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Record W4393229738 · doi:10.1080/02697459.2024.2323886

Are rural places prepared for the energy transition? An evaluation of land use plans in rural Manitoba

2024· article· en· W4393229738 on OpenAlexaffabout
Michael Kvern, Leith Deacon, Dave Guyadeen

Bibliographic record

VenuePlanning Practice and Research · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicSocial Acceptance of Renewable Energy
Canadian institutionsUniversity of Guelph
Fundersnot available
KeywordsEnvironmental planningTransition (genetics)Energy (signal processing)Land usePolitical scienceGeographyRegional scienceBusinessEconomic growthPublic administrationCivil engineeringEconomicsEngineering

Abstract

fetched live from OpenAlex

As energy systems transition from fossil fuels to renewable sources, energy infrastructure will become a predominant land use, especially in rural areas. This poses a challenge for municipalities who need to adapt land use planning frameworks to more renewable energy. Using plan quality evaluation, this paper assesses how 57 rural official plans in Manitoba (Canada) are attempting to integrate energy planning. Consideration of energy within plans is poor, especially for implementation mechanisms and fact base. While rural communities are the forefront of the energy transition, existing land use planning frameworks are maladapted to enable it.

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)0.010
metaresearch head score (Gemma)0.016
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.124
Threshold uncertainty score0.326

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0100.016
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.004
Science and technology studies0.0050.003
Scholarly communication0.0040.001
Open science0.0010.002
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.184
GPT teacher head0.478
Teacher spread0.294 · 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 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

Citations4
Published2024
Admission routes2
Has abstractyes

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