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Record W2153599438 · doi:10.3138/cmlr.63.4.563

Literacy Autobiographies in a University ESL Class

2007· article· en· W2153599438 on OpenAlexvenueno aff
Linda Steinman

Bibliographic record

VenueCanadian Modern Language Review/ La Revue canadienne des langues vivantes · 2007
Typearticle
Languageen
FieldArts and Humanities
TopicDiscourse Analysis in Language Studies
Canadian institutionsnot available
Fundersnot available
KeywordsLiteracyPedagogyClass (philosophy)Sociocultural evolutionContext (archaeology)Second language writingSociologyRhetoricMathematics educationLanguage educationLinguisticsSecond languageComputer sciencePsychology

Abstract

fetched live from OpenAlex

Abstract: I define the literacy autobiography as a reflective, first-person account of one's development as a writing being. In this article I share a classroom practice that invited language learners to consider and compose their literacy autobiographies (LA). The context was a university credit English as a second language (ESL) classroom. The purposes of the LA were to enact many of the principles and concepts considered beneficial to second language writing, particularly the bringing of the first language (L1) into the second language (L2) classroom, and to engage with students in constructivist learning. I describe why and how I envisioned this small LA project; how we (the students and I) enacted the project; the theoretical frameworks supporting LA; how the project developed into a contrastive analysis assignment; and, finally, why I must revision the project. In my view, contrastive rhetoric, contrastive analysis, communities of practice, multiliteracies, and sociocultural theory all provide support for using LA in the classroom.

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)0.006
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 score0.013
Threshold uncertainty score0.048

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0030.001
Science and technology studies0.0080.005
Scholarly communication0.0050.002
Open science0.0010.003
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0080.001

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 head0.012
GPT teacher head0.230
Teacher spread0.217 · 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

Citations19
Published2007
Admission routes1
Has abstractyes

Explore more

Same venueCanadian Modern Language Review/ La Revue canadienne des langues vivantesSame topicDiscourse Analysis in Language StudiesFrench-language works237,207