Climate change, poverty, and health: A scoping review of the Canadian context
Bibliographic record
Abstract
Purpose: Those experiencing poverty tend to be more exposed to the effects of climate change and less prepared to withstand them, increasing their health vulnerability. Exploring the research conducted in Canada on the interacting influences of climate change and poverty on the physical and mental health can thus help to identify key areas of concern. Research question: In the Canadian context, what are the impacts and implications of climate change and weather extremes on the physical and mental health of those experiencing poverty, as evidenced in the peer-reviewed academic literature? Search engines: Scopus, Pubmed, PsycINFO, Google scholar Search string: ( poverty OR impoverish* OR socioeconomic OR ses OR income ) AND ( climate OR weather ) AND ( mental OR health OR trauma* OR stress* OR anxi* OR eco-anxiety OR depress* OR solastalgia OR distress OR grief OR psycholog* OR well-being OR ill* OR disease OR disorder ) AND ( canad* ) AND ( LIMIT-TO ( DOCTYPE , "re" ) )
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.052 | 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 teacher head, 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".