Indigenous Health and Climate Change - A scoping review on climate-health outcomes for First Nations in Canada
Bibliographic record
Abstract
Indigenous populations in Canada are generally categorized as vulnerable to the impacts of \nclimate change. Despite this, research is lacking in terms of location- and populations-specific \ndata on how climate change affects their health. To address this gap, we conducted a scoping \nreview to explore the impact of climate change on the health of First Nations communities in \nCanada. Our study also investigated how climate change influences the Inverse Care Law \n(ICL) in relation to First Nations' health.\nWe utilized a scoping review methodology, searching 4 databases to explore the theme of this \nthesis. Our approach to understanding health was framed through an "Indigenous lens," \nencompassing not only physical and mental health perspectives but also spiritual and \ncommunity health considerations. The generated literature was numerically and thematically \nanalyzed. Our findings reveal that climate change exacerbates existing health disparities \namong First Nations, impacting traditional activities, diet, finances, cultural identity, and \nmental well-being. This exacerbation deepens the burden of lifestyle-related diseases\nexacerbates health disparities through perpetuating and/or exacerbating the Inverse Care Law \n(ICL). The analysis also looks at the importance of incorporating Indigenous-specific health \nindicators for understanding and addressing these multifaceted impacts.\nWe also recognize the dual characterization of First Nations as vulnerable yet resilient. While \nclimate change poses significant threats, communities demonstrate adaptive capacity and \nIndigenous Health and Climate Change\nresilience. However, the label of vulnerability can have negative connotations, potentially \nundermining autonomy and self-determination.\nOur research identifies significant knowledge gaps, particularly regarding gendered \nperspectives. Additionally, research on First Nations in the Prairie region remains limited, \nemphasizing the need for more inclusive studies. The small number of eligible studies also \nhighlight the need for continued focus on the theme of this thesis. \nIn conclusion, our study underscores the complex and interconnected impacts of climate \nchange on First Nations' health. Holistic and culturally sensitive approaches to health \nmeasurement and intervention are essential. Addressing knowledge gaps and including \ndiverse perspectives are crucial for mitigating the health impacts of climate change on \nIndigenous populations and supporting their journey towards greater health equity and self determination
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 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 | 0.010 | 0.041 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.005 |
| Bibliometrics | 0.016 | 0.026 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.006 | 0.002 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".