Understanding governance barriers and enablers for municipal and regional transition towards sustainability—Presenting a comprehensive diagnostic tool based on six case studies in Sweden
Bibliographic record
Abstract
Abstract Municipal and regional leaders' achievements for synchronised sustainability transitions are still not enough. Systemic, systematic and strategic cross‐sectoral collaboration and co‐creation are needed. However, sectors isolated in silos leads to suboptimal measures and strategies, and a reductionist view on what hinders and enables joint action towards full sustainability. Consequently, methodological support for addressing the coordinative challenge is often not asked for. This study investigates the observed reductionist perspective as foundation for developing enhanced methodological support for strategic sustainable development (SSD) and further aimed to gain insight into how leaders can be better supported to understand their current reality of barriers and enablers for cross‐sectoral SSD work and to prototype such support. Results from fieldwork with leaders in six municipalities and regions suggest that both frequency and depth of barriers and enablers in relation to elements for SSD are insufficient. Nine categories were identified and combined with SSD core elements into a diagnostic tool.
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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 | 0.009 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".