Mortality management and climate action: A review and reference for using Terror Management Theory methods in interdisciplinary environmental research
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
Abstract Global climate change awareness is increasing, but efforts to convey information can trigger undesirable behaviors , including denial, skepticism, and increased resource consumption. It is therefore essential to more fully investigate social–psychological responses to climate information and messaging if we are to prompt, support, and sustain pro‐environmental behaviors. Yet consideration of these responses is typically absent from interdisciplinary environmental study designs. Of specific relevance is research using social psychology's Terror Management Theory (TMT) showing that people's efforts to repress mortality salience (MS) or awareness significantly influence their attitudes, beliefs, and behaviors. Research on MS's influence on climate change beliefs is progressing but, to date, a systematic scoping review of the literature has been unavailable. Here, we provide such a review. We propose that TMT insights and methods should be better integrated into research designs to guide climate communications and to generate the comprehensive cultural and behavioral changes needed to address societies' climate problems. We introduce a methodological framework for interdisciplinary researchers to incorporate TMT into their research designs and to help practitioners anticipate how their mortality‐laden messaging could trigger unintentional social‐psychological responses that degrade climate communication strategies. This article is categorized under: Perceptions, Behavior, and Communication of Climate Change > Behavior Change and Responses
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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 | 0.014 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.019 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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