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The Role of Local Government in Coal Transition: The Case of Rural Alberta

2024· article· en· W4401435851 on OpenAlexafffundvenueabout
Martin Mateus, Sean Markey, Laura Ryser, Greg Halseth, Lars Hällström

Bibliographic record

VenueCanadian Planning and Policy / Aménagement et politique au Canada · 2024
Typearticle
Languageen
FieldEngineering
TopicMining and Resource Management
Canadian institutionsUniversity of Northern British ColumbiaSimon Fraser University
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsTransition (genetics)CoalLocal governmentGovernment (linguistics)Political scienceBusinessPublic administrationGeographyChemistryArchaeologyLinguistics

Abstract

fetched live from OpenAlex

Since the 1980s, Canadian municipalities have experienced pressures due to legislative/policy reforms and the downloading of responsibilities from senior governments. This shift has affected daily operations as municipalities struggle with outdated financial and jurisdictional structures. Such pressures have been exacerbated in Alberta by provincial and federal ‘coal phase-out’ policies, as the coal industry has historically been a primary source of revenue for some communities. In response, municipalities have engaged in processes to generate revenue, maintain service levels, and diversify their economies. This research, in Parkland County and Forestburg, Alberta, explores impacts and responses associated with top-down policy change. Results indicate that senior government supports were inadequate in the delivery of effective transition supports, which created challenges for local governments grappling with transition impacts. Municipalities have developed innovative and entrepreneurial solutions in transition, but the research outlines lessons and policy recommendations to better integrate municipalities into future transition policy 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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.080
Threshold uncertainty score0.581

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0270.008
Scholarly communication0.0070.001
Open science0.0020.005
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0050.000

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 head0.004
GPT teacher head0.207
Teacher spread0.203 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
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
Published2024
Admission routes4
Has abstractyes

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