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Record W2052349578 · doi:10.3138/cmlr.58.3.341

Loss and Maintenance of First Language Skills: Case Studies of Hispanic Families in Vancouver

2002· article· en· W2052349578 on OpenAlexvenueaboutno aff
Martin Guardado

Bibliographic record

VenueCanadian Modern Language Review/ La Revue canadienne des langues vivantes · 2002
Typearticle
Languageen
FieldSocial Sciences
TopicMultilingual Education and Policy
Canadian institutionsnot available
Fundersnot available
KeywordsPerspective (graphical)Identity (music)Context (archaeology)PsychologyQualitative researchHeritage languageData collectionDevelopmental psychologySociologyPedagogyComputer scienceHistory

Abstract

fetched live from OpenAlex

This qualitative study aims to explore the loss and maintenance of Spanish in Hispanic children in Vancouver from the perspective of parents. It focuses on the experiences of Hispanic parents of children either developing bilingually (Spanish-English) or monolingually (English). The primary method of data collection is the semi-structured interview. Data collected in this study support the notion that first language (L1) cultural identity is crucial to heritage language maintenance in the context of a dominant second language (L2). However, the data contradict previous findings that a narrow linguistic community and the input of one parent are not sufficient for L1 maintenance. The bilingual (i.e., L1 maintenance) children in the present study had L1 input from only one parent and limited L1 contacts outside the home. The data also show that the type of encouragement parents give to their children to speak the L1 can have a facilitating or a detrimental effect. Therefore, this article urges parents committed to L1 maintenance to promote a positive attitude in their children and to address their affective needs accordingly.

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)0.005
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 score0.368
Threshold uncertainty score0.739

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.005
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.002
Science and technology studies0.0180.005
Scholarly communication0.0030.001
Open science0.0020.004
Research integrity0.0010.002
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 head0.032
GPT teacher head0.335
Teacher spread0.304 · 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

Citations172
Published2002
Admission routes2
Has abstractyes

Explore more

Same venueCanadian Modern Language Review/ La Revue canadienne des langues vivantesSame topicMultilingual Education and PolicyFrench-language works237,207