Small and Rural Local Government Environmental Sustainability Plans, Programs and Policies in Cascadia: A Comparative Analysis
Bibliographic record
Abstract
Small and rural local governments currently face many ongoing and numerous new challenges that complicate their task of sustaining current public services and programs. How government officials adapt to these changes will affect the long-term viability of local governments in both the U.S. and Canadian contexts. This study examines the presence or absence of environmental sustainability plans, policies, or programs in small and rural local governments in the “Cascadia” region of Canada and the U.S. (British Columbia, Oregon, and Washington). Using surveys and interviews of Cascadia local government leaders during the summer and fall of 2023, correlates of policy adoption are examined, including cultural, demographic, economic, and political factors. Findings suggest that environmental sustainability is a priority in Canada and the U.S. and that overcoming existing challenges including funding, staffing, and political salience, could help facilitate environmental sustainability policies and programs.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".