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Record W2599543250 · doi:10.3138/jcfs.45.1.55

Cultivating the Difference: Social Class, Parental Values, Cultural Capital and Children’s After-School Activities in Taiwan

2014· article· en· W2599543250 on OpenAlexvenueno aff
Yi-Ping Shih, Chin-Chun Yi

Bibliographic record

VenueJournal of Comparative Family Studies · 2014
Typearticle
Languageen
FieldSocial Sciences
TopicYouth Development and Social Support
Canadian institutionsnot available
Fundersnot available
KeywordsSocializationThe artsSociologyContext (archaeology)Social capitalCultural capitalSocial reproductionSocial classCultural reproductionDevelopmental psychologyPsychologyGender studiesSocial scienceGeographyPolitical science

Abstract

fetched live from OpenAlex

Inspired by Melvin Kohn and Annette Lareau’s works, this paper aims to uncover the mechanisms of social reproduction practiced via after-school activities. The world’s lowest fertility rate, patriarchal family system, and burgeoning cram institutes make Taiwan a solid case to explore. Drawing on data from the Youth Project from 2000 and 2001 (N=2,126), we examine, step-by-step, the associations between parents’ social class, parents’ child-rearing values, and children’s after-school activity participation. By comparing maternal and paternal models, this paper demonstrates how Taiwanese parents carefully arranged the fabric of after-school time as an Asian version of concerted cultivation, and illustrates how cultural capital in Taiwan is practiced in the local context of parenting. Separate models on seven activities, including music, calligraphy, arts, dance, computer, sports and chess lessons, are investigated as well. By identifying the dynamic embedded within after-school activities, this paper contributes a fundamental understanding of after-school learning, a popular form of childhood socialization in East Asia.

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)0.002
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 score0.030
Threshold uncertainty score0.059

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
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)0.0010.000

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 head0.053
GPT teacher head0.355
Teacher spread0.302 · 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

Citations27
Published2014
Admission routes1
Has abstractyes

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