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Record W4200207449 · doi:10.1016/j.erss.2021.102462

Rooted in place: Regional innovation, assets, and the politics of electric vehicle leadership in California, Norway, and Québec

2021· article· en· W4200207449 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.
fundA Canadian funder is recorded on the work.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueEnergy Research & Social Science · 2021
Typearticle
Languageen
FieldEngineering
TopicElectric Vehicles and Infrastructure
Canadian institutionsUniversity of OttawaUniversity of TorontoUniversity of Waterloo
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsElectrificationPoliticsNormalization (sociology)Political scienceBusinessIndustrial organizationEngineeringElectricitySociologySocial science

Abstract

fetched live from OpenAlex

In the media, Norway, California, and Québec are widely acknowledged as innovative leaders in transportation electrification. Yet, what does leadership mean and how did these jurisdictions achieve it? We contend that leadership reflects both intentional forethought through early, experimental and innovative policy to promote electric vehicles and the on-the-ground successful outcomes of these policies. All three jurisdictions have embarked on different leadership paths. We argue that these differences are a function of how electromobility policy entrepreneurs engaged unique pre-existing local assets and activated similar political mechanisms of normalization, coalition building and capacity building. When policy actors harness mutually reinforcing political and industrial dynamics, electric vehicle policies can scale up. Eventually, these dynamics may lead to new industrial path development and the decarbonization of the transportation sector.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.703
Threshold uncertainty score0.667

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.005
Science and technology studies0.0000.001
Scholarly communication0.0000.000
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 head0.045
GPT teacher head0.286
Teacher spread0.241 · 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