MétaCan
Menu
Back to cohort
Record W2137858987

A Simple Test of Learning Theory

2006· article· en· W2137858987 on OpenAlexaff
Jim Engle‐Warnick, Ed Hopkins

Bibliographic record

VenueÉrudit documents and data repository (Érudit Consortium, University of Montreal) · 2006
Typearticle
Languageen
FieldSocial Sciences
TopicExperimental Behavioral Economics Studies
Canadian institutionsMcGill University
FundersNuffield Foundation
KeywordsMathematical economicsStochastic gameNash equilibriumSimple (philosophy)Best responseRepeated gameEquilibrium selectionTest (biology)Fictitious playMathematicsGame theoryEconomicsPhilosophy
DOInot available

Abstract

fetched live from OpenAlex

Nous faisons le compte rendu d'expériences élaborées afin de tester la possibilité théorique, découverte par Shapley (1964), que dans certains jeux, l'apprentissage ne converge pas vers un équilibre, que ce soit en termes de fréquences marginales ou de jeu moyen. Les sujets ont joué à répétition en paires fixes à un de deux jeux 3 ´ 3, chaque jeu ayant un équilibre de Nash unique avec stratégies mixtes. On prévoit que l'équilibre du premier jeu soit stable après apprentissage, et le deuxième jeu instable, à condition que les gains soient suffisamment élevés. Pour chaque jeu, nous avons eu recours à deux différents traitements : un avec gains faibles et l'autre avec gains élevés. Nous avons constaté que dans tous les traitements, le jeu moyen est près de l'équilibre bien qu'il y ait présence de cycles importants dans les données.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.797
Threshold uncertainty score0.978

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.014
GPT teacher head0.256
Teacher spread0.242 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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

Citations5
Published2006
Admission routes1
Has abstractyes

Explore more

Same venueÉrudit documents and data repository (Érudit Consortium, University of Montreal)Same topicExperimental Behavioral Economics StudiesFrench-language works237,207