Bibliographic record
Abstract
Abstract This research develops and tests a model of individual intentions to actively seek information about climate change. Our premise is that the individual's intention to actively seek information about climate change would determine their knowledge of and attitudes towards climate change, and this would in turn influence how they act or change their behaviors in response to that risk. Our model identifies key cognitive, affective, and situational variables drawn from research in human information behavior and risk communication. We conducted an online survey in which 212 participants in Canada and the United States responded. The results showed that the model was able to explain more than 40% of the variance in intention to seek climate change information. Social Norms, Affective Response, and Social Trust were the most important variables in influencing intention to seek climate change information. We conclude that climate change information seeking has a strong social dimension where social norms and expectations of relevant and respected others exert a major influence, and that the individual's emotional response towards the risk of climate change is more important than the individual's cognitive perception of how much information they need on climate change.
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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 | 0.006 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.006 |
| 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".