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Record W1987197647 · doi:10.1177/0741088305280350

Commitments to Academic Biliteracy

2005· article· en· W1987197647 on OpenAlexaffabout
Guillaume Gentil

Bibliographic record

VenueWritten Communication · 2005
Typearticle
Languageen
FieldArts and Humanities
TopicDiscourse Analysis in Language Studies
Canadian institutionsCarleton University
Fundersnot available
KeywordsAppropriationSociologyAcademic writingNeuroscience of multilingualismDisciplineEnglish for academic purposesField (mathematics)DocumentationPedagogyNegotiationTranslanguagingLinguisticsPsychologySocial science

Abstract

fetched live from OpenAlex

This article examines the appropriation of academic biliteracy by three French-speaking students at an English-medium university in the Canadian province of Québec. Drawing on Hornberger’s continua model of biliteracy, Bourdieu’s critical social theory, and philosophical hermeneutics, the author conceptualizes individual biliterate development as a subjective and intersubjective evaluative response to social contexts of possibilities for biliteracy. Case study data were collected during 2 ½ years and included autobiographical and text-based interviews, inventories and analyses of academic writing in English and French, classroom-based observations, field notes, and documentation of the legal, historical, institutional, and demographic contexts. Analyses of the participants’ negotiations and trajectories of bilingual academic writing development reveal the challenges and resources of bilingual writers to uphold their commitment to academic biliteracy within English-dominant institutional and disciplinary contexts. Implications for the advancement of multilingual academic literacies are drawn.

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)0.006
metaresearch head score (Gemma)0.022
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.121
Threshold uncertainty score0.240

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.022
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0210.024
Scholarly communication0.0100.003
Open science0.0020.011
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0040.000

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 head0.041
GPT teacher head0.325
Teacher spread0.284 · 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 designNot applicable
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

Citations73
Published2005
Admission routes2
Has abstractyes

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