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Record W2952431084 · doi:10.1017/s0143814x19000175

The polarisation of energy policy in the US Congress

2019· article· en· W2952431084 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.

Bibliographic record

VenueJournal of Public Policy · 2019
Typearticle
Languageen
FieldSocial Sciences
TopicElectoral Systems and Political Participation
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsSalience (neuroscience)Energy policyConvergence (economics)Political scienceEnergy (signal processing)Climate policyPublic administrationPublic economicsEnvironmental policyEconomicsPolitical economyClimate changeMacroeconomicsEnvironmental economicsRenewable energyEngineeringPsychology

Abstract

fetched live from OpenAlex

Abstract Although energy policy used to be a nonpartisan issue in Congress, partisan conflicts over energy policies are intense these days. To examine how a nonpartisan issue became a highly partisan one, we create and use a new measure of energy policy positions of members of Congress. Our analyses of member behaviour show that, in addition to partisan realignment in the South, energy policy-specific factors – rising oil prices, the climate change debate since 1988, and the salience of energy policy in Congress – are significantly related to increasing party polarisation over energy policy. We also find that the increasing convergence between energy policy and environmental policy has significantly contributed to party polarisation over energy issues. The study thus provides important understanding of this specific policy area as well as insights into the party polarisation literature by demonstrating how policy-specific events and policy convergence transform a nonpartisan issue into a highly partisan one.

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)0.003
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.853
Threshold uncertainty score0.911

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
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 head0.044
GPT teacher head0.373
Teacher spread0.330 · 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