Universal Design on University Campuses: A Literature Review
Bibliographic record
Abstract
Disabled students face systemic, social and institutional barriers to quality education, and they may need accommodations to complete their post-secondary education (Canadian Human Rights Commission, 2017). Universities and professors often have difficulty determining the fairest and best way to meet the needs of disabled students (Sokal, 2016). A recent solution that has been applied in higher education is Universal Design (UD). UD signifies that resources and environments can be utilized by the greatest number of people (Scott, McGuire, & Shaw, 2003). A systematic review of the literature was conducted in order to identify UD articles related to accessibility on university campuses. THE AIM: We wanted to determine: (a) whether there was empirical research on UD in universities; (b) whether universities were open to implementing UD principles; (c) whether there were UD limitations or gaps in the literature. CONCLUSION: Educational professionals have a long way to go to eliminate barriers for disabled students on university campuses. UD is a positive starting point where universities and disabled students can meet and formulate a more inclusive experience of higher education.
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 imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.002 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.002 |
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 teacher head, 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".