Mainstreaming decarbonization through local climate budgets in Norwegian municipalities
Bibliographic record
Abstract
Climate budgets are increasingly being used in local climate governance, but it is not clear whether they have the potential to drive systemic change toward decarbonization. This study uses a political dynamics of decarbonization framework to assess the transformative potential of municipal climate budgets to catalyze changes across cultural, economic, political, and technological systems to overcome carbon lock-in. Document analysis and interviews with climate budget experts from Oslo, Fredrikstad, Hamar, Bergen, Arendal, Bærum, Asker and the county of Agder in Norway were employed in this study to identify and discuss transformative conditions for decarbonization. Climate budgets are used to integrate climate change mitigation as a core element of municipal governance. This approach aims to integrate climate change mitigation into existing decision-making mechanisms and expand the mandates of municipal departments and agencies in executing and overseeing climate actions. Local climate budgets are also being used to catalyze changes across cultural, economic, political, and technological systems through the alignment of new laws, regulations, financial and institutional capacities, inter-municipal coalitions, and cooperation with the private sector. However, climate budgeting in cities and local governments faces multiple barriers. These include a lack of jurisdiction over emissions accounted for in climate budgets; inadequate legal frameworks to support municipal climate actions; and competition for financial and institutional resources with other public services expected by city residents. These findings deepen our understanding of the transformative change potential in local climate action experiments by emphasizing the role of political dynamics in overcoming carbon lock-in.
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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 | 0.007 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.002 | 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 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".