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Record W4387670579 · doi:10.3390/educsci13101033

Communication, Language, and Modality in the Education of Deaf Students

2023· article· en· W4387670579 on OpenAlex
Connie C. Mayer, Beverly J. Trezek

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

VenueEducation Sciences · 2023
Typearticle
Languageen
FieldPsychology
TopicHearing Impairment and Communication
Canadian institutionsYork University
Fundersnot available
KeywordsConversationDeaf educationModality (human–computer interaction)Cognitive reframingContext (archaeology)Spoken languageLiteracyPsychologyFocus (optics)PopulationLinguisticsPedagogySign languageComputer scienceSociologyCommunicationSocial psychology

Abstract

fetched live from OpenAlex

In the history of deaf education, questions attending communication, language, and modality have generated much discussion, and even heated debate. This should not be surprising as these questions touch on a fundamental issue that is central to policy and practice in the field—how to provide early, ready, and meaningful linguistic access. While one point of agreement is that such access is vital for age-appropriate language and literacy development, there is less consensus on how this access should be realized. This focus has heightened consequences and significance in the current context in which auditory access to spoken language is possible for the majority of deaf children. With a goal of reframing the conversation, the focus of this article will be on making the critical distinctions between language and modality that can inform understandings as to how access can be best achieved for an increasingly diverse population of deaf children and their families.

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)0.002
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 score0.145
Threshold uncertainty score0.199

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.081
GPT teacher head0.503
Teacher spread0.422 · 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