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Record W1980819929 · doi:10.1515/bejeap-2012-0040

A Cross-Cultural Real-Effort Experiment on Wage-Inequality Information and Performance

2013· article· en· W1980819929 on OpenAlexaff
Hong Liu-Kiel, Charles Bram Cadsby, Heike Y. Schenk-Mathes, Fei Song, Xiaolan Yang

Bibliographic record

VenueThe B E Journal of Economic Analysis & Policy · 2013
Typearticle
Languageen
FieldSocial Sciences
TopicExperimental Behavioral Economics Studies
Canadian institutionsToronto Metropolitan UniversityUniversity of Guelph
Fundersnot available
KeywordsPiece workAffect (linguistics)WageContrast (vision)Wage inequalityEconomicsChinaWork (physics)Demographic economicsLabour economicsPsychologyMicroeconomicsComputer sciencePolitical scienceEngineering

Abstract

fetched live from OpenAlex

Abstract We conduct a real-effort laboratory experiment to examine how disclosure of information about the pay received by co-workers affects work performance in Germany and China. We employ an individual piece-rate setting in which a piece rate is received for each unit of output successfully produced. We find that receiving information that one’s co-workers are all receiving the same piece rate as oneself has no significant effect on performance compared to non-disclosure. In contrast, learning that one co-worker is receiving a higher piece rate than oneself does significantly affect performance. In particular, receiving such information initially results in a larger performance increase than receiving information that others are all receiving the same piece rate as oneself. However, this performance gap decreases toward the end of the experiment.

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)0.001
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.163
Threshold uncertainty score0.970

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.002
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 head0.036
GPT teacher head0.388
Teacher spread0.352 · 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

Citations2
Published2013
Admission routes1
Has abstractyes

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