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Record W2501754583 · doi:10.1075/lllt.23.13whi

Speeding up acquisition of his and her: Explicit L1/L2 contrasts help

2008· article· en· W2501754583 on OpenAlex

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

VenueLanguage learning and language teaching · 2008
Typearticle
Languageen
FieldPsychology
TopicReading and Literacy Development
Canadian institutionsConcordia University
Fundersnot available
KeywordsGrammaticalityPossessivePsychologyContext (archaeology)Metalinguistic awarenessCognitionCognitive styleLinguisticsCognitive psychologyMetalinguisticsMathematics educationGrammarTeaching methodVocabulary development

Abstract

fetched live from OpenAlex

This paper reviews three pedagogical intervention studies that demonstrate the effectiveness of providing pre-adolescent and adolescent learners in communicatively-oriented classrooms with explicit metalinguistic information and opportunities to use it. The studies, which target the possessive determiners (PDs), his and her , follow a pretest/posttest design and were carried out in intact treatment and comparison classes. Measures consist of grammaticality judgement, metalinguistic comment, and oral picture description tasks. A number of issues are discussed in the context of older children’s second language learning in a classroom setting. These include implementing age-appropriate instruction that takes into account learners’ cognitive and linguistic readiness for form-focused instruction, their learning style and motivation, and the context of instruction.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.222
Threshold uncertainty score0.780

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.012
GPT teacher head0.295
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