Environmental Justice and Fish Consumption Advisories on the Detroit River
Bibliographic record
Abstract
The Detroit River serves as a source of recreation, food, transportation and is an international demarcation. Decades of industrial and municipal pollution have threatened this valuable resource, particularly for those that are dependent on it for a food source. As Detroit, MI and Windsor, Ontario jointly govern this waterway, both communities were examined as a part of this study. The demographics of these communities are varied, with those living in Detroit predominantly African American. We sought to determine if fish consumption advisories are indeed an environmental justice issue; whether the most vulnerable populations receive and utilize this information; if contaminated fish consumption contributes to food insecurity; and how public information provided by institutions influences anglers. To accomplish this, we conducted creel surveys of anglers on the Canadian and US sides of the Detroit River to look at comparative aspects of jurisdictional boundaries affecting the attitudes, knowledge and beliefs of risks of fish consumption and contamination. Our results and conclusions reflect and highlight the environmental injustice surrounding fish consumption and the status of fish advisories.
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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 | 0.001 | 0.003 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".