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Record W2613213661 · doi:10.3138/jcfs.33.3.401

The Changing Role of the Husband/Father in the Dual-Earner Family in South Africa

2002· article· en· W2613213661 on OpenAlexvenueno aff
Ria Smit

Bibliographic record

VenueJournal of Comparative Family Studies · 2002
Typearticle
Languageen
FieldSocial Sciences
TopicWork-Family Balance Challenges
Canadian institutionsnot available
Fundersnot available
KeywordsPerceptionFamily lifeGender studiesDeveloping countrySpillover effectDeveloped countrySociology of the familySociologyDemographic economicsPolitical sciencePsychologyEconomic growthPopulationDemographyEconomics

Abstract

fetched live from OpenAlex

In recent research studies that have been done within the cadre of Family Sociology, researchers have emphasised the fact that the role of the man in the family has become an important topic, as is evident in extensive public debate and scholarly inquiry. For several decades the focus in South Africa, as in the case of other countries, fell on the increasing interface between work and family life, within the work/family spillover model, as experienced by the working married woman and how her marital and familial relationships are influenced by it. While it is clear from these research results, especially from those studies conducted in South Africa, that most men are no longer the sole or primary breadwinner in the family, it is less clear which new patterns of commitment and involvement these men are developing with regard to their family life. In this article the focus falls on some of the findings from a resent extensive quantitative study that aimed to shed light on the man’s perception of his roles as husband and father in the dual-earner family and to ascertain to what extend this perception may or may not stand in relationship to his experience of marital integration.

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)0.003
metaresearch head score (Gemma)0.005
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.023
Threshold uncertainty score0.046

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0080.005
Scholarly communication0.0030.002
Open science0.0010.004
Research integrity0.0000.001
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 head0.121
GPT teacher head0.342
Teacher spread0.221 · 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

Citations40
Published2002
Admission routes1
Has abstractyes

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