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Record W3001418019 · doi:10.1017/s0007123420000113

Party Cues in the News: Democratic Elites, Republican Backlash, and the Dynamics of Climate Skepticism

2020· article· en· W3001418019 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

VenueBritish Journal of Political Science · 2020
Typearticle
Languageen
FieldSocial Sciences
TopicClimate Change Communication and Perception
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsSkepticismElitePublic opinionClimate changePolitical scienceDemocracyConstruct (python library)BacklashDynamics (music)Political economySociologyLawPoliticsEpistemologyPhilosophy

Abstract

fetched live from OpenAlex

Supporters of the Republican Party have become much more skeptical of the science of climate change since the 1990s. This article argues that out-group cues from Democratic elites caused a backlash that resulted in greater climate skepticism. The authors construct aggregate measures of climate skepticism from nearly 200 public opinion polls at the quarterly level from 2001 to 2014 and at the annual level from 1986 to 2014. They also build time-series measures of possible contributors to climate skepticism using an automated media content analysis. The analyses provide evidence that cues from party elites – especially from Democrats – are associated with aggregate dynamics in climate change skepticism, including among supporters of the Republican Party. The study also involves a party cue survey experiment administered to a sample of 3,000 Americans through Amazon Mechanical Turk to provide more evidence of causality. Together, these results highlight the importance of out-group cue taking and suggest that climate change skepticism should be examined through the lens of elite-led opinion formation.

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)0.004
metaresearch head score (Gemma)0.004
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
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 score0.808
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.003
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.151
GPT teacher head0.396
Teacher spread0.245 · 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