Community-based responses to climate hazards: typology and global analysis
Bibliographic record
Abstract
The severity and frequency of climate change hazards are increasing around the world. Because the impacts are most acutely felt in local communities, it is critical to improve understanding of the response options that are available for and being chosen by communities. We conducted a mixed methods analysis of case studies reporting community-based responses to climate change hazards. Based on content analysis of published case studies, we generated an emergent evidence-based typology of such responses according to their nature and goals. Using this typology, we quantitatively analysed more than 1500 response examples and determined the patterns with which community-level climate change adaptation and disaster mitigation strategies vary across world regions and across economic and governance conditions. Specifically, diversity of responses is lower in developing countries, and implementation of local-level policy and planning responses is less frequent in countries characterised by low governance quality. Our results confirm that, although there is much that local communities can do to respond to the challenges of climate change, there is also a need for increased support of local activities. By synthesising data from many local studies, our research provides a first global evidence base for local-level climate change adaptation policy.
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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 | 0.001 | 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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".