Strategies for Transforming Coastal Governance: Addressing Interdependent Dimensions
Bibliographic record
Abstract
Coastal areas are places where land and sea meet. These places offer many socio‐economic opportunities but also face profound social and environmental challenges that are often exacerbated by limitations in current governance systems. These limitations include a lack of coordination, unclear mandates and roles, fragmented knowledge, power dynamics, and insufficient stakeholder involvement. Transforming coastal governance is therefore needed to enhance the effectiveness and legitimacy of governance systems and their institutions, but current practices and past experiences have shown that changing governance is anything but easy. In this article, we analyse how three critical governance dimensions: (1) forms of integration of land and sea management; (2) forms of knowledge mobilized; and (3) forms of democracy in their interplay, shape possibilities and limits for transforming governance. Drawing on insights from the literature and three case studies from Spain, the UK, and Norway, we highlight how these different governance dimensions are strongly interrelated and should be addressed in coherent ways to make governance more effective and legitimate.
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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 | 0.018 | 0.014 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.005 | 0.030 |
| Scholarly communication | 0.017 | 0.011 |
| Open science | 0.002 | 0.017 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.005 | 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".