Risk Propensity Among Liberals and Conservatives
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
Political conservatives, compared to liberals, are commonly thought to be more threat-sensitive and risk-averse. Using an American sample of community adults ( n = 397), we investigated when conservatives and liberals might be risk-taking or risk-averse. Participants completed measures of political orientation, and perceptions of risk, expected benefits (EB) of risk, and risk-propensity, across five domains (financial, recreational, ethical, social, and health). The relation between perceptions of risk and EB and risk-propensity differed as a function of political conservatism and varied across risk domains. For example, with regard to new business ventures, conservatives were generally willing to take risks unless perceived risk was high and expected benefit was low, whereas liberals were generally unwilling to take risks unless perceived risk was low and expected benefit was high. Implications for understanding risk-taking are considered.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.003 | 0.013 |
| 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