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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 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)0.004
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
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 score0.529
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0010.002
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 head0.114
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 teacher head, not a consensus.

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

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