Accessibility Work in Academia: Balancing Needs, Bridging Gaps, and Breaking Down Barriers
Bibliographic record
Abstract
Universities grow increasingly committed to equal access for individuals with disabilities, balancing the appearance of inclusion while upholding values of academic rigour. Within these universities, employees working in accessibility must mediate an unstable web of organizational and technological infrastructures. This study examines the government mandates, organizational structures, processes, and policies in a research university in Canada aimed at meeting the accessibility needs of its students. Our findings suggest that there is an interplay between informal and formal practices to navigate institutional systems. Technology serves as a mediator in the ''behind-the-scenes'' work that occurs at the intersection of infrastructures. Based on these findings, we provide recommendations to better support accessibility work in universities. We suggest the use of seamful design to support accessibility work, as it aligns with the dynamic nature of disability and distributed networks of accessibility work. We recommend designers foster interdependence to support workers who navigate overlapping infrastructures and breakdowns at the seams.
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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 | 0.026 | 0.039 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.029 | 0.020 |
| Scholarly communication | 0.018 | 0.019 |
| Open science | 0.004 | 0.028 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".