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Record W7106119500 · doi:10.17605/osf.io/y6vub

Parents’ Views on Child Socialization Goals: A Cross-Cultural Comparison

2025· other· W7106119500 on OpenAlexaboutno aff

Bibliographic record

VenueOSF Preprints (OSF Preprints) · 2025
Typeother
Language
Field
Topic
Canadian institutionsnot available
Fundersnot available
KeywordsSocializationCollectivismIndividualismObedienceIndependence (probability theory)Cultural diversityEast AsiaValue (mathematics)

Abstract

fetched live from OpenAlex

Children’s development is shaped by the qualities that parents consider important for them to have, often described as child socialization goals. These goals reflect broader cultural norms, and past research has shown that parents across cultures differ in the qualities they view as important (Bornstein, 2013; Rosenthal & Roer-Strier, 2001). Earlier cross-cultural work highlighted a broad contrast between “Eastern” and “Western” parents, suggesting that East Asian parents value obedience and interdependence in line with collectivist traditions, whereas Western parents prioritize independence and self-expression consistent with individualist norms.(Markus & Kitayama, 1991; Chao, 1994; Triandis, 1995). More recent findings suggest that these differences may not be as clear-cut as previously assumed. Using Wave 5 of the World Values Survey (1989–2010), Park et al. (2014) found that parents from East Asian societies (e.g. China, Japan, South Korea) increasingly endorsed independence as an important child socialization goal. This raises the question of whether these patterns have continued in the past decade. The current project examines this question using Wave 7 of the World Values Survey (2017–2022). Consistent with Park et al. (2014), the current study focuses on parents from three East Asian societies (China, Japan, South Korea) and three Western societies (Australia, Canada, United States) and examines how likely parents are to select each of the 11 WVS child socialization goals (e.g., independence, obedience, imagination, thrift) as “especially important.” I expect to find cultural differences consistent with older findings, along with indications that some of these differences have narrowed in more recent years.

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)0.002
metaresearch head score (Gemma)0.006
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.010
Threshold uncertainty score0.020

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.006
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 science0.0000.002
Research integrity0.0000.001
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 head0.036
GPT teacher head0.352
Teacher spread0.317 · 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 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

Citations0
Published2025
Admission routes1
Has abstractyes

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