Environmental Justice and Fish Consumption Advisories on the Detroit River
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
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.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it