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Record W3048038662 · doi:10.1177/0091415020943318

Linking Lives in Ethnically Diverse Families: The Interconnectedness of Home Leaving and Retirement Transitions

2020· article· en· W3048038662 on OpenAlexafffundabout
Barbara Mitchell, Andrew Wister, Grace Li, Zheng Wu

Bibliographic record

VenueThe International Journal of Aging and Human Development · 2020
Typearticle
Languageen
FieldSocial Sciences
TopicMigration, Aging, and Tourism Studies
Canadian institutionsUniversity of VictoriaSimon Fraser University
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsEthnic groupPersianEthnically diverseLife course approachDemographyGerontologyPsychologyMedicineSociologyDevelopmental psychology

Abstract

fetched live from OpenAlex

Drawing from a sociocultural life course perspective, this study examines the linkages between two age-related family transitions: young adult children leaving home and parental retirement. A sample of 580 ethnically diverse parents aged 50+ with at least one adult child aged 19-35 living in Metro Vancouver, British Columbia, Canada, was used in this study based on four cultural groups: British-, Chinese-, Persian/Iranian-, or South Asian-Canadian. Separate survival analyses are used to predict the timing of, and associations between children's leaving home and parents' retirement. Later timing of adult children's leaving home is associated with delays in retirement of parents and is influenced by a number of predictors. Main and interaction effects were supported for ethnicity, where belonging to the Persian/Iranian ethnic group (compared to British) delays home leaving, and belonging to Persian/Iranian and South Asian ethnic groups (compared to British) delays retirement timing.

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)0.001
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: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.770
Threshold uncertainty score0.262

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.046
GPT teacher head0.306
Teacher spread0.261 · 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 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

Citations7
Published2020
Admission routes3
Has abstractyes

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