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Record W2278539648

Heritage Language Acquisition and Maintenance: Home Literacy Practices of Japanese-Speaking Families in Canada.

2013· article· en· W2278539648 on OpenAlexaboutno aff
Takako Nomura, Nadia Caidi

Bibliographic record

VenueInformation Research: An International Electronic Journal · 2013
Typearticle
Languageen
FieldSocial Sciences
TopicMultilingual Education and Policy
Canadian institutionsnot available
Fundersnot available
KeywordsHeritage languageMainstreamThematic analysisLiteracyImmigrationCultural heritageProcess (computing)PedagogyPsychologySociologyQualitative researchPolitical scienceSocial scienceComputer science
DOInot available

Abstract

fetched live from OpenAlex

Introduction. In this study, we examine the case of Japanese-speaking families in Canada and their experiences with teaching a heritage language at home, along with the uses and perceived usefulness of public library resources, collections, and services in the process. Methods. We interviewed fourteen mothers who speak Japanese to their children. We complemented the interviews with picture diaries produced by participants about their vision of the 'ideal' library. Analysis. Interviews were transcribed and a thematic analysis conducted through an iterative process. A visual analysis process was performed on the picture diaries. Results. There is a disconnect between the women’s needs and practices relating to heritage language education, and their ability to navigate the 'mainstream' information environment for relevant information. Conclusion. Findings point to the symbolic importance of engaging in heritage language literacy. Although the home remains the crucial site for heritage language literacy practices and the mother plays a critical role in this process, the literacy practices used by Japanese immigrant mothers in Toronto to teach and maintain heritage language are diverse and varied.

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)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.250
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.005
Open science0.0000.000
Research integrity0.0000.001
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 head0.050
GPT teacher head0.459
Teacher spread0.409 · 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.

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

Citations14
Published2013
Admission routes1
Has abstractyes

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