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Record W2912489701 · doi:10.33137/cpoj.v1i2.32046

HEALTH CARE ACCESSIBILITY FOR INDIVIDUALS WITH DISABILITIES: BARRIERS AND RISK FACTORS IMPACTING CARE

2018· article· en· W2912489701 on OpenAlexvenueaboutno aff
Abbey Senczyszyn, J. Chad Duncan

Bibliographic record

VenueCanadian Prosthetics & Orthotics Journal · 2018
Typearticle
Languageen
FieldSocial Sciences
TopicDisability Rights and Representation
Canadian institutionsnot available
Fundersnot available
KeywordsHealth careConstruct (python library)PsychologyHealth professionalsPresentation (obstetrics)NursingGerontologyPublic relationsMedicinePolitical scienceComputer scienceLaw

Abstract

fetched live from OpenAlex

BACKGROUND
 Healthcare professionals have certain professional, legal, and ethical obligations that they must fulfill with each patient interaction. Though professional and legal obligations may vary between fields of practice, the core ethical responsibility remains the same: provide just health care1. This requires that healthcare professionals are aware of systemic and institutional factors that lead to disparity and discrimination in the provision of health services1. Disability is a complex construct that can be related to various factors related to health condition as well as social and environmental factors that influence participation. This complexity results in varying definitions; the ICF model of disability was used in this research2.
 Abstract PDF Link:https://jps.library.utoronto.ca/index.php/cpoj/article/view/32046/24460
 How to cite: Senczyszyn A, Duncan J.C. HEALTH CARE ACCESSIBILITY FOR INDIVIDUALS WITH DISABILITIES: BARRIERS AND RISK FACTORS IMPACTING CARE. CANADIAN PROSTHETICS & ORTHOTICS JOURNAL, VOLUME 1, ISSUE 2, 2018; ABSTRACT, POSTER PRESENTATION AT THE AOPA’S 101ST NATIONAL ASSEMBLY, SEPT. 26-29, VANCOUVER, CANADA, 2018. DOI: https://doi.org/10.33137/cpoj.v1i2.32046 
 Abstracts were Peer-reviewed by the American Orthotic Prosthetic Association (AOPA) 101st National Assembly Scientific Committee. 
 http://www.aopanet.org/

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.668
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0040.002
Scholarly communication0.0010.000
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 head0.022
GPT teacher head0.343
Teacher spread0.321 · 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.

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

Citations1
Published2018
Admission routes2
Has abstractyes

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