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Record W2140292502 · doi:10.1111/lang.12129

Validating an Elicited Imitation Task as a Measure of Implicit Knowledge: Comparisons With Other Validation Studies

2015· article· en· W2140292502 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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueLanguage Learning · 2015
Typearticle
Languageen
FieldArts and Humanities
TopicEFL/ESL Teaching and Learning
Canadian institutionsUniversity of Toronto
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsPsychologyConstruct (python library)ImitationTask (project management)Construct validityCognitive psychologyImplicit knowledgeMeasure (data warehouse)LinguisticsSocial psychologyPsychometricsCognitive scienceDevelopmental psychologyComputer science

Abstract

fetched live from OpenAlex

This study builds on research investigating the construct validity of elicited imitation (EI) as a measure of implicit second language (L2) grammatical knowledge. It differs from previous studies in that the EI task focuses on a single grammatical feature and time on task is strictly controlled. Seventy‐three EFL learners and 20 native English speakers completed the EI and four other tests hypothesized as measures of implicit or explicit L2 knowledge. Factor analytic results indicated that learners’ EI scores loaded on the factor labeled implicit L2 knowledge, confirming previous findings. Results from other tests and methodological issues concerning EI design and use suggest that the construct validation of EI as a measure of implicit L2 grammatical knowledge awaits further investigation.

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)0.001
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 score0.041
Threshold uncertainty score0.550

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
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 integrity0.0000.000
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 head0.114
GPT teacher head0.358
Teacher spread0.245 · 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