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Record W4411927085 · doi:10.3390/educsci15070816

The Emotional Work of Heritage Language Maintenance: Insights from a Longitudinal Study of Chinese–Canadian Bilingual Parenting

2025· article· en· W4411927085 on OpenAlexafffundabout
Guofang Li, Zhen Lin

Bibliographic record

VenueEducation Sciences · 2025
Typearticle
Languageen
FieldArts and Humanities
TopicEFL/ESL Teaching and Learning
Canadian institutionsUniversity of British Columbia
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsHeritage languagePsychologyNeuroscience of multilingualismWork (physics)Longitudinal studyDevelopmental psychologyLinguisticsMathematics educationPedagogyEngineeringMedicine

Abstract

fetched live from OpenAlex

Drawing on data from a three-year longitudinal study of 56 Chinese–Canadian families with early elementary school-aged children, this study explores Chinese immigrant parents’ lived-through emotional experiences of heritage language maintenance (HLM). Informed by Vygotsky’s concept of perezhivanie, thematic analysis of annual interview data reveals the mixed and refracted nature of parental emotions involved in Chinese language preservation and bilingual child-rearing. These emotional experiences were profoundly shaped by the intersection of environmental, personal, and situational factors and were deeply entangled with parents’ perceptions of and attitudes toward their children’s heritage language learning and use at home. The emotional work involved significantly influenced the parents’ language and literacy planning and HLM practices. By foregrounding the emotional dimensions of heritage language education, this study offers important implications for educational stakeholders seeking to support immigrant parents both emotionally and practically in raising bilingual children in the host country.

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)0.000
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.172
Threshold uncertainty score0.962

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
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 head0.036
GPT teacher head0.326
Teacher spread0.290 · 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

Citations5
Published2025
Admission routes3
Has abstractyes

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