Pollution et limites des corps : échelle des perturbations endocriniennes, genre et recours au droit par une communauté amérindienne du Canada
Bibliographic record
Abstract
Focusing on the case of sex-ratio imbalance in the Aamjiwnaang community—one of the Canadian First Nations whose exposition to chemical pollution has been chronic, this paper analyzes the resources that Canadian tort law offers to the victims of disorders originating in endocrine disruptions both individually and collectively. This emblematic case shows how difficult the demonstration of tort is when exposure is multiple, massive, and affecting several generations. This difficulty is rooted in the probabilistic nature of the relationship between the substances and their adverse effects, in issues of scale and duration, in the legally problematic nature of low dose pollution. Both the centrality given to the category of person in tort laws and their highly individual understanding of the body, however, operate as major hindrances. This paper questions the propensity of environmental justice movements at conceiving torts on the basis of problematic notions of what is natural and normal in hormonal regulations. It offers a critical reading of the various categories (wounds, nuisances, neglect. . .) that shape litigation, mobilizing feminist theory and a concept of community taking into account the social and political context of exposure, as well as the colonial history of Canadian First Nations.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".