Updated review on contaminant communication experiences in the circumpolar Arctic
Bibliographic record
Abstract
Arctic populations are amongst the highest exposed populations to long-range transported contaminants globally, with the main exposure pathway being through the diet. Dietary advice is an important immediate means to address potential exposure and help minimize adverse health effects. The objective of this work is to enable easier access to dietary advice and communication guidance on contaminants with a focus on the Arctic. This manuscript is part of a special issue summarizing the Arctic Monitoring and Assessment Programme's Assessment 2021: Human Health in the Arctic. The information was derived with internet searches, and by contacting relevant experts directly. Results include risk communication efforts in European Arctic countries, effectiveness evaluation studies for several Arctic countries, experience of social media use, and the advantages and challenges of using social media in risk communication. We found that current risk communication activities in most Arctic countries emphasize the importance of a nutritious diet. Contaminant-related restrictions are mostly based on mercury; a limited amount of dietary advice is based on other contaminants. While more information on effectiveness evaluation was available, specific information, particularly from Arctic countries other than Canada, is still very limited.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.005 | 0.006 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".