Are local climate adaptation policies credible? A conceptual and operational assessment framework
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
After the Paris Agreement that put stronger emphasis on the development of climate change adaptation policies and on the definition of financing mechanisms, there is a patent need to track whether actual planning efforts are proving sufficient. This entails the development of assessment methods and metrics as plans are drafted and actions implemented. To this end, this paper explores the concept of credibility as a critical issue in climate policy and develops an Adaptation Policy Credibility (APC) conceptual and operational assessment framework for helping to allocate public funding and private investments, and for implementing and catalysing climate policy. Through a pilot testing in four early-adopting cities (Copenhagen, Durban, Quito and Vancouver), a clear potential for large-n tracking and assessment exercises of local climate adaptation plans is envisaged. The APC approach might also be useful to guide individual cities that aim to improve their adaptation planning and policy-making processes.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 it