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Record W4407923500 · doi:10.1080/08941920.2025.2463075

Small and Rural Local Government Environmental Sustainability Plans, Programs and Policies in Cascadia: A Comparative Analysis

2025· article· en· W4407923500 on OpenAlexafffundabout
Erika Allen Wolters, Brent S. Steel, Tamara Krawchenko, Sadaf Farooq

Bibliographic record

VenueSociety & Natural Resources · 2025
Typearticle
Languageen
FieldEnvironmental Science
TopicSustainable Development and Environmental Policy
Canadian institutionsFulbright CanadaUniversity of Victoria
FundersFulbright CanadaUniversity of Victoria
KeywordsSustainabilityGovernment (linguistics)Environmental planningLocal governmentEnvironmental policyEnvironmental resource managementBusinessPolitical sciencePublic administrationGeographyEnvironmental scienceEcology

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.076
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.006
GPT teacher head0.223
Teacher spread0.217 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations1
Published2025
Admission routes3
Has abstractyes

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