Nature prescribing: emerging insights about reconciliation-based and culturally inclusive approaches from a tricultural community health centre
Bibliographic record
Abstract
This commentary highlights the importance of social and nature prescribing programs reflecting culturally diverse perspectives and practices. Creating and holding space for Indigenous and other worldviews should be a key priority of nature prescribing, a relatively recent practice in Canada that recognizes and promotes health benefits associated with engaging in a variety of activities in natural settings. Central to designing and delivering nature prescribing that is culturally inclusive and grounded in fulfilling obligations of reconciliation is recognizing the ongoing dominance of Western worldviews and their associated implications for decolonizing and Indigenizing nature-based programming. Consciously working to expand Western values, with the aim of extending nature prescribing practices beyond mere nature exposure to fostering emotional connections to nature, is a critically important part of the ongoing development of nature-based interventions and nature prescribing.
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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 | 0.017 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.031 | 0.045 |
| Scholarly communication | 0.015 | 0.007 |
| Open science | 0.005 | 0.012 |
| Research integrity | 0.007 | 0.014 |
| 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".