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Record W3171801177 · doi:10.3138/jmvfh-2020-0019

A consumer assessment of women who use wheelchairs

2021· article· en· W3171801177 on OpenAlexvenueno aff
Mark Greenhalgh, Stephanie K. Rigot, Stacy Eckstein, James Joseph, Rosemarie Cooper

Bibliographic record

VenueJournal of Military Veteran and Family Health · 2021
Typearticle
Languageen
FieldSocial Sciences
TopicDisability Rights and Representation
Canadian institutionsnot available
Fundersnot available
KeywordsWheelchairFocus groupUsabilityAthletesPsychologyService (business)Applied psychologyGerontologyMedical educationMedicineInternet privacyNursingPhysical therapyComputer scienceBusinessMarketingWorld Wide Web

Abstract

fetched live from OpenAlex

LAY SUMMARY Female Veterans and female athletes with disabilities express concerns with mobility devices that are male-centric and do not address their unique needs. It is important that the needs of women are given the same attention as those of men. The following study asked groups of women who use wheelchairs or scooters, including Veterans and athletes, about their experiences. Twenty-four women, recruited from two sporting events for Veterans with disabilities, were asked to fill out a survey and participate in a focus group where they would discuss their views on mobility aids and related services. There were four major themes women often mentioned when they talked about using their mobility aids: usability (how they like using it), service delivery (how they get help with it), well-being (how they feel), and design (how it looks and works). Participants were concerned about the ability to adjust their device to their needs, how people obtained a device, and how they felt about using the device. Female wheelchair and scooter users recommended several changes to mobility aids that would improve the devices and improve the lives of women who use them.

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)0.002
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.463
Threshold uncertainty score0.531

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.055
GPT teacher head0.382
Teacher spread0.327 · 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 designObservational
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

Citations11
Published2021
Admission routes1
Has abstractyes

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