Cancer and the Environment projects with four First Nations organizations: working together to address concerns about carcinogens in the environment
Bibliographic record
Abstract
SETTING: For First Nations people, human health and well-being are interconnected with a healthy environment. First Nations organizations commonly raise concerns regarding carcinogens in the environment; however, few case studies are available as guidance for working in a participatory and respectful way to help assess and address these concerns. INTERVENTION: Through four community-led pilot projects executed over two years, we collaborated with 15 participants from four First Nations organizations across four provinces to identify concerns related to environmental carcinogens and to address those concerns through an integrated knowledge translation (KT) approach. We co-developed and implemented strategic KT plans for each pilot project, and conducted evaluation surveys and interviews with participants at multiple time points to assess process, progress, barriers and facilitators, and impact. OUTCOMES: The activities and outputs of the pilot projects are available at www.carexcanada.ca . Participants identified 18 concerns, and we co-developed 24 knowledge products. Tailored fact sheets for communities and briefing notes for leadership were deemed most useful; interactive maps were deemed less useful. Evaluation indicated that the collaborative projects were effective in addressing the concerns raised regarding exposures to carcinogens. IMPLICATIONS: The participant-led approach and multi-year funding to support capacity enhancement and face-to-face engagement were facilitators to project success. However, participants did face important barriers to collaborate which should be considered in future projects of this kind: the most important being a lack of resources (people and time), given competing and often more urgent priorities.
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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 | 0.023 | 0.021 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.016 | 0.006 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.003 | 0.014 |
| Research integrity | 0.003 | 0.006 |
| Insufficient payload (model declined to judge) | 0.010 | 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".