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Record W2588938982 · doi:10.1177/0145482x1611000402

Rehabilitation and Research Priorities in Deafblindness for the Next Decade

2016· article· en· W2588938982 on OpenAlex

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

VenueJournal of Visual Impairment & Blindness · 2016
Typearticle
Languageen
FieldPsychology
TopicHearing Impairment and Communication
Canadian institutionsInstitut Universitaire de Gériatrie de MontréalUniversité de MontréalCentre Intégré Universitaire de Santé et de Services Sociaux du Centre-Sud-de-l'Île-de-MontréalMcGill UniversityMAB-Mackay Rehabilitation Centre
Fundersnot available
KeywordsRehabilitationThematic analysisService providerQualitative researchContext (archaeology)Focus groupPsychologyService (business)Perspective (graphical)Rehabilitation counselingMedical educationApplied psychologyNursingMedicineSociologyComputer scienceBusiness

Abstract

fetched live from OpenAlex

Purpose Previous studies have guided the development of deafblindness rehabilitation by reporting on the priorities of researchers and of deafblind individuals; however, service and care providers may be able to bring a different and important perspective to shaping the development of this clinical field and its research. The present study aims to give them a voice in this process. Methods We conducted a qualitative survey in which 68 stakeholders in deaf-blind rehabilitation from 6 countries described their perceived research and rehabilitation priorities for the coming decade. Verbatim transcripts were analyzed using thematic analysis through open coding, creating categories, and abstraction. Results Three categories of priorities emerged: those common to rehabilitation and research (such as assistive technology, communication services, and interdisciplinarity), those unique to rehabilitation (such as augmented service provision), and those unique to research (such as recruitment databases and measurement tools). Conclusions When viewing the findings from within the context of the existing research literature, the overlap indicated that research and rehabilitation efforts are moving in a congruent direction for researchers, service providers, and persons with deafblindness. Future efforts should focus on information exchange in order to improve evidence-based rehabilitation practice.

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)0.007
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.624
Threshold uncertainty score0.286

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0070.001
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 head0.150
GPT teacher head0.488
Teacher spread0.338 · 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