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Record W2160791614

The Effect of an Additional Alternative on Measured Risk Preferences in a Laboratory Experiment in Peru

2006· preprint· en· W2160791614 on OpenAlexafffundabout
Jim Engle‐Warnick, Javier Escobal, Sonia Laszlo

Bibliographic record

VenueeScholarship@McGill (McGill) · 2006
Typepreprint
Languageen
FieldDecision Sciences
TopicDecision-Making and Behavioral Economics
Canadian institutionsMcGill University
FundersMcGill UniversityJohns Hopkins UniversityBrown University
KeywordsQuarter (Canadian coin)Test (biology)ChosePsychologyEconometricsEconomicsDemographyGeographySociologyPolitical scienceBiology
DOInot available

Abstract

fetched live from OpenAlex

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.

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.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.008
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.015

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.008
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0040.000

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.

Opus teacher head0.063
GPT teacher head0.343
Teacher spread0.280 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations3
Published2006
Admission routes3
Has abstractyes

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