Implementing coastal adaptation: assessing and explaining success by local governments in Nova Scotia, Canada
Bibliographic record
Abstract
As coastal communities increasingly plan for climate change, there is a need to understand factors that influence whether planned actions get implemented. This study examines the implementation of coastal adaptation actions across Nova Scotia, Canada, the first province in the country to establish a regional policy framework to address adaptation by requiring municipalities to prepare Municipal Climate Change Action Plans (MCCAPs). Using the MCCAPs from 20 coastal communities, this study employs a mixed-methods approach that includes content analysis, surveys, and expert interviews to follow up on the actions identified as priorities in these plans. It finds that the MCCAPs successfully stimulated coastal adaptation throughout the province: within six years, nearly 75% of the 331 priority actions in these plans were implemented to some degree. Logistic regression models, supported by interviews with municipal representatives, indicate that political continuity and public participation throughout the planning process are significant determinants of successful implementation.
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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 | 0.000 |
| 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".