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Record W2095040162 · doi:10.1111/1467-937x.00133

The Scope of Anonymous Voluntary Bargaining Under Asymmetric Information

2000· article· en· W2095040162 on OpenAlexfundno aff
Ehud Lehrer, Zvika Neeman

Bibliographic record

VenueThe Review of Economic Studies · 2000
Typearticle
Languageen
FieldDecision Sciences
TopicAuction Theory and Applications
Canadian institutionsnot available
FundersMcGill University
KeywordsScope (computer science)Information asymmetryLibrary scienceEconomicsPolitical scienceComputer scienceFinance

Abstract

fetched live from OpenAlex

We present a model of anonymous collective bargaining where individuals' preferences and information may be significantly interdependent. We show that the bargaining outcome becomes independent of individuals' preferences and information as the bargaining group increases in size. As a corollary, we show that anonymous voluntary bargaining completely fails in large groups. Either the difference between the bargaining outcome and the status quo vanishes as the size of the group becomes larger, or, the bargaining becomes coercive and results in a violation of at least some individuals' rights. The result provides a rationale for the inherent difficulty of reform in the presence of asymmetric information. “There is nothing more difficult to carry out, nor more doubtful of success, nor more dangerous to handle, than to initiate a new order of things.” Niccolò Machiavelli, The Prince (1532)

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)0.007
metaresearch head score (Gemma)0.014
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.007
Threshold uncertainty score0.036

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.014
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0020.009
Scholarly communication0.0050.008
Open science0.0020.004
Research integrity0.0030.003
Insufficient payload (model declined to judge)0.0040.001

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 head0.099
GPT teacher head0.401
Teacher spread0.302 · 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 designTheoretical or conceptual
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
Published2000
Admission routes1
Has abstractyes

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