Climate emergency declarations by local governments– what comes next?
Bibliographic record
Abstract
More than 2000 jurisdictions globally have declared climate emergencies. Climate emergency declarations are amongst the strongest climate change policy statements. Yet, there has been limited research focusing on what comes after a climate emergency declaration is made, and the extent to which subsequent planning includes ‘transformative’ elements. This research focuses on local governments in the State of Victoria, Australia, and analyses the emergency declarations and subsequent action plans of 39 Councils, applying an analytical framework that defines ‘transformative action’ as including mitigation and adaptation; collaboration action across and within Councils; inclusion of intersecting biodiversity emergency responses; acknowledgement of First Peoples’ knowledges and aspirations; and consideration of justice and equity. Results point to the importance of alliances and networks to push ambition and facilitate informed climate action planning. The research has potential to inform policy both locally and globally and progress understandings of the enabling conditions for transformative approaches.
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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 | 0.014 | 0.029 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.009 | 0.009 |
| Scholarly communication | 0.010 | 0.017 |
| Open science | 0.002 | 0.010 |
| Research integrity | 0.002 | 0.005 |
| Insufficient payload (model declined to judge) | 0.010 | 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".