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Local responses to regional mandates: assessing municipal greenhouse gas emissions reduction targets in British Columbia

2013· article· en· W324311759 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueSustainability Science Practice and Policy · 2013
Typearticle
Languageen
FieldSocial Sciences
TopicUrban Transport and Accessibility
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsLegislationGreenhouse gasPer capitaClimate changeWork (physics)GeographyEnvironmental protectionPopulationPopulation growthNatural resource economicsBusinessAgricultural economicsPolitical scienceEconomicsEnvironmental healthEcologyEngineering

Abstract

fetched live from OpenAlex

Local governments around the world face external and internal pressures to adopt climate change mitigation strategies. Provincial legislation in the Canadian province of British Columbia has recently mandated that all municipalities adopt targets for reducing greenhouse-gas emissions. Lack of specificity in the legislation gives rise to the possibility that even if compliance with the legislation is universal it could nonetheless result in minimal reductions in emissions releases. This article examines the response to the legislation of twenty municipalities in British Columbia’s most populous regions. We hypothesized that noncompliance would be rampant and that cities with large populations, high residential densities, lower growth rates, and prior climate change planning work would set more ambitious targets. However, findings indicate that municipal targets vary widely in terms of intensity, target year, and type of reduction and have little or no relationship to population, residential density, or growth rate. We found 90% compliance and some correlation between prior planning activities related to climate change and target intensity. Findings also indicate that despite the wide range of emissions targets by each municipality, provincial per capita targets would be met if each municipality were to achieve the targets that they have set by the 2050 target year.

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.

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)0.005
metaresearch head score (Gemma)0.013
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Science and technology studies, Scholarly communication
Consensus categoriesScience and technology studies
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.553
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.013
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
Science and technology studies0.0020.003
Scholarly communication0.0020.007
Open science0.0000.000
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 head0.023
GPT teacher head0.374
Teacher spread0.352 · 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