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Record W2148475543 · doi:10.15057/25384

SELLER-BUYER ETHNIC MATCHES: THE CASE OF CAR TRANSACTIONS AT TWO NORTH AMERICAN AUTO DEALERSHIPS

2012· article· en· W2148475543 on OpenAlexaboutno aff
Hideo Owan, Tsuyoshi Tsuru, Katsuhito Uehara

Bibliographic record

VenueInstitutional Repositories DataBase (IRDB) · 2012
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicCorporate Finance and Governance
Canadian institutionsnot available
Fundersnot available
KeywordsEthnic groupDemographicsDatabase transactionBusinessMarketingTransaction dataDemographyDatabaseComputer sciencePolitical science

Abstract

fetched live from OpenAlex

Using personnel and transaction data obtained from two Canadian auto dealerships, we examine whether ethnic matches between salespersons and customers affectsales prices and the number of units sold by individual salespersons. Regarding prices, we detect neither premium price setting nor discounting among seller-buyer matches of the same ethnic groups relative to those of different ethnic groups. Regarding the number of units sold by individual salespersons, however, we find that, relative to customer demographics, salespersons sell larger quantities to customers of the same ethnic group. Moreover, we find that high-performing salespersons conduct more transactions with customers of the same ethnic group than low-performers, especially in months when business conditions are unfavorable.

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)0.002
metaresearch head score (Gemma)0.008
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.826
Threshold uncertainty score0.351

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.008
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.004
Science and technology studies0.0040.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.041
GPT teacher head0.260
Teacher spread0.219 · 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 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

Citations1
Published2012
Admission routes1
Has abstractyes

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