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Record W2041762877 · doi:10.3366/hac.2002.14.1-2.129

Reconciling Cross-Sectional and Longitudinal Measures of Fertility, Quebec 1890–1900

2002· article· en· W2041762877 on OpenAlexaffabout
Patricia A. Thornton, Danielle Gauvreau

Bibliographic record

VenueHistory and Computing · 2002
Typearticle
Languageen
FieldArts and Humanities
TopicHistorical Studies on Reproduction, Gender, Health, and Societal Changes
Canadian institutionsConcordia University
Fundersnot available
KeywordsFertilityCensusImmigrationDemographyGeographyPopulationEthnic groupDemographic transitionDemographic economicsLongitudinal studyTotal fertility rateRural areaSociologyPolitical scienceEconomicsFamily planningMedicineResearch methodology

Abstract

fetched live from OpenAlex

In the absence of vital registration, studies of the onset and early phases of the fertility transition in North America have been seriously hampered and yet the seemingly early timing of the decline, the multi-ethnic nature of the population and continuous flow of immigrants from Europe suggest that North America has much to offer to this debate. This paper is primarily methodological drawing on parallel data for the city of Montreal and surrounding region. By reconciling cross-sectional census measures of fertility using the own-child methods (1901) with those derived from a longitudinal ten-year panel (1891-1901) using family reconstitution, it exposes some of the weaknesses and the potentials of the two methods most often currently used and the advantages of combining methods. Own-children measures of marital fertility are seriously affected by significant local differences in infant survival between rural and urban areas and between cultural groups as well as by residual effects of duration and timing of marriage, while small-scale longitudinal studies in complex environments cannot always render reliable results for all sub-populations not can they necessarily be 'scaled up.' They suggest that national and even regional averages of fertility may conceal large diversity, which in turn raises questions about the existence of any single transition with uniform characteristics and timing, or universal cause. Instead we argue different groups in different environments may actually have been fine-tuning their fertility behaviour to compensate for the differential effects of mortality through adjustments to both marriage and fertility within 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 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)0.000
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 score0.773
Threshold uncertainty score0.706

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
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 head0.231
GPT teacher head0.275
Teacher spread0.044 · 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

Citations2
Published2002
Admission routes2
Has abstractyes

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