MétaCan
Menu
Back to cohort
Record W3158456108 · doi:10.22215/cjers.v14i2.2764

Environmental Issues in Recent British and Canadian Elections

2021· article· en· W3158456108 on OpenAlexaffvenueabout
Harold D. Clarke, Jon H. Pammett

Bibliographic record

VenueThe Canadian Journal of European and Russian Studies · 2021
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicEnergy, Environment, Economic Growth
Canadian institutionsCarleton University
Fundersnot available
KeywordsAppealVotingPolitical sciencePoliticsPublic opinionGeneral electionRhetoricPublic administrationPolitical economyPublic relationsSociologyLaw

Abstract

fetched live from OpenAlex

ENVIRONMENTAL ISSUES IN RECENT BRITISH AND CANADIAN ELECTIONS The 2019 elections in Britain and Canada illustrate the difficulties in communication between a concerned public and prospective office-holders on the most critical set of issues of our times. An increased level of public awareness and concern about the state of the environment has been expressed in public opinion polls, social movement activity has increased, and Green parties have expanded their appeal. Despite these developments in recent years, environmental issues have not been able to exert a major impact on individual voting behaviour in elections, or on overall election outcomes. Issues related to the environment are usually treated, by both politicians and the public, in valence terms. Valence issues are ones upon which there is broad consensus about the goals of public policy, and political debate focuses not on "what to accomplish" but rather on "how to do it" and "who is best able." Regarding the environment, general formulations like global warming and climate change prompt politicians to offer concerned rhetoric and engage in virtue signaling, but specific policy proposals are often absent. This paper examines four reasons why environmental/climate change issues did not have a major impact on the 2019 Canadian and British elections. First, environmental concern in society at large was imperfectly translated into election issues. Second, the major political parties produced inadequate and unconvincing environmental manifestos. Third, environmental issues were not central to most voting decisions. Fourth, environmental issues had limited impacts on election outcomes.

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 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)0.000
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.795
Threshold uncertainty score0.935

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.025
GPT teacher head0.197
Teacher spread0.172 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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
Published2021
Admission routes3
Has abstractyes

Explore more

Same venueThe Canadian Journal of European and Russian StudiesSame topicEnergy, Environment, Economic GrowthFrench-language works237,207