Fish consumption advisory programs: Opportunities and challenges for the protection of human health in Canada and the US
Bibliographic record
Abstract
abstract: Fish consumption advisories are important to the protection of human health but are not often widely communicated nor systematically or comprehensively conducted. The objective of this thesis is to explore the strengths and weaknesses of current fish consumption advisory programs in the US and Canada, providing a comparison between the two countries. The US and Canada were chosen because the two countries are relatively similar in socio-economic makeup as well as in their state vs. federal regulatory setup, allowing for easier comparison. At the sub-federal level, Arizona was chosen to serve as a case study for the US, and Nova Scotia as a case study for Canada. To compare each country, fish consumption advisory programs were broadly described across the 50 US states and 13 Canadian provinces and territories to provide a full understanding of the variation in such programs within each country. In addition to comparison across states and provinces, opportunities and challenges for policy correction to strengthen fish consumption advisory programs will be provided, including suggestions on how the US and Canada can learn from each other in creating better environmental policy. Policy is addressed as a means of improving fish consumption advisory programs because without state or federal requirements to monitor fish tissue for contaminants of concern across the US and Canada, there is no guarantee human health and environmental justice will remain protected in either country. Potential global sources of enhanced environmental policy will be provided as examples of further opportunities for the US and Canada to improve fish consumption advisory program policies.
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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 | 0.006 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.006 |
| Science and technology studies | 0.012 | 0.003 |
| Scholarly communication | 0.008 | 0.002 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.006 | 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".