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Record W1985934573 · doi:10.1080/15595690801894269

From Peanut Butter to Eid … Blending Perspectives: Teaching Urdu to Children in Canada

2008· article· en· W1985934573 on OpenAlexaffabout
Rahat Naqvi

Bibliographic record

VenueDiaspora Indigenous and Minority Education · 2008
Typearticle
Languageen
FieldSocial Sciences
TopicMultilingual Education and Policy
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsUrduEthnographyLiteracyImmigrationIdentity (music)Context (archaeology)SociologyPedagogyMathematics educationPsychologyLinguisticsHistoryLiteratureAnthropologyArtAesthetics

Abstract

fetched live from OpenAlex

The focus of this article is to examine the notions of language learning, heritage (referring to tradition) and ancestry (descendants & properties passed on), and cultural identification for Urdu-speaking immigrant children now living in Canada. This article provides a detailed ethnographic account of an innovative language program developed to teach Urdu to children within the Canadian context. The author draws on the research of Taylor (1983) Taylor, D. 1983. Family literacy: Young children learning to read and write, Portsmouth, NH: Heinemann. [Google Scholar] to show that the evolution of literacy transmission is highly dependent on the childhood experiences of individual educators and evolves through the interplay of their unique biographies and educative styles, including the use of various texts. Questions explored include the following: What types of texts are used? What are the students' reactions to the texts? What are the teacher's practices within the classrooms? What kind of an impact does the learning of Urdu have on the identity construction of these 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 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: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.387
Threshold uncertainty score0.999

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 head0.022
GPT teacher head0.348
Teacher spread0.326 · 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 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

Citations5
Published2008
Admission routes2
Has abstractyes

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