Compensating personal climate response inefficacy with political conservatism?
Bibliographic record
Abstract
Abstract People grapple with the reality that their individual actions are too insignificant to impact climate change—a phenomenon known as personal climate response inefficacy. The compensatory control theory articulates that people may turn to overarching social institutions or ideologies (e.g., conservatism) when they lack personal control. Inspired by this theory, the present research explored whether individuals experiencing personal climate response inefficacy are more likely to embrace political conservatism. Study 1 analyzed data from the European Social Survey ( N = 44,387) and provided preliminary evidence of a positive association between personal climate response inefficacy and political conservatism. Study 2 utilized four‐wave longitudinal data from 1008 American participants and identified a consistent within‐person cross‐lagged effect, where personal climate response inefficacy predicted increased political conservatism over time. Both studies ruled out the potential conflating effect of the perceived threat of climate change. Study 3 collected cross‐sectional data from 270 Americans and replicated the major findings while controlling for the potential confounding effect of general self‐efficacy. Study 4 ( N = 261) manipulated personal climate response inefficacy yet only provided partial supportive evidence for our main findings. These pieces of evidence suggest that psychological processes specific to climate change can have spillover effects on other domains.
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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 | 0.017 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".