Climate change adaptation to extreme heat: a global systematic review of implemented action
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract Extreme heat events impact people and ecosystems across the globe, and they are becoming more frequent and intense in a warming climate. Responses to heat span sectors and geographic boundaries. Prior research has documented technologies or options that can be deployed to manage extreme heat and examples of how individuals, communities, governments and other stakeholder groups are adapting to heat. However, a comprehensive understanding of the current state of implemented heat adaptations—where, why, how and to what extent they are occurring—has not been established. Here, we combine data from the Global Adaptation Mapping Initiative with a heat-specific systematic review to analyze the global extent and diversity of documented heat adaptation actions (n = 301 peer-reviewed articles). Data from 98 countries suggest that documented heat adaptations fundamentally differ by geographic region and national income. In high-income, developed countries, heat is overwhelmingly treated as a health issue, particularly in urban areas. However, in low- and middle-income, developing countries, heat adaptations focus on agricultural and livelihood-based impacts, primarily considering heat as a compound hazard with drought and other hydrological hazards. 63% of the heat-adaptation articles feature individuals or communities autonomously adapting, highlighting how responses to date have largely consisted of coping strategies. The current global status of responses to intensifying extreme heat, largely autonomous and incremental yet widespread, establishes a foundation for informed decision-making as heat impacts around the world continue to increase.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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 it