Students with disabilities as partners: A case study on user testing an accessibility website
Bibliographic record
Abstract
While partnership is widely encouraged as an approach to advancing the inclusion of disabled postsecondary students, these collaborations are largely taking place between staff offices and failing to meaningfully integrate disabled students as partners. In this case study, we describe the successes and challenges of a pilot project where students and staff with and without disabilities worked together to user test our university’s accessibility website, to which faculty/staff are regularly directed for resources on making their teaching more accessible. We achieved our goal of compiling results into a report for decision-makers in order to advance campus-wide technological accessibility. Instead of primarily treating disabled students as lacking capacities and requiring programmatic intervention to succeed in the university, a partnership approach validates and draws on disabled students’ specific expertise and experience to make institutional change.
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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 | 0.009 | 0.025 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.020 | 0.010 |
| Scholarly communication | 0.007 | 0.006 |
| Open science | 0.004 | 0.015 |
| Research integrity | 0.006 | 0.007 |
| Insufficient payload (model declined to judge) | 0.005 | 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".