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Record W2601038279 · doi:10.1086/711491

The Cobb-Douglas Marriage Matching Function: Marriage Matching with Peer and Scale Effects

2020· preprint· en· W2601038279 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueJournal of Labor Economics · 2020
Typepreprint
Languageen
FieldSocial Sciences
TopicGender, Labor, and Family Dynamics
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsMatching (statistics)CobBPopulationScale (ratio)Function (biology)EconomicsEconometricsMicroeconomicsMathematical economicsSociologyMathematicsGeographyStatisticsDemographyBiologyEvolutionary biologyCartography

Abstract

fetched live from OpenAlex

Across states, there is little correlation between a state’s marriage rate or cohabitation rate and own population. Within states, there is a positive (no) correlation between a state’s marriage (cohabitation) rate and its population growth rate. The Cobb-Douglas marriage matching function (CDMMF), which extends the Choo-Siow MMF to include peer effects, can rationalize these correlations. The model is easy to estimate. The CDMMF is estimated using panel data across US states from 1990 to 2010. The estimated model replicates the above scale effects. These effects are not sufficient to explain the large recent declines in the gains to 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.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Scholarly communication
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.269
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0010.000
Research integrity0.0000.001
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 head0.012
GPT teacher head0.245
Teacher spread0.233 · 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