Opportunities and challenges for financing women’s, children’s and adolescents’ health in the context of climate change
Bibliographic record
Abstract
Women, children and adolescents (WCA), especially in low-income and middle-income countries (LMICs), will bear the worst consequences of climate change during their lifetimes, despite contributing the least to global greenhouse gas emissions. Investing in WCA can address these inequities in climate risk, as well as generating large health, economic, social and environmental gains. However, women's, children's and adolescents' health (WCAH) is currently not mainstreamed in climate policies and financing. There is also a need to consider new and innovative financing arrangements that support WCAH alongside climate goals.We provide an overview of the threats climate change represents for WCA, including the most vulnerable communities, and where health and climate investments should focus. We draw on evidence to explore the opportunities and challenges for health financing, climate finance and co-financing schemes to enhance equity and protect WCAH while supporting climate goals.WCA face threats from the rising burden of ill-health and healthcare demand, coupled with constraints to healthcare provision, impacting access to essential WCAH services and rising out-of-pocket payments for healthcare. Climate change also impacts on the economic context and livelihoods of WCA, increasing the risk of displacement and migration. These impacts require additional resources to support WCAH service delivery, to ensure continuity of care and protect households from the costs of care and enhance resilience. We identify a range of financing solutions, including leveraging climate finance for WCAH, adaptive social protection for health and adaptations to purchasing to promote climate action and support WCAH care needs.
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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 | 0.007 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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".