Crimes against future inuit generations: Heavy metals and persistent organic pollutants (POPs)
Bibliographic record
Abstract
In the preamble of the 2001 Stockholm Convention on 'Persistent Organic Pollutants' we find the following acknowledgement: ' that the Arctic ecosystems and Indigenous communities are particularly at risk because of the biomagnification of persistent organic pollutants and that contamination of their traditional foods is a public health issue'. The vulnerability of the Indigenous populations of the Arctic to persistent organic pollutants ('POPs') was an impetus behind the 'Stockholm Convention' and although the relationship between POPs and the health of Indigenous peoples, especially children and the unborn, has been known for a very long time, there has been little in terms of legislation and public policy initiatives to diminish toxic chemicals in the food and natural environment of the Inuit. In addition to POPs, the children and adults of the Arctic communities are also disproportionately exposed to heavy metal contamination due to the presence of mercury, lead and cadmium, among others. In 2013, the 'Minamata' Convention on Mercury was adopted, under the auspices of the United Nations Environment Programme ('UNEP') and building on the 1998 to the 1979 Convention on Long-Range 'Transboundary Air Pollution on Heavy Metals'. Given the long-term effects on the Inuit of these substances, it begs the question whether this situation is in fact a crime against future generations of the Inuit.
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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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.004 | 0.005 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.003 | 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".