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Record W2036175887 · doi:10.3138/cmlr.67.1.123

Family Treasures: A Dual-Language Book Project for Negotiating Language, Literacy, Culture, and Identity

2011· article· en· W2036175887 on OpenAlexfundvenueno aff
Hetty Roessingh

Bibliographic record

VenueCanadian Modern Language Review/ La Revue canadienne des langues vivantes · 2011
Typearticle
Languageen
FieldSocial Sciences
TopicMultilingual Education and Policy
Canadian institutionsnot available
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsPrideLiteracySociologyFamily literacyEllPedagogyIdentity (music)Context (archaeology)LinguisticsPolitical scienceTeaching methodVocabulary development

Abstract

fetched live from OpenAlex

This article advances a framework for early language and literacy development among young English language learners (ELLs). A dual-language book project undertaken in partnership with a local elementary school provides a context within which to address children's need to negotiate language, culture, and identity as they transition and make meaning from their home language (L1) to English and the language of school (L2) and back. Using objects of cultural and personal relevance that the children brought from home, stories of ‘Family Treasures’ were generated from the original telling in the L1 into English in small-group contexts, transcribed, illustrated, and uploaded to a Web site for permanent sharing, rereading, and exchange. These booklets also provided an opportunity for identity formation, pride of family and culture, and the acquisition of rudimentary technology skills, which all work to motivate and engage young learners in the development of early literacy.

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)0.004
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 score0.070
Threshold uncertainty score0.138

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0070.004
Scholarly communication0.0030.002
Open science0.0020.004
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0050.000

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 head0.058
GPT teacher head0.388
Teacher spread0.329 · 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

Citations32
Published2011
Admission routes2
Has abstractyes

Explore more

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