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Record W1542619166

Writing Life 1 in Language 2

2006· article· fr· W1542619166 on OpenAlexaff
Linda Steinman

Bibliographic record

VenueMcGill Journal of Education / Revue des sciences de l'éducation de McGill · 2006
Typearticle
Languagefr
FieldArts and Humanities
TopicDiscourse Analysis in Language Studies
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsHumanitiesSecond-language acquisitionLinguisticsTheme (computing)PsychologyPhilosophyComputer science
DOInot available

Abstract

fetched live from OpenAlex

ABSTRACT. What is second language acquisition like from the learner’s perspective? I examined published autobiographies authored by those who have documented their language learning journeys. One theme that recurred across the texts was Writing; a sub-theme was Writing life 1 in language 2. Some narrativists/learners described the dissonance, while others described the relief they felt when writing about events in a language other than the language in which those events occurred. Insights about writing provided by the learners/narrativists could illuminate both second language acquisition (SLA) theory and SLA pedagogy. ECRIRE LA VIE 1 DANS LA LANGUE 2 RESUME. Comment l’apprenant considere-t-il l’acquisition d’une langue seconde? J’ai examine des autobiographies publiees par des personnes qui ont documente leur parcours d’apprentissage d’une langue. L’un des themes recurrents des textes est l’ecriture; un sous-theme etant l’ecriture d’une vie dans une autre langue que la langue maternelle. Certains narrateurs/apprenants ont fait etat d’une discordance, tandis que d’autres ont exprime leur soulagement d’ecrire sur leur vie dans une langue autre que celle dans laquelle cette derniere s’est produite. Les observations que nous ont fournies les narrateurs/apprenants sur l’ecriture pourraient contribuer a enrichir la theorie de l’acquisition d’une langue seconde (SLA) et la pedagogie SLA.

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)0.003
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.803
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0020.001
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.000
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 head0.148
GPT teacher head0.393
Teacher spread0.246 · 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.

Study designTheoretical or conceptual
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

Citations6
Published2006
Admission routes1
Has abstractyes

Explore more

Same venueMcGill Journal of Education / Revue des sciences de l'éducation de McGillSame topicDiscourse Analysis in Language StudiesFrench-language works237,207