Interrogating ‘effectiveness’ in climate change adaptation: 11 guiding principles for adaptation research and practice
Bibliographic record
Abstract
The Paris Agreement articulates a global goal on adaptation, which aims to ensure an ‘adequate adaptation response’ to the ‘global temperature goal’, and requires countries to report progress through periodic global stocktakes. However, there remain conceptual and methodological challenges in defining an adaptation goal and mixed evidence on what effective adaptation looks like and how it can be enabled. In this review, we demonstrate how different normative views on adaptation outcomes, arising from different epistemological and disciplinary entry points, can lead to very different interpretations of adaptation effectiveness. We argue that how effectiveness is framed will significantly impact adaptation implementation and outcomes. This, furthermore, represents a way of exercising influence in adaptation decision-making. Eleven principles of effective adaptation are distilled as a way to pluralize guidance in international processes such as the Global Stocktake as well as national and sub-national exercises on tracking and monitoring adaptation.
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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 | 0.296 | 0.161 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.005 | 0.002 |
| Bibliometrics | 0.009 | 0.010 |
| Science and technology studies | 0.008 | 0.171 |
| Scholarly communication | 0.038 | 0.040 |
| Open science | 0.010 | 0.020 |
| Research integrity | 0.014 | 0.017 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".