A Social Ecology of Youth and Planetary Wellbeing in Various Contexts
Bibliographic record
Abstract
Abstract The United Nations has identified overarching ecological, climate and social crises as causes of unprecedented declines in human wellbeing in 90% of the world’s countries and cautioned about a “generational catastrophe” for youth wellbeing (2020). This paper presents our process and methods of working alongside youth in Chile, Canada, Costa Rica, and Belize in our Partnership for Youth and Planetary Wellbeing project. We describe our social ecology of youth wellbeing framework and the research practices that are youth-centred, participatory and anticolonial including the development of Youth Advisory Committees, co-design of research activities and co-analysis of 117 youth interviews. Co-analyses examines perceptions of wellbeing amidst overlapping social and ecological crises and what it means for young people to live well based in relations with community, territory and biosphere. Implications for youth and planetary wellbeing partnerships and research are offered as we continue to learn alongside these young people and their communities.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.009 | 0.011 |
| Scholarly communication | 0.007 | 0.003 |
| Open science | 0.001 | 0.013 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".