Beyond gains and losses: The effect of need on risky choice in framed decisions.
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
Substantial evidence suggests people are risk-averse when making decisions described in terms of gains and risk-prone when making decisions described in terms of losses, a phenomenon known as the framing effect. Little research, however, has examined whether framing effects are a product of normative risk-sensitive cognitive processes. In 5 experiments, it is demonstrated that framing effects in the Asian disease problem can be explained by risk-sensitivity theory, which predicts that decision makers adjust risk acceptance on the basis of minimal acceptable thresholds, or need. Both explicit and self-determined need requirements eliminated framing effects and affected risk acceptance consistent with risk-sensitivity theory. Furthermore, negative language choice in loss frames conferred the perception of high need and led to the construction of higher minimal acceptable thresholds. The results of this study suggest that risk-sensitivity theory provides a normative rationale for framing effects based on sensitivity to minimal acceptable thresholds, or needs.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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) | 0.000 | 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