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
Inequality has been associated with risk-taking at the societal level. However, this relationship has not been directly investigated at the individual level. Risk-sensitivity theory predicts that decision makers should increase risk-taking in situations of disparity between one's present state and desired state. Economic inequality creates such a disparity. In two experiments, we examined whether imposed economic inequality affects risk-taking. In Experiment 1, we examined whether victims of inequality engaged in greater risk-taking compared to beneficiaries of inequality and those not experiencing inequality. In Experiment 2, we examined whether ameliorating inequality for victims reduced risk-taking. In both experiments, victims of inequality engaged in greater risk-taking compared to beneficiaries of inequality and those not experiencing inequality. Among victims, amelioration of inequality contributed to decreased risk-taking. These findings provide further evidence in support of risk-sensitivity theory and suggest that reductions in economic inequality may lead to lower risk-taking.
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 | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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 | 0.001 |
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