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Record W2045901871 · doi:10.3200/socp.144.1.5-29

The Chinese in Canada: A Study in Ethnic Change With Emphasis on Gender Roles

2004· article· en· W2045901871 on OpenAlexaffabout
Chankon Kim, Michel Laroche, Marc A. Tomiuk

Bibliographic record

VenueThe Journal of Social Psychology · 2004
Typearticle
Languageen
FieldSocial Sciences
TopicGender Roles and Identity Studies
Canadian institutionsHEC MontréalConcordia UniversitySaint Mary's University
Fundersnot available
KeywordsAcculturationEthnic groupPsychologySocial psychologyGender roleIdentification (biology)Task (project management)Developmental psychologySociology

Abstract

fetched live from OpenAlex

The authors investigated the impact of ethnic change experienced by Chinese Canadian couples on gender-role attitude, household task-role expectations and performance. The authors presented acculturation and Chinese ethnic identification as the two discriminant facets of ethnic change. Results indicated a nonsignificant role of acculturation in bringing about modifications of the gender-role attitudes of husbands and of their household task-role expectations. In contrast, the acculturation of Chinese Canadian wives proved to be a significant factor in promoting more modern (less traditional) gender-role attitudes, which in turn led to role expectations that they should contribute less to the performance of the tasks that traditionally fall in the female domain whereas their husbands should contribute more. Subsequent results also revealed that the acculturation of wives was directly linked to the role expectation that they should assume a greater share of responsibility in taking care of the traditionally husband-responsible tasks whereas their husbands should contribute a smaller share. Moreover, Chinese ethnic identification emerged as a significant determinant of husbands' gender-role attitudes and influenced their role expectation that husbands should contribute more to the performance of the tasks that traditionally fall in the male domain whereas their wives should contribute less.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.423
Threshold uncertainty score0.383

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.100
GPT teacher head0.405
Teacher spread0.305 · 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 teacher head, 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
Published2004
Admission routes2
Has abstractyes

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