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Record W4403177785 · doi:10.1080/09644016.2024.2413345

Why path dependence leads to a fossilized Alberta: regionalism and the climate transition in Canada

2024· article· en· W4403177785 on OpenAlexafffundabout
Louis Massé

Bibliographic record

VenueEnvironmental Politics · 2024
Typearticle
Languageen
FieldEnergy
TopicGlobal Energy and Sustainability Research
Canadian institutionsUniversity of Ottawa
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsRegionalism (politics)Path dependenceClimate changePath (computing)Political scienceEconomic geographyTransition (genetics)GeologyEarth scienceGeographyEconomicsPoliticsChemistryOceanographyLaw

Abstract

fetched live from OpenAlex

Canada is the world’s fourth largest producer of oil and fifth largest producer of natural gas. Yet, the country faces a ‘twin’ challenge in tackling the climate crisis. On the one hand, Canada’s federal climate goals state that it must achieve net-zero carbon emissions by 2050. On the other hand, regionalism stronghold in fossil-producing provinces lead to difficult trade-offs between an ambitious climate transition and reluctant actors supporting the fossil fuel industry. This situation is characterized as ‘fossilized’ petro-provinces by political scientist Angela Carter. This article explores how Alberta, Canada’s largest oil and natural gas producer, became fossilized. The article develops a path dependence argument organized around the role of regionalism in Alberta’s political development. Regionalism is a crucial persistent feature of Alberta to explain its fossilization because it influenced the formation of an interdependence between the government and the industry, a distinct political culture, and a conservative-led party system.

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)0.001
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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.881
Threshold uncertainty score0.863

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0210.010
Scholarly communication0.0070.002
Open science0.0010.003
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0060.000

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 head0.220
Teacher spread0.214 · 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 designNot applicable
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 routes3
Has abstractyes

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