Access and Inclusion: The Experiences of Postsecondary Students with Mobility-Related Physical Disabilities
Bibliographic record
Abstract
Relatively little is known about how physical and social environments influence access to and inclusion in educational and leisure activities for students with a mobility-related physical disability attending a post-secondary institution. Understanding how environments shape access is important because educational and leisure activities affect one’s emotional, social, mental, and physical health. The aim of this qualitative exploratory study was to gain an understanding of the lived experiences of access and inclusion for students with a mobility-related physical disability, and specifically, the barriers and facilitators within the physical and social environments which shape access and inclusion. One-on-one semi-structured interviews were conducted with nine students attending a post-secondary institution in Nova Scotia, Canada who self-identified as living with a mobility-related physical disability. From an analysis of the interviews, five themes emerged: 1) navigating disclosure; 2) invisibility (and passing) and visibility; 3) accommodations and supports; 4) the prevailing conceptualization of mobility-related disabilities; and 5) places and spaces for the “normal” body. Although there have been actions taken by the post-secondary institution to transform environments and improve access and inclusion, additional efforts are urgently needed, and it is suggested that Universal Design is one possible strategy.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.011 | 0.008 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.001 | 0.012 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".