The bidirectional relationship between interpersonal climate change discussion and climate change anxiety
Bibliographic record
Abstract
Emerging research has suggested that people may experience anxiety and distress about climate change (i.e., climate change anxiety), even for those who are not directly affected by extreme weather events. While previous research has demonstrated the benefit of interpersonal climate change discussion in promoting climate change beliefs, the literature has yet to examine the relationship between interpersonal climate change discussion and climate change anxiety. On the one hand, such discussion may increase people's exposure to climate change information and make them more focused on it, which possibly triggers more anxiety. On the other hand, previous studies suggest that climate change anxiety can be a normal and adaptive response to climate change, which motivates people to engage in behaviors aiming to address climate change. It is thus possible that climate change anxiety would promote interpersonal climate change discussion. In this research, we test this bidirectional relationship using a two-wave longitudinal design. Cross-lagged panel analyses revealed a positive bidirectional longitudinal link in both the U.S. and China, suggesting a potential feedback loop between climate change anxiety and interpersonal climate change discussion. Climate change anxiety would relate to more frequent engagement in interpersonal climate change discussions, and yet such discussion would relate to more anxiety responses. Our findings thus indicate the need to examine under what circumstances interpersonal climate change discussion would be an adaptive rather than a maladaptive strategy.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 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) | 0.000 | 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".