Reaching for environmental health justice: Canadian experiences for a comprehensive research, policy and advocacy agenda in health promotion
Bibliographic record
Abstract
Spatial disparities in environmental quality and practices are contributing to rising health inequalities worldwide. To date, the field of health promotion has not contributed as significantly as it might to a systematic analysis of the physical environment as a determinant of health nor to a critique of inequitable environmental governance practices responsible for social injustice-particularly in the Canadian context. In this paper, we explore ways in which health promotion and environmental justice perspectives can be combined into an integrated movement for environmental health justice in health promotion. Drawing on Canadian experiences, we describe the historical contributions and limitations of each perspective in research, policy and particularly professional practice. We then demonstrate how recent environmental justice research in Canada is moving toward a deeper and multi-level analysis of environmental health inequalities, a development that we believe can inform a comprehensive research, policy and advocacy agenda in health promotion toward environmental health justice as a fundamental determinant of health. Lastly, we propose four key considerations for health promotion professionals to consider in advancing this movement.
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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 | 0.015 | 0.020 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.006 |
| Science and technology studies | 0.059 | 0.025 |
| Scholarly communication | 0.012 | 0.004 |
| Open science | 0.003 | 0.011 |
| Research integrity | 0.007 | 0.011 |
| Insufficient payload (model declined to judge) | 0.005 | 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".