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Record W4396902585 · doi:10.1016/j.ehb.2024.101383

How did the European Marriage Pattern persist? Social versus familial inheritance: England and Quebec, 1650–1850

2024· article· en· W4396902585 on OpenAlexaboutno aff
Gregory Clark, Neil Cummins, Matthew Curtis

Bibliographic record

VenueEconomics & Human Biology · 2024
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicHistorical Economic and Social Studies
Canadian institutionsnot available
FundersUniversity of California, DavisNational Research FoundationNational Institutes of HealthDanmarks GrundforskningsfondNational Science Foundation
KeywordsInheritance (genetic algorithm)GenealogyDemographyHistoryGeographySociologyGeneticsBiology

Abstract

fetched live from OpenAlex

The European Marriage Pattern (EMP), in place in NW Europe for perhaps 500 years, substantially limited fertility. But how could such limitation persist when some individuals who deviated from the EMP norm had more children? If their children inherited their deviant behaviors, their descendants would quickly become the majority of later generations. This puzzle has two possible solutions. The first is that all those that deviated actually had lower net fertility over multiple generations. We show, however, no fertility penalty to future generations from higher initial fertility. Instead the EMP survived because even though the EMP persisted at the social level, children did not inherit their parents’ individual fertility choices. In the paper we show evidence consistent with lateral, as opposed to vertical, transmission of EMP fertility behaviors. • The European Marriage Pattern (EMP), in place in NW Europe for perhaps 500 years, substantially limited fertility. • We show no fertility penalty to future generations from higher initial fertility in the first generation. • The EMP survived because children did not inherit their parents’ individual fertility choices. • We show evidence consistent with lateral, as opposed to vertical, transmission of fertility behaviors.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.943
Threshold uncertainty score0.977

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.042
GPT teacher head0.225
Teacher spread0.183 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
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
Published2024
Admission routes1
Has abstractyes

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