Bibliographic record
Abstract
Este artigo foca nos impactos das mudanças climáticas na saúde mental de jovens e adultos/as, especificamente os/as estudantes universitários/as de programas relacionados com o meio ambiente. A metodologia photovoice foi utilizada como ferramenta de recolha de dados e analisada como potencial intervenção para gerir os impactos na saúde mental relacionado com o clima e empoderar os/as jovens. Os/As jovens envolvidos/as experimentaram diversos impactos na saúde mental relacionados com as mudanças climáticas, derivados de experiências, incluindo a própria educação ambiental. Para lidar com isso, os/as participantes recorreram a fontes primárias de resiliência, incluindo passar tempo na natureza, participar de atividades na comunidade, promover ações ambientais e praticar reflexão consciente. O estudo a partir da metodologia photovoice reflete elementos-chave dessas estratégias de coping e os/as jovens experimentaram melhorias subjetivas na saúde mental e bem-estar, desenvolvendo empoderamento. Concluímos, recomendando a gestão dos impactos na saúde mental relacionados com as mudanças climáticas, melhorando o apoio à saúde mental em instituições pós-secundárias. Recebido: 25/1/2022 Aceite: 25/5/2022
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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 | 0.003 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.008 | 0.005 |
| Scholarly communication | 0.016 | 0.012 |
| Open science | 0.002 | 0.010 |
| Research integrity | 0.007 | 0.006 |
| Insufficient payload (model declined to judge) | 0.230 | 0.103 |
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".