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Record W3002125664 · doi:10.1080/09644016.2019.1708538

Climate change risk perceptions and the problem of scale: evidence from cross-national survey experiments

2020· article· en· W3002125664 on OpenAlex
Endre Tvinnereim, Ole Martin Lægreid, Xiaozi Liu, Daigee Shaw, Christopher P. Borick, Érick Lachapelle

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.

Bibliographic record

VenueEnvironmental Politics · 2020
Typearticle
Languageen
FieldSocial Sciences
TopicClimate Change Communication and Perception
Canadian institutionsUniversité de Montréal
FundersSocial Sciences and Humanities Research Council of CanadaNorges Forskningsråd
KeywordsClimate changeOptimismOptimism biasSurvey data collectionPerceptionScale (ratio)Empirical evidenceGeographySurvey researchConfoundingPsychologyDemographic economicsSocial psychologyEconomicsApplied psychology

Abstract

fetched live from OpenAlex

We examine the concept of spatial optimism, defined as the tendency for individuals to perceive climate change as less threatening to themselves than to people in geographically more distant locations. Existing studies find mixed evidence of this phenomenon, while the methods employed often fail to rule out confounding factors. To resolve these empirical and methodological tensions, we present results from a survey experiment fielded in nine countries spanning Europe, North America, and Asia. The survey finds that respondents systematically perceive climate change as a greater threat to the world than to themselves, in nine countries. However, while groups that may be considered more vulnerable to climate change often display higher levels of perceived overall risk, the survey finds evidence of spatial bias to be systematic across and within cases. Future research should apply this measurement strategy in more vulnerable countries and over time.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.120
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.446
GPT teacher head0.448
Teacher spread0.002 · 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