“Act on Climate Change”: An Application of Protection Motivation Theory
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Our planet's climate is changing (U.S. Environmental Protection Agency, 2010), and current scientific evidence proves that global climate change is induced by humans (Intergovernmental Panel on Climate Change, 2007). Many scientists agree that climate change is one of the greatest threats faced by our planet. The climate change literature demonstrates that fear appeals can be used to encourage behavioral changes that will mitigate climate change (Nisbet, 2009; Patchen, 2006; Pike, Doppelt, & Herr, 2010). This article proposes Protection Motivation Theory (PMT; Rogers, 1983) as a suitable model to guide communication campaigns in the area of climate change. It also analyzes the extent to which a series of communication campaigns that are designed to persuade individuals to adopt behaviors that prevent climate change conform to PMT. Recommendations to improve the campaigns are presented.
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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 | 0.000 | 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) | 0.001 | 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 it