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Record W2520082720 · doi:10.1111/jomf.12346

Marriage‐Market Constraints and Mate‐Selection Behavior: Racial, Ethnic, and Gender Differences in Intermarriage

2016· article· en· W2520082720 on OpenAlexaff
Kate H. Choi, Marta Tienda

Bibliographic record

VenueJournal of Marriage and the Family · 2016
Typearticle
Languageen
FieldSocial Sciences
TopicFamily Dynamics and Relationships
Canadian institutionsWestern University
FundersEunice Kennedy Shriver National Institute of Child Health and Human Development
KeywordsMarriage marketEthnic groupMate choiceScarcityDemographic economicsSalientDemographyEconomicsSociologyPolitical scienceMating

Abstract

fetched live from OpenAlex

Despite theoretical consensus that marriage markets constrain mate selection behavior, few studies directly evaluate how local marriage market conditions influence intermarriage patterns. Using data from the American Community Survey, we examine what aspects of marriage markets influence mate selection; assess whether the associations between marriage market conditions and intermarriage are uniform by gender and across pan-ethnic groups; and investigate the extent to which marriage market conditions account for group differences in intermarriage patterns. Relative group size is the most salient and consistent determinant of intermarriage patterns across pan-ethnic groups and by gender. Marriage market constraints typically explain a larger share of pan-ethnic differences in intermarriage rates than individual traits, suggesting that scarcity of co-ethnic partners is a key reason behind decisions to intermarry. When faced with market constraints, men are more willing or more successful than women in crossing racial and ethnic boundaries in marriage.

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)0.001
metaresearch head score (Gemma)0.005
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 score0.005
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0040.000

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 head0.049
GPT teacher head0.303
Teacher spread0.254 · 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

Citations98
Published2016
Admission routes1
Has abstractyes

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