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Record W2001656295 · doi:10.1177/0038038508091621

`It's Just Easier for Me to Do It': Rationalizing the Family Division of Foodwork

2008· article· en· W2001656295 on OpenAlexaffabout
Brenda L. Beagan, Gwen E. Chapman, Andrea D’Sylva, B. Raewyn Bassett

Bibliographic record

VenueSociology · 2008
Typearticle
Languageen
FieldSocial Sciences
TopicWork-Family Balance Challenges
Canadian institutionsUniversity of British ColumbiaDalhousie University
Fundersnot available
KeywordsInterviewSociologyGender studiesDivision of labourQualitative researchPerceptionSocial psychologyPsychologySocial sciencePolitical scienceLawAnthropology

Abstract

fetched live from OpenAlex

While women continue to do the lion's share of foodwork and other housework, they and their families appear to perceive this division of labour as fair. Much of the research in this area has focused on families of European origin, and on the perceptions of women. Here we report findings of a qualitative study based on interviewing multiple family members from three ethno-cultural groups in Canada. Women, men and children employed similar rationales for why women did most of the foodwork, though explanations differed somewhat by ethno-cultural group. Explicitly naming foodwork as women's work was uncommon, except in one ethno-cultural group.Yet more individualized, apparently gender-neutral rationales such as time availability, schedules, concern for family health, foodwork standards, and the desire to reduce family conflict were grounded in unspoken assumptions about gender roles. Such implicit gender assumptions may be more difficult to challenge.

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)0.008
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: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.168
Threshold uncertainty score0.335

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0080.008
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0130.041
Scholarly communication0.0080.005
Open science0.0010.004
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0020.000

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 head0.126
GPT teacher head0.380
Teacher spread0.254 · 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

Citations238
Published2008
Admission routes2
Has abstractyes

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