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Record W1491775449 · doi:10.3138/jcfs.36.4.583

Post-Familial Families and the Domestic Division of Labour

2005· article· en· W1491775449 on OpenAlexvenueno aff
Janeen Baxter, Belinda Hewitt, Mark Western

Bibliographic record

VenueJournal of Comparative Family Studies · 2005
Typearticle
Languageen
FieldSocial Sciences
TopicGender, Labor, and Family Dynamics
Canadian institutionsnot available
Fundersnot available
KeywordsSocioeconomic statusDemographyCensusSocial classRacial groupArgument (complex analysis)Marital statusDemographic economicsSociologyRace (biology)PopulationEconomicsMedicineGender studies

Abstract

fetched live from OpenAlex

This paper examines independent living among elderly Brazilians age 65+ of different racial groups using 1980 and 2000 census microsamples. Although there was an overall increase in independent living among Brazilian elders, that increase mainly reflects change among Whites whereas there was little change among Browns or Blacks. Since Whites tend to have higher socioeconomic status than Browns or Blacks in Brazil, one might suppose that a racial disparity merely reflects socioeconomic differences. That is a common argument anyway. But if that were so, then after controlling for socioeconomic factors there should be 1) no racial difference in the likelihood of independent living, and 2) no racial difference hi the change in that likelihood. However, we find 1) net racial differences in independent living in both 1980 and 2000, and 2) a net racial difference in change among unmarried men. Our findings suggest that social, cultural or minority status factors not captured in our statistical models may explain these differences. Additional study is needed to confirm or negate this that will ideally include information about non-coresident as well as coresident kin.

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)0.003
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.027
Threshold uncertainty score0.054

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0040.000

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 head0.046
GPT teacher head0.368
Teacher spread0.322 · 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

Citations85
Published2005
Admission routes1
Has abstractyes

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