A combination of four planning models for use in First Nations environmental health
Bibliographic record
Abstract
This project is an inquiry into understanding community-based planning models that may be used for First Nations' environmental health to contribute to more equitable partnerships. The purpose of this project was to conduct a review of the literature in order to select planning models that could better address the environmental health needs in relation to assessment, ecological considerations, culturally sustainable community development, and comprehensive First Nations community planning. My questions in this inquiry were: "Which community-based planning approaches may be used for First Nations environmental health programs and projects?" and "What specific models when combined together might be used by First Nations people, environmental health professionals; and others in the planning of environmental health programs and endeavours that contribute to the development of healthy, sustainable First Nations communities?" To answer these questions, and following an extensive review of the literature, I focused on two books, one article, and one manual as contributions to the field of environmental health planning and the importance of using models respectful of culture. The outcomes of the inquiry were enhanced by my own professional experience within First Nations environmental health and an awareness of planning between cultural paradigms. As a result, this project demonstrates that a select variety of planning models need to be considered as a foundation for developing healthy sustainable communities in order to connect environmental health with long-range comprehensive community planning. Such an opportunity offers First Nations and non-First Nations planners a way to proceed that has the potential to address the present, complex needs and future aspirations of community members within a larger regional, global context.
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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 | 0.016 | 0.016 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.004 | 0.006 |
| Science and technology studies | 0.006 | 0.008 |
| Scholarly communication | 0.013 | 0.013 |
| Open science | 0.004 | 0.007 |
| Research integrity | 0.003 | 0.006 |
| Insufficient payload (model declined to judge) | 0.012 | 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".