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Record W2115068291 · doi:10.1093/deafed/enr004

Adapting the Assessing British Sign Language Development: Receptive Skills Test Into American Sign Language

2011· article· en· W2115068291 on OpenAlexaff
Charlotte Enns, R. Herman

Bibliographic record

VenueThe Journal of Deaf Studies and Deaf Education · 2011
Typearticle
Languageen
FieldPsychology
TopicHearing Impairment and Communication
Canadian institutionsUniversity of Manitoba
Fundersnot available
KeywordsAmerican Sign LanguageSign languageLanguage interpretationTest (biology)PsychologyManually coded languageSign (mathematics)Language assessmentDeaf educationStandardized testSociolinguistics of sign languagesLinguisticsMathematics educationComputer science

Abstract

fetched live from OpenAlex

Signed languages continue to be a key element of deaf education programs that incorporate a bilingual approach to teaching and learning. In order to monitor the success of bilingual deaf education programs, and in particular to monitor the progress of children acquiring signed language, it is essential to develop an assessment tool of signed language skills. Although researchers have developed some checklists and experimental tests related to American Sign Language (ASL) assessment, at this time a standardized measure of ASL does not exist. There have been tests developed in other signed languages, for example, British Sign Language, that can serve as models in this area. The purpose of this study was to adapt the Assessing British Sign Language Development: Receptive Skills Test for use in ASL in order to begin the process of developing a standardized measure of ASL skills. The results suggest that collaboration between researchers in different signed languages can provide a valuable contribution toward filling the gap in the area of signed language assessment.

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)0.001
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.595
Threshold uncertainty score0.400

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 studies0.0010.000
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 head0.041
GPT teacher head0.369
Teacher spread0.328 · 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 designQualitative
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

Citations67
Published2011
Admission routes1
Has abstractyes

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