Affect-inducing risk communication: current knowledge and future directions
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
Affect appears to have a central role in peoples risk perception and decision-making. It is, therefore, important that researchers and communicators know how risk communication can induce affect or more specific emotions. In this paper, several studies that examined affect-inducing cues presented in and around risk communication are discussed. We thereby distinguish between integral affect induction, meaning through the risk message, and incidental affect induction, which occurs unintentional through the risk communication context. The following cues are discussed: emotion induction, fear appeals, outrage factors, risk stories, probability information, uncertainty information and graphs and images. Relatively few studies assessed the effect of their risk communication material on affect or specific emotions. Incidental affect induction appeared to occur more often than expected based on its factual content. Risk communication easily seems to induce affect incidentally and, thus, may be difficult to control. We, therefore, argue that incidental affect induction is more influential than integral affect induction. Implications for further research and risk communication in practice are given. Based on this overview, we strongly suggest considering and empirically assessing the affect-inducing potential of risk communication formats and content during their development and evaluation. © 2012 Copyright Taylor and Francis Group, LLC.
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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 | 0.008 | 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 | 0.001 |
| 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 it