MétaCan
Menu
Back to cohort
Record W4307244303 · doi:10.1075/itl.22008.rob

3K-LEx-MC

2022· article· en· W4307244303 on OpenAlex
Pablo Robles‐García, Glen Wallace, Claudia Sánchez‐Gutiérrez

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

VenueITL Review of Applied Linguistics · 2022
Typearticle
Languageen
FieldPsychology
TopicSecond Language Acquisition and Learning
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsRasch modelCourseworkTest (biology)VocabularyReliability (semiconductor)Mathematics educationPsychologyItem analysisCurse of dimensionalityItem response theoryPolytomous Rasch modelEnglish as a foreign languageNatural language processingComputer scienceStatisticsMathematicsLinguisticsPsychometrics

Abstract

fetched live from OpenAlex

Abstract This study presents the development and validation of a 132-item Spanish-English bilingual multiple-choice vocabulary test based on the 3,000 most frequent lemmas that distinguishes between North American university students who satisfy the Foreign Language requirement and those who need to complete coursework. 819 students were assigned to one of the two 144-item forms of the preliminary test, which had 72 shared anchor items and other 72 form-specific items. Factor analysis was used to evaluate dimensionality and the Rasch model was used to select the items that best differentiated between these two student populations. This final form was administered to 213 students. Results showed high levels of unidimensionality, and the final form provided a Rasch reliability coefficient of 0.97.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.904
Threshold uncertainty score0.837

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 integrity0.0000.000
Insufficient payload (model declined to judge)0.1640.000

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 head0.017
GPT teacher head0.328
Teacher spread0.312 · 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