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Record W3161640490 · doi:10.1177/0192513x211016041

Do Spousal Intimate Relationships Affect Fertility Intentions and Preferences?

2021· article· en· W3161640490 on OpenAlexafffund
Amir Erfani, Roya Jahanbakhsh

Bibliographic record

VenueJournal of Family Issues · 2021
Typearticle
Languageen
FieldSocial Sciences
TopicFamily Dynamics and Relationships
Canadian institutionsNipissing University
FundersSocial Sciences and Humanities Research Council of CanadaNipissing University
KeywordsEgalitarianismFertilityNormativeSocial psychologyPsychologyAffect (linguistics)Ideal (ethics)Developmental psychologyDemographySociologyPopulationPolitical science

Abstract

fetched live from OpenAlex

The fertility influence of spousal intimate relationships is unknown. Drawing on the Giddens’s theory of transformation of intimacy, this study proposed a hypothesis that couples supporting egalitarian intimate relationships, with a greater risk profile attached to the relationship, and having less attachments to the external normative pressures shaping marital relations, are more likely to have low-fertility intentions and preferences. Using data from a self-administered pilot survey ( n = 375 prospective grooms and brides) designed by the authors, and employing multivariate regression models, we found that the lower attachment to external social forces in mate selection was associated with the lower ideal number of children, and those with a greater spousal relational egalitarianism and a higher risk profile attached to their relationships preferred lower number of children and were less likely to intend to have children after marriage. The study sheds new light on the determinants of low fertility.

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)0.008
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 score0.004
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.008
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.099
GPT teacher head0.365
Teacher spread0.266 · 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

Citations6
Published2021
Admission routes2
Has abstractyes

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