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Record W2098741629 · doi:10.1177/0192513x07302103

Nonresident Fathers and Children

2007· article· en· W2098741629 on OpenAlexaff
Heather Juby, Jean‐Michel Billette, Benoı̂t Laplante, Céline Le Bourdais

Bibliographic record

VenueJournal of Family Issues · 2007
Typearticle
Languageen
FieldSocial Sciences
TopicFamily Dynamics and Relationships
Canadian institutionsMcGill UniversityInstitut National de la Recherche Scientifique
Fundersnot available
KeywordsAffect (linguistics)Developmental psychologyPsychologyFragile Families and Child Wellbeing StudySeparation (statistics)DemographySociology

Abstract

fetched live from OpenAlex

Children often lose contact with their biological fathers after their parents separate and form new families. Using detailed longitudinal data on family transitions made by mothers and fathers after separation, the authors examine whether and how changes in the family trajectories of both biological parents affect frequency of contact that nonresident fathers maintain with their children. Approximately half of fathers experienced a change in contact frequency. The analysis shows that fathers' new union formation reduces visits to nonresident children, but only when it closely follows separation, before fathers and children have established the structure of their postseparation relationship. Unlike other studies, however, the authors do not find that the birth of a child in the father's new union significantly reduces his level of contact with nonresident children. Findings suggest that nonresident fathers reduce frequency of visits when their children acquire a stepfather.

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)0.004
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 score0.010
Threshold uncertainty score0.035

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0100.000

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 head0.032
GPT teacher head0.347
Teacher spread0.316 · 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

Citations99
Published2007
Admission routes1
Has abstractyes

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