Access for Whom? An Examination of Public-Facing Accessibility Practices in Library Accessibility Alliance Members’ Open Access Institutional Repositories
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Introduction: Open access aims to provide access to research and scholarship without barriers. An important tool in this process has been institutional repositories (IRs), which disseminate and preserve open scholarship. The goal of this research project was to examine the extent to which IRs in the U.S. are incorporating publicfacing accessibility practices to make their open access works accessible to users of all abilities. Method: This environmental scan reviews the IRs of Library Accessibility Alliance member institutions to identify the prevalence of accessibility practices across those IRs, including contact information, accessibility statements, instructions for submitters, and accessibility-related metadata. Results: This environmental scan found that all but two institutions offered contact information, an avenue for requesting remediation and asking questions. Just over half of the institutions offered IR accessibility documentation, and many linked to other institutional accessibility documentation. Additionally, slightly under a quarter of the institutions provided support for researchers hoping to make their submissions accessible, and three included accessibility information in item-level metadata. Conclusion: While many IR teams are taking some steps to ensure that their IRs are accessible, many accessibility features are not standard across the IRs examined in this study, which suggests the potential for future improvement. Expanded adoption of accessibility best practices would improve access to IR materials and help achieve the ultimate goals of the open access movement.
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.
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 | 0.011 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.035 | 0.251 |
| Open science | 0.005 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it