MétaCan
Menu
Back to cohort
Record W2105281284 · doi:10.1177/1049732314546755

Assistive Technology Provision Within the Navajo Nation

2014· article· en· W2105281284 on OpenAlexaff
Kim D. Reisinger, Jacquie Ripat

Bibliographic record

VenueQualitative Health Research · 2014
Typearticle
Languageen
FieldHealth Professions
TopicAssistive Technology in Communication and Mobility
Canadian institutionsUniversity of Manitoba
FundersU.S. Department of Education
KeywordsFocus groupNavajoAffect (linguistics)FeelingQualitative researchStakeholderAssistive technologyTheme (computing)PsychologyNursingPublic relationsMedical educationMedicineSociologyBusinessSocial psychologyPolitical scienceMarketingComputer scienceCommunication

Abstract

fetched live from OpenAlex

In this study we explored the factors that affect assistive technology (AT) provision within the Navajo Nation using a qualitative approach to inquiry. Focus groups were held in which AT users discussed their awareness of AT and their need for, use of, and satisfaction with AT devices and services. Twenty-eight individuals who used wheelchairs, orthotics or prosthetics, hearing aids, communication aids, vision aids, and other AT participated in one of seven focus groups. Seven AT providers discussed the facilitators and barriers that affect AT provision. The findings revealed six themes common to both stakeholder groups and two additional themes for AT users. The central theme for AT users centered on (not) feeling understood; the central theme for AT providers revolved around the processes, activities, and roles the providers engaged in at times for different clients. Activities to increase awareness and to promote successful AT provision and satisfaction with AT devices were proposed.

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)0.001
metaresearch head score (Gemma)0.003
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 score0.040
Threshold uncertainty score0.079

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0040.001
Scholarly communication0.0020.001
Open science0.0000.003
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.582
GPT teacher head0.681
Teacher spread0.100 · 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
Published2014
Admission routes1
Has abstractyes

Explore more

Same venueQualitative Health ResearchSame topicAssistive Technology in Communication and MobilityFrench-language works237,207