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Record W2071887228 · doi:10.1558/sols.v1.i1.47

The dictée in multilingual contexts

2008· article· en· W2071887228 on OpenAlex
Ann Beer, Mary Maguire, Reiko Yoshida, Hourig Attarian, Diane Baygin, Xiao Lan Curdt‐Christiansen, Heekyeong Lee, Arminée Yaghejian

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueSociolinguistic Studies · 2008
Typearticle
Languageen
FieldArts and Humanities
TopicEFL/ESL Teaching and Learning
Canadian institutionsMcGill University
Fundersnot available
KeywordsDictationNarrativeLiteracyArmenianVariety (cybernetics)EmpowermentLinguisticsEstonianPsychologyPedagogySociologyTask (project management)Computer sciencePolitical science

Abstract

fetched live from OpenAlex

We examine a familiar classroom task: the dictation exercise or dictée. This apparently simple pedagogical practice occurs in a variety of language learning settings internationally. Using extracts from our multilingual research group members’ narratives and conversations, we explore dictation in six language contexts (Chinese, Japanese, Korean, Armenian, French and English). The narratives are organized into four themes: power issues in the classroom, conservative vs. innovative pedagogies, linguistic features, and implications. We raise questions about the relationships between literacy and student empowerment in different contexts.

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.

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)0.004
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.776
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0020.001
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 head0.119
GPT teacher head0.346
Teacher spread0.227 · 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