The moderating role of processing style in risk perceptions and risky decision making
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 When evaluating risks, such as skydiving or taking an experimental drug, there are both possible harms and benefits to consider. In the current research, we hypothesize that individuals evaluating risks visually possibly see greater potential harms—but not more potential benefits—compared with those doing so verbally. This is likely because visualizing risks is inherently an affective experience, and negative affect (e.g., potential harms in risk taking) is more dominant than positive affect (e.g., potential benefits). This means that perceived harms are greater for visualizers, reducing their willingness to take risks. We obtain support for this theorizing across four studies, with visualizing individuals more likely to see harms from taking risks, leading to their risk aversion. This research thus demonstrates that visualizing risks asymmetrically shapes how individuals evaluate the two main components of risk taking (perceived harms, perceived benefits). We discuss the application of our findings to how individuals perceive risks in both the marketplace and policy settings.
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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 | 0.006 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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