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Record W1993019819 · doi:10.1080/00324728.2014.889741

The impact of socio-economic status on net fertility during the historical fertility decline: A comparative analysis of Canada, Iceland, Sweden, Norway, and the USA

2014· article· en· W1993019819 on OpenAlexaboutno aff
Martin Dribe, J. David Hacker, Francesco Scalone

Bibliographic record

VenuePopulation Studies · 2014
Typearticle
Languageen
FieldSocial Sciences
TopicFamily Dynamics and Relationships
Canadian institutionsnot available
FundersEunice Kennedy Shriver National Institute of Child Health and Human Development
KeywordsFertilityResidenceGeographyContext (archaeology)Demographic transitionDemographyTotal fertility rateSocioeconomic statusSocioeconomicsPopulationDemographic economicsEconomicsFamily planningSociologyResearch methodology

Abstract

fetched live from OpenAlex

We used micro-level data from the censuses of 1900 to investigate the impact of socio-economic status on net fertility during the fertility transition in five Northern American and European countries (Canada, Iceland, Norway, Sweden, and the USA). The study is therefore unlike most previous research on the historical fertility transition, which used aggregate data to examine economic correlates of demographic behaviour at regional or national levels. Our data included information on number of children by age, occupation of the mother and father, place of residence, and household context. The results show highly similar patterns across countries, with the elite and upper middle classes having considerably lower net fertility early in the transition. These patterns remain after controlling for a range of individual and community-level fertility determinants and geographical unobserved heterogeneity.

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)0.002
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 score0.032
Threshold uncertainty score0.075

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.004
Science and technology studies0.0020.001
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.059
GPT teacher head0.363
Teacher spread0.304 · 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

Citations82
Published2014
Admission routes1
Has abstractyes

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