Climate change and its impact on the mental health well‐being of Indigenous women in Western cities, Canada
Bibliographic record
Abstract
Abstract This collaborative paper explores the interconnections between climate change and the mental health and well‐being of Indigenous women in Western Canada. As the impacts of climate change intensify globally, vulnerable populations, particularly Indigenous communities, face disproportionate and multifaceted challenges. Centering on Indigenous women in Western Canada, this study explores how the climate crisis magnifies Indigenous communities' mental health disparities. Drawing from the Indigenist feminist research approach, the investigation focuses on Indigenous women's lived experiences, perceptions, and land‐based coping strategies amidst climate challenges, while simultaneously addressing the unique social, cultural, and historical factors influencing their mental health vulnerabilities within the context of climate change. The findings shed light on the complex relationships between environmental degradation, ongoing colonial impacts on traditional practices, and the mental well‐being of Indigenous women. Concluding with implications for policy and community‐led interventions, this research contributes to the discourse on the intersectionality of climate change impacts and mental health, particularly focusing on Indigenous women in Western Canada.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.010 | 0.002 |
| Scholarly communication | 0.002 | 0.000 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 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".