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Record W1524367418

Multi-Agent Bilateral Bargaining with Endogenous Protocol

2004· preprint· en· W1524367418 on OpenAlexaff
Sang-Chul Suh, Quan Wen

Bibliographic record

VenueRePEc: Research Papers in Economics · 2004
Typepreprint
Languageen
FieldEconomics, Econometrics and Finance
TopicGame Theory and Voting Systems
Canadian institutionsUniversity of Windsor
Fundersnot available
KeywordsCensusRentingHousing discriminationCensus tractRace (biology)Demographic economicsEconomicsState (computer science)Labour economicsValue (mathematics)Work (physics)Property valueBusinessPublic economicsLawPolitical scienceEconomic growthSociologyFinancePopulationDemography
DOInot available

Abstract

fetched live from OpenAlex

This paper measures the housing market impact of state-level anti-discrimination laws in the 1960s using household-level and census-tract data. State-level "fair-housing" laws attempted to bar discrimination on the basis of race, religion, and national origin in the sale, rental, and financing of housing, and they were the direct antecedents of the federal Fair Housing Act of 1968. Their influence on the housing market outcomes of African Americans has not been assessed in previous work by economists, but policy variation across states during the 1960s provides an opportunity to pursue such estimates. During the 1960s, blacks' housing market outcomes improved relative to whites', and the proportion of exclusively white census tracts declined markedly. But I find little evidence that the fair-housing laws contributed to those changes. Rather, the bulk of the evidence indicates that the laws' effects on blacks' housing market outcomes, on residential segregation, and on the value of property in predominantly nonwhite neighborhoods were negligible.

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)0.008
metaresearch head score (Gemma)0.020
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.034
Threshold uncertainty score0.115

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0080.020
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0010.002
Science and technology studies0.0010.002
Scholarly communication0.0030.004
Open science0.0040.004
Research integrity0.0040.003
Insufficient payload (model declined to judge)0.0340.004

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 head0.114
GPT teacher head0.317
Teacher spread0.203 · 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 designSimulation or modeling
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
Published2004
Admission routes1
Has abstractyes

Explore more

Same venueRePEc: Research Papers in EconomicsSame topicGame Theory and Voting SystemsFrench-language works237,207