MétaCan
Menu
Back to cohort
Record W2888732156 · doi:10.1177/1525740118766480

Out of Time: The Experience of Speech-Generating Device Users

2018· article· en· W2888732156 on OpenAlexaff
Kathy Howery

Bibliographic record

VenueCommunication Disorders Quarterly · 2018
Typearticle
Languageen
FieldHealth Professions
TopicAssistive Technology in Communication and Mobility
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsPsychologyContext (archaeology)Lift (data mining)Computer scienceCognitive psychologyHistory

Abstract

fetched live from OpenAlex

This article presents a phenomenological investigation into speech-generating device (SGD) use in the school context. Derived from a larger study on the experience of speaking through a SGD, this article focuses particularly on the experience of time and timing of speaking for one who must use a SGD to give audible voice to their words. Themes explored in this article include the challenge of time, the untimely rate of speech, which can be silencing, planning to talk tomorrow, and finally text time and how this time may lift the burden of time from SGD users. Implications for educators and others who support children and youth who use SGD are brought forward through reflection and discussion of this unique experience of voice and time.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.005
metaresearch head score (Gemma)0.013
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.007
Threshold uncertainty score0.024

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.013
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0070.010
Scholarly communication0.0070.006
Open science0.0010.008
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0030.000

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 head0.064
GPT teacher head0.422
Teacher spread0.357 · 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 source (direct Gemma or distilled Codex), 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

Citations18
Published2018
Admission routes1
Has abstractyes

Explore more

Same venueCommunication Disorders QuarterlySame topicAssistive Technology in Communication and MobilityFrench-language works237,207