Do climate concerns and worries predict energy preferences? A meta-analysis
Bibliographic record
Abstract
Public perceptions of energy choices will play a major role in the energy transition. Climate-related emotions, particularly concerns and worries, influence these perceptions, as they signal a heightened awareness of climate risks and greater personal salience of climate change. Here we conduct a series of meta-analyses to estimate whether climate worries and concerns influence energy preferences (k = 233; N = 85,285; 36 countries). Our findings reveal that climate worries and concerns translate into support for renewable energy, particularly solar and wind, and modest opposition to fossil fuels, particularly coal and gas. Climate worries and concerns are not associated with nuclear energy, albeit with a high degree of variance. Socio-demographic moderators, such as gender, education, and political orientation, did not influence these associations, while age and national energy supply attenuated these associations. These results suggest that climate concerns and worries translate into support for renewable energy, but not equal opposition to fossil fuels. More broadly, this meta-analysis underscores the role of climate-related emotions in shaping energy preferences, providing insights into the influence factors of energy policy support, the psychology of climate change, and climate change communication.
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 imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 teacher head, 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".