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Record W2180011677 · doi:10.1093/deafed/env049

Comprehension of Written Grammar Test: Reliability and Known-Groups Validity Study With Hearing and Deaf and Hard-of-Hearing Students

2015· article· en· W2180011677 on OpenAlexafffund
Joanna Cannon, Anita M. Hubley, Courtney L. Millhoff, Shahla Mazlouman

Bibliographic record

VenueThe Journal of Deaf Studies and Deaf Education · 2015
Typearticle
Languageen
FieldPsychology
TopicHearing Impairment and Communication
Canadian institutionsUniversity of British Columbia
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsPsychologyTest (biology)GrammarComprehensionAudiologyReliability (semiconductor)SentenceTest validityVocabularyDevelopmental psychologyPsychometricsLinguisticsNatural language processingComputer scienceMedicine

Abstract

fetched live from OpenAlex

The aim of the current study was to gather validation evidence for the Comprehension of Written Grammar (CWG; Easterbrooks, 2010) receptive test of 26 grammatical structures of English print for use with children who are deaf and hard of hearing (DHH). Reliability and validity data were collected for 98 participants (49 DHH and 49 hearing) in Grades 2-6. The objectives were to: (a) examine 4-week test-retest reliability data; and (b) provide evidence of known-groups validity by examining expected differences between the groups on the CWG vocabulary pretest and main test, as well as selected structures. Results indicated excellent test-retest reliability estimates for CWG test scores. DHH participants performed statistically significantly lower on the CWG vocabulary pretest and main test than the hearing participants. Significantly lower performance by DHH participants on most expected grammatical structures (e.g., basic sentence patterns, auxiliary "be" singular/plural forms, tense, comparatives, and complementation) also provided known groups evidence. Overall, the findings of this study showed strong evidence of the reliability of scores and known group-based validity of inferences made from the CWG.

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 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)0.002
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.021
Threshold uncertainty score0.359

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
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)0.0000.000

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 head0.135
GPT teacher head0.398
Teacher spread0.263 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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

Citations6
Published2015
Admission routes2
Has abstractyes

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