Global evidence of constraints and limits to human adaptation
Bibliographic record
Abstract
Abstract Constraints and limits to adaptation are critical to understanding the extent to which human and natural systems can successfully adapt to climate change. We conduct a systematic review of 1,682 academic studies on human adaptation responses to identify patterns in constraints and limits to adaptation for different regions, sectors, hazards, adaptation response types, and actors. Using definitions of constraints and limits provided by the Intergovernmental Panel on Climate Change (IPCC), we find that most literature identifies constraints to adaptation but that there is limited literature focused on limits to adaptation. Central and South America and Small Islands generally report greater constraints and both hard and soft limits to adaptation. Technological, infrastructural, and ecosystem-based adaptation suggest more evidence of constraints and hard limits than other types of responses. Individuals and households face economic and socio-cultural constraints which also inhibit behavioral adaptation responses and may lead to limits. Finance, governance, institutional, and policy constraints are most prevalent globally. These findings provide early signposts for boundaries of human adaptation and are of high relevance for guiding proactive adaptation financing and governance from local to global scales.
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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 | 0.026 | 0.073 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.008 | 0.015 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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".