Northern lights against POPs : combatting toxic threats in the Arctic
Bibliographic record
Abstract
In addition to co-editing, David Downie is a contributing author, “Global POPs Policy: The 2001 Stockholm Convention on Persistent Organic Pollutants" and (with Terry Fenge), "“Introduction". Book description: Representatives of 111 nations gathered in Stockholm in May 2001 to sign a legally binding convention to eliminate or reduce emissions of pesticides, insecticides, and other industrial combustion by-products. Long-range transport by air and water carries many of these pollutants to the circumpolar north, where they threaten the health and cultural survival of Inuit and other northern Indigenous peoples. Northern Lights against POPs tells the many-faceted scientific, policy, legal, and advocacy story that led to the Stockholm convention. Unique in its perspective, scope, and breadth, it reveals the key links among environmental and health science, international politics, advocacy, law, and global negotiations. Never before have public health concerns articulated by northern Indigenous peoples in Canada and throughout the circumpolar Arctic had such a direct impact on global policy-making. Authors show how research on POPs (persistent organic pollutants) in the Arctic from the mid-1980s influenced international negotiations and analyze the potential for the convention to be effective. Contributors include elected representatives, researchers, civil servants, Indigenous people who participated in the negotiations, and scientists who provided the compelling Arctic data that prompted the United Nations Environment Programme to sponsor negotiations.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.007 | 0.004 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.016 | 0.002 |
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".