Moving from local to global: The examples of the United Nations Sustainable Development Goals and the Okanagan Charter
Bibliographic record
Abstract
The United Nations Sustainable Development Goals (SDGs) set forth 17 broad goals that we should pursue globally to ensure the health of the planet and of humankind. Within each goal, several targets are identified. This article explores the overarching framework of the SDGs as a guide to ensuring human and planetary health. The one goal, Goal #3: Global Health and Wellbeing was described in more detail. Simultaneous to the development of the SDGs, a health promotion framework, the Okanagan Charter, was launched. The Okanagan Charter similarly identifies the calls to action and principles that are the foundation of the work. This article explores briefly the origins of the Okanagan Charter and describes the study that was conducted to explore the implementation of the Charter at the first 10 campuses to sign on to the Charter. The findings identify that systems approaches require leadership and engaged champions, effective communication structures, dedicated resources, work across silos, and development of targets and measures to gauge progress; these structures are crucial for effective systems approaches to complex initiatives such as holistic health promotion strategies. The article concludes with a discussion about future directions for the crucial health promotion agenda.
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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 | 0.005 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.015 | 0.018 |
| Scholarly communication | 0.012 | 0.010 |
| Open science | 0.001 | 0.014 |
| Research integrity | 0.004 | 0.007 |
| Insufficient payload (model declined to judge) | 0.008 | 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".