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Record W4417193144 · doi:10.1177/00380385251393091

Saying, Doing, Talking, Listening: A Mixed Methods Study of Fathers’ Involvement in Childcare and Household Work Tasks and Responsibilities

2025· article· en· W4417193144 on OpenAlexafffundabout
Kim de Laat, Andrea Doucet

Bibliographic record

VenueSociology · 2025
Typearticle
Languageen
FieldSocial Sciences
TopicWork-Family Balance Challenges
Canadian institutionsBrock UniversityUniversity of Waterloo
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsSituatedSet (abstract data type)Work (physics)Care workSurvey data collectionDomestic workPaid workSurvey researchChild care

Abstract

fetched live from OpenAlex

This article examines how methodological approaches shape understandings of domestic responsibilities. Using mixed methods data from Canadian dual-earner households, we compare fathers' individual survey responses with couple interview accounts about their childcare and housework involvement. Survey and interview data align when assessing tasks - discrete actions with defined boundaries - but diverge when evaluating responsibilities, which involve anticipating needs, managing care and organizing household life. These discrepancies also reflect how gendered and racialized expectations can influence how fathers conceptualize their contributions. We argue that couple interviews reveal relational dimensions of domestic responsibilities that survey data alone cannot capture. This study advances feminist and family sociology by theorizing household labour not only as a set of measurable actions but as socially situated and cognitively distributed practices. Methodological pluralism, we contend, is essential to understanding the meanings and organization of care in everyday life.

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)0.023
metaresearch head score (Gemma)0.020
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.023
Threshold uncertainty score0.122

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0230.020
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.002
Science and technology studies0.0080.004
Scholarly communication0.0030.003
Open science0.0010.003
Research integrity0.0010.001
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 head0.042
GPT teacher head0.370
Teacher spread0.328 · 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 designQualitative
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

Citations1
Published2025
Admission routes3
Has abstractyes

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