A paradox of public engagement: The discursive politics of environmental justice in Canada's Chemical Valley
Bibliographic record
Abstract
Abstract For over a decade, members of the Aamjiwnaang Nation have continued to fight for the recognition and redress of their unique environmental health concerns in a region known as Canada's Chemical Valley. From a critical policy studies lens, this article addresses the discursive policy challenges faced by those who are most affected by the toxic policy assemblage of enduring pollution exposure. In response to the research question: how can the voices and lived experiences of those living in pollution hotspots like Chemical Valley contribute to the theory and practice of environmental justice, this article draws upon findings from extensive field‐work in the surrounding region of Lambton County as well as policy advocacy including participation in Senate of Canada hearings. This analysis examines how the omission of community‐based knowledge and expertise reproduces inequities. The article concludes with strategies for improved environmental justice and lessons learned for policy justice in Canada and beyond. Related Articles Al‐Kohlani, Sumaia A., Heather E. Campbell, and Stephen Omar El‐Khatib. 2023. “Minority Faith and Environmental Justice.” Politics & Policy 51(6): 1069–96. https://doi.org/10.1111/polp.12564 . Ash, John. 2010. “New Nuclear Energy, Risk, and Justice: Regulatory Strategies for an Era of Limited Trust.” Politics & Policy 38(2): 255–84. https://doi.org/10.1111/j.1747‐1346.2010.00237.x . Dilmaghani, Maryam, and Jeremy Dias. 2023. “In or Out? Citizenship Outcomes of Working Sexual and Gender Minority People of Canada.” Politics & Policy 51(5): 868–97. https://doi.org/10.1111/polp.12557 .
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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 | 0.012 | 0.019 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.073 | 0.053 |
| Scholarly communication | 0.022 | 0.005 |
| Open science | 0.003 | 0.013 |
| Research integrity | 0.006 | 0.010 |
| Insufficient payload (model declined to judge) | 0.008 | 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".