Climate Change: What Are the Implications of Worldview, Political Orientation, Values on Climate Belief and Engagement in the French Context?
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".