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 We conducted a series of field experiments to investigate the ability of experimentally measured risk preferences to predict the contractual choices of workers in the real labour market. In a first set of experiments we twice measured workers’ risk preferences using the lottery approach of Holt and Laury (Am Econ Rev 92(5):1644–165, 2002). These workers subsequently participated in a contract-choice experiment, making 12 decisions. For each decision, the worker chose between his/her regular piece-rate contract and a particular fixed wage contract, each distinguished by the level of the fixed wage. One of the twelve decisions was then chosen at random and the worker was paid according to his/her choice for that decision over a period of two working days. We estimate the effect of risk preferences on contractual choices, controlling for measurement error and worker ability. Risk preferences effectively predict contract choices—risk-averse workers are more likely to select fixed-wage contracts. High-ability workers prefer piece-rates.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 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) | 0.001 | 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