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Record W4252674644 · doi:10.1075/lllt.18

Learning and Teaching Languages Through Content

2007· book· en· W4252674644 on OpenAlexaffabout
Roy Lyster

Bibliographic record

VenueLanguage learning and language teaching · 2007
Typebook
Languageen
FieldArts and Humanities
TopicSecond Language Learning and Teaching
Canadian institutionsMcGill University
Fundersnot available
KeywordsInterlanguageCurriculumPedagogyContent (measure theory)Computer scienceMathematics educationComprehensionSet (abstract data type)NegotiationLanguage acquisitionPsychologyLinguisticsSociology

Abstract

fetched live from OpenAlex

Based on a synthesis of classroom SLA research that has helped to shape evolving perspectives of content-based instruction since the introduction of immersion programs in Montreal more than 40 years ago, this book presents an updated perspective on integrating language and content in ways that engage second language learners with language across the curriculum. A range of instructional practices observed in immersion and content-based classrooms is highlighted to set the stage for justifying a counterbalanced approach that integrates both content-based and form-focused instructional options as complementary ways of intervening to develop a learner’s interlanguage system. A counterbalanced approach is outlined as an array of opportunities for learners to process language through content by means of comprehension, awareness, and production mechanisms, and to negotiate language through content by means of interactional strategies involving teacher scaffolding and feedback.

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)0.000
metaresearch head score (Gemma)0.001
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: Other · Consensus signal: Other
Teacher disagreement score0.006
Threshold uncertainty score0.021

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.002
Scholarly communication0.0050.004
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0060.002

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 head0.021
GPT teacher head0.277
Teacher spread0.256 · 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
GenreOther

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

Citations638
Published2007
Admission routes2
Has abstractyes

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