Priming memories of past wins induces risk seeking.
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Bibliographic record
Abstract
People are often risk averse when making decisions under uncertainty. When those decisions are based on past experience, people necessarily rely on their memories. Thus, what is remembered at the time of the choice should influence risky choice. We tested this hypothesis by priming memory for past outcomes in a simple risky-choice task. In the task, people repeatedly chose between a safe option and a risky option that paid off with a larger or smaller reward with a 50/50 chance. Some trials were preceded by a priming cue that was previously paired with one of the outcomes. We found that priming cues associated with wins caused people to become risk seeking, whereas priming cues associated with relative losses had little effect. These results suggest that people can be induced to be more risk seeking through subtle reminders of previous winning experiences.
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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 | 0.003 | 0.001 |
| 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 | 0.001 | 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