples to be seen as inherent rightsholders, especially in land management and Great Lakes water governance. The study focuses on the understanding of land and water from Indigenous perspectives and suggests modes of incorporating these understandings to address major issues that affect Toronto Island and Toronto Harbour, including water quality, contamination, and flooding due to over-development in the Great Lakes Basin. This thesis takes a two-eyed seeing approach wherein fifteen qualitative interviews were conducted with Indigenous knowledge-keepers and Toronto Island residents or water quality experts. The questions addressed the social construction of environmental risks and rewards by asking about the Toronto Purchase, Great Lakes water quality, and land use on Toronto Island. The knowledge learned from the qualitative interviews is contextualized in a historical analysis to help frame treaty rights, water governance and relationships with lands and waters from a story-telling perspective to amplify Indigenous voices in the sciences and explain the importance of Indigenous self-determination to enhance land and water management processes.
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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 | 0.001 |
| Science and technology studies | 0.020 | 0.025 |
| Scholarly communication | 0.006 | 0.002 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".