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Record W7015777367

TRANSNATIONAL PARENT KNOWLEDGE IN HERITAGE LANGUAGE EDUCATION: A NARRATIVE INQUIRY WITH THREE CHINESE IMMIGRANT MOTHERS

2024· dissertation· en· W7015777367 on OpenAlexaboutno aff

Bibliographic record

VenueUniversity Library (University of Saskatchewan) · 2024
Typedissertation
Languageen
FieldSocial Sciences
TopicMultilingual Education and Policy
Canadian institutionsnot available
Fundersnot available
KeywordsHeritage languageImmigrationNarrativeNarrative inquiryFirst languageLanguage revitalizationArtifact (error)Language acquisition
DOInot available

Abstract

fetched live from OpenAlex

In this dissertation, I explore the perspectives of transnational parents in bilingual education, particularly how they maintain connections to their home countries while adapting to the new country. Through my research, I investigate their strategies and practices for supporting heritage language development amidst transnational life complexities. The focus of my research is on how these parents navigate language decisions, bridge cultural divides, and weave multiple languages into their family dynamics, all while embracing their transnational identities.\nUsing narrative inquiry, I emphasize the interplay of personal, social, and material environments in shaping human experiences. This research approach goes beyond merely representing experiences; it involves engaging with them to forge new connections between individuals and their surroundings. I collaborated with three Chinese immigrant mothers in Saskatoon, Canada. Our interactions, including recorded conversations, shared observations, and family artifact analysis, revealed their ways of supporting their children's language learning. The collected field text of diverse moments and conversations across both English and Chinese languages, reflects the authentic language practices of these families.\nIn this dissertation, I present a compassionate inquiry into these mothers' journeys in heritage language education for their bi/multilingual children. Central to this exploration is "transnational parent knowledge," encompassing the mothers' deep insights and experiences. Through this research, I intertwine my personal narrative as an immigrant parent with the challenges of preserving Chinese heritage language in an English-dominated context, providing an empathetic lens to understand similar experiences of other immigrant mothers. Using this collective portrait, I illuminate the daily language practices of these families, showcasing how the mothers, living in transnational and translingual realities, nurture their children's bilingualism. I showcase their stories to highlight the dynamic facets of language teaching and learning within transnational families. The narratives, developed collaboratively, spotlight the mothers' strategies in maintaining heritage language, their resilience against raciolinguistic challenges, and their efforts against linguistic discrimination, emphasizing their pivotal role in fostering their children's bilingual identities and cultural connections.\nI extend the narrative to emphasize the significance of transnational parent knowledge in heritage language education. Challenging deficit narratives, I use this dissertation to advocate for an inclusive, strength-based approach to education that recognizes and celebrates the linguistic and cultural diversity of immigrant families. By foregrounding transnational parents' voices and experiences, I call for a reimagined heritage language education that fully integrates immigrant families' insights, enriching the educational experiences of bi/multilingual children.

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)0.005
metaresearch head score (Gemma)0.005
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 score0.026
Threshold uncertainty score0.052

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.005
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0230.008
Scholarly communication0.0050.005
Open science0.0020.007
Research integrity0.0020.004
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 head0.015
GPT teacher head0.303
Teacher spread0.288 · 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

Citations2
Published2024
Admission routes1
Has abstractyes

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