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Record W2143579414 · doi:10.1111/1467-9442.00181

Is it Harmful to Allow Partial Cooperation?

2000· article· en· W2143579414 on OpenAlexaff
Paul Beaudry, Pierre Cahuc, Hubert Kempf

Bibliographic record

VenueScandinavian Journal of Economics · 2000
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicEconomic theories and models
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsEconomicsPoliticsPublic goodMicroeconomicsWelfarePartial equilibriumWagePublic economicsNeoclassical economicsMarket economyPolitical scienceGeneral equilibrium theoryLaw

Abstract

fetched live from OpenAlex

In economics, politics and society, examples abound in economics, politics and society where agents can enter partial cooperation schemes, i.e., they can collude with a subset of agents. Several contributions devoted to specific settings have claimed that such partial cooperation actually worsens welfare compared to the no‐cooperation situation. Our paper assesses this view by highlighting the forces that lead to such results. We find that the nature of strategic spillovers is central to determining whether partial cooperation is bad. Our propositions are then applied to various examples as industry wage bargaining or local public goods. JEL classification: C 72; E 62; J 5

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.802
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0150.002

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 head0.049
GPT teacher head0.244
Teacher spread0.195 · 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; both teacher heads agree on what is shown here.

Study designNot applicable
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

Citations23
Published2000
Admission routes1
Has abstractyes

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