Racism, traditional food access, and industrial development across Ontario: Perspectives from the fields of environmental law and environmental studies
Bibliographic record
Abstract
Racism and industrial development across lands and waters in the province of Ontario have played a significant role in decreased access to traditional food for Indigenous peoples. Traditional food access is important for health reasons, as well as cultural and spiritual wellness, and its loss has dire consequences for both people and the environment. In this commentary, we bring together our practices and experiences as settler Canadians in the fields of environmental law and environmental studies to share three short case studies exploring the linkages among traditional food access, racism, and industrial development. Specifically, we discuss how the aerial spraying of forests, mining exploration, and contaminants in fish are impacting traditional food access, and analyze how industry and monetary gains are drivers in these scenarios. For each of these case studies, we provide examples of research and advocacy from our respective fields carried out with Indigenous communities. We conclude by offering our insights for addressing systemic racism in food systems, focusing on a need for policy to prioritize Indigenous sovereignty and rights and opportunities for collaboration spanning different areas of practice and Western and Indigenous knowledge systems.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.045 | 0.042 |
| Scholarly communication | 0.010 | 0.003 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.003 | 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".