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Record W2562717297 · doi:10.3138/jcfs.42.4.579

The Intersection of Motherhood and Disability: Being a “Good” Korean Mother to an “Imperfect” Child

2011· article· en· W2562717297 on OpenAlexvenueno aff
Hyun‐Kyung You, Lori A. McGraw

Bibliographic record

VenueJournal of Comparative Family Studies · 2011
Typearticle
Languageen
FieldPsychology
TopicFamily and Disability Support Research
Canadian institutionsnot available
Fundersnot available
KeywordsSituatedMainstreamGender studiesDevelopmental psychologyPsychologySocial constructionismMeaning (existential)Sociocultural evolutionMiddle classSociologySocial psychologyPolitical science

Abstract

fetched live from OpenAlex

This study springs from a larger cross-cultural project about mothering a child with a disability in South Korea and in the United States. The present analysis focuses on data collected in South Korea. Integrating critical feminist and disability theories within a social constructionist framework (McGraw & Walker, 2007), we asked (a) how dominant sociocultural systems related to mothering and disability shape South Korean mothers’ understanding of themselves and their children with autism and (b) how mothers conform to and resist these systems. To answer these questions, we conducted in-depth interviews with 14 middle-class, South Korean mothers with children who have autism. We found that mothers resist stigmatizing beliefs about their children by reconstructing the meaning of “normal” childhood and by relying on a network of similarly situated mothers for support. We also found that these mothers conform to traditional beliefs about “good” mothering by adhering to Confucian family values that encourage women to sacrifice themselves to focus on their children’s success. From these findings, we offer implications for practice.

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)0.002
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: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.010
Threshold uncertainty score0.020

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0060.008
Scholarly communication0.0030.003
Open science0.0000.005
Research integrity0.0010.001
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 head0.154
GPT teacher head0.417
Teacher spread0.263 · 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

Citations50
Published2011
Admission routes1
Has abstractyes

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