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Record W2965645444 · doi:10.5539/jsd.v12n4p112

Climate Change: What Are the Implications of Worldview, Political Orientation, Values on Climate Belief and Engagement in the French Context?

2019· article· en· W2965645444 on OpenAlexvenueno aff
Oumar Marega, Philippe Chagnon, Séverine Frère, Anne-Peggy Hellequin, Hervé Flanquart, Iratxe Calvo-Mendieta, Baptiste Berry, Sophie Cornet

Bibliographic record

VenueJournal of Sustainable Development · 2019
Typearticle
Languageen
FieldSocial Sciences
TopicClimate Change Communication and Perception
Canadian institutionsnot available
FundersEuropean Regional Development FundRégion Hauts-de-FranceMinistère de l'Education Nationale, de l'Enseignement Superieur et de la Recherche
KeywordsBiology and political orientationOpposition (politics)SkepticismClimate changePoliticsPerceptionIdeologySocial psychologyContext (archaeology)SociologyEnvironmental ethicsPsychologyPolitical scienceEpistemologyGeographyEcologyLaw

Abstract

fetched live from OpenAlex

To what extent do our worldviews, political and religious beliefs and our values influence the way we perceive the climate emergency and the commitment to combat it in France? Through this question we pursue two clear objectives: firstly, to study the social dimensions of climate change and secondly to shed light on the vectors of engagement in the fight against climate change. Based on a perception survey we conducted in the Hauts-de-France region in 2017, we highlight how an approach that takes into account worldview, values and beliefs help us to understand the different attitudes towards CC perception and the fight against it. We show that the opposition between those who are convinced and those who are skeptical about CC refers to ideological differences that are deeply-rooted in the right-left political divide, but also in different beliefs and values. In addition, among the main vectors of climate engagement, our analyses highlight the importance of a worldview based on the finiteness of natural resources, values related to associative engagement and trust.

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)0.004
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: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.471
Threshold uncertainty score0.448

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
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 head0.183
GPT teacher head0.407
Teacher spread0.224 · 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 designQualitative
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

Citations2
Published2019
Admission routes1
Has abstractyes

Explore more

Same venueJournal of Sustainable DevelopmentSame topicClimate Change Communication and PerceptionFrench-language works237,207