The Effect of an Additional Alternative on Measured Risk Preferences in a Laboratory Experiment in Peru
Bibliographic record
Abstract
Une étude expérimentale a été menée dans le but de vérifier l'incidence qu'un choix supplémentaire peut avoir sur les préférences mesurées des fermiers des zones rurales du Pérou à l'égard du risque. Au cours de notre expérience, les sujets étaient appelés à exprimer leurs préférences face au risque en fonction d'une série de choix entre deux loteries. Nous avons ajouté une troisième loterie, laquelle était toujours dominée par une des deux loteries existantes. Nous avons pu constater que, le quart du temps, les sujets choisissaient cette nouvelle loterie, de sorte que, dans certains cas, les sujets semblaient être plus enclins au risque. Nous avons constaté, dans un environnement de laboratoire traditionnel, que les sujets ne choisissaient pas la loterie dominée, mais que leurs choix étaient influencés par sa présence.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".