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Record W3183162417 · doi:10.20381/ruor-26685

A Literature Review on Polarization and on Energy and Climate Policy in Canada

2020· review· en· W3183162417 on OpenAlexaboutno aff
Rafael Aguirre

Bibliographic record

VenueuO Research (University of Ottawa) · 2020
Typereview
Languageen
FieldEconomics, Econometrics and Finance
TopicClimate Change Policy and Economics
Canadian institutionsnot available
Fundersnot available
KeywordsCommissionOil and natural gasResearch councilEnergy policyPetroleumNatural resourcePolitical scienceGeographyFossil fuelRenewable energyEngineeringLawGeologyGovernment (linguistics)

Abstract

fetched live from OpenAlex

This review explores scholarly literature on polarization as a general phenomenon as well as the state of knowledge over its extent and nature in the energy and environmental domain. Overall, the review finds that polarization as a general phenomenon has increased in Canada, as it has in other jurisdictions, notably the United States. There are some differences between the two countries: in both countries, there is evidence of increased affective polarization (strong positive/negative feelings towards political parties) and partisan sorting (views on policy issues polarized along partisan lines), but, contrary to the US, studies on Canada have not yet firmly established that partisan polarization (hardening of partisan identities) is on the rise. When it comes to polarization over energy and environment in Canada, there has been relatively scant research undertaken to understand the nature, extent and drivers of polarization.

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)0.003
metaresearch head score (Gemma)0.010
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: Review · Consensus signal: Review
Teacher disagreement score0.346
Threshold uncertainty score0.697

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.010
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0130.032
Science and technology studies0.0020.001
Scholarly communication0.0040.002
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0070.001

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 head0.133
GPT teacher head0.307
Teacher spread0.174 · 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
GenreReview

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

Citations0
Published2020
Admission routes1
Has abstractyes

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Same venueuO Research (University of Ottawa)Same topicClimate Change Policy and EconomicsFrench-language works237,207