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Record W4306942271 · doi:10.4102/ajod.v11i0.936

Transport experiences of people with disabilities during learnerships

2022· article· en· W4306942271 on OpenAlexaff
Amanda Gibberd, Ntombizivumile Hankwebe

Bibliographic record

VenueAfrican Journal of Disability · 2022
Typearticle
Languageen
FieldSocial Sciences
TopicUrban Transport and Accessibility
Canadian institutionsTransport Canada
FundersUniversiteit Stellenbosch
KeywordsLanguage barrierPublic transportPsychologySample (material)Political scienceTransport engineeringChemistryEngineering

Abstract

fetched live from OpenAlex

Transport is a known national barrier for people with disabilities in South Africa. It is similarly identified as a barrier in learnerships and economic opportunity programmes. This article discusses the extent to which transport is a barrier during learnerships for students with disabilities. The Department of Transport administered an online evaluation questionnaire to a random sample of students with disabilities. Results were coded in terms of 'barriers to access' and 'barriers to participation'. The data were organised into themes. The collated evidence is discussed in this article. The findings demonstrated that transport barriers were present in different modes of transport and different parts of the travel chain. However, the findings also demonstrated the negative impact of transport on the learnership experience and economic opportunities. The findings indicated that inaccessible transport is an integral cause of learnership incompletion for students with disabilities, where the universal accessibility of both transport and the built environment are a prerequisite need. Most students with disabilities reported that transport was not a barrier to learnership participation or that problems with transport could be resolved. Nevertheless, it was one of the identified barriers that negatively affected learnership participation experiences. It was a significant barrier to learnership completion for students with the most severe experience of disability. The sample consisted of only 32 students and a high number of unspecified responses. Evidence from other studies indicates that transport for all persons with disabilities remains a barrier warranting further examination, because public transport has remained inaccessible for over 23 years. Further research is required to verify this study and to investigate learnership cost-benefit for all students.

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)0.002
metaresearch head score (Gemma)0.008
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 score0.019
Threshold uncertainty score0.037

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.008
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0080.003
Scholarly communication0.0040.003
Open science0.0010.008
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0040.000

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 head0.023
GPT teacher head0.269
Teacher spread0.246 · 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

Citations8
Published2022
Admission routes1
Has abstractyes

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