Users with Disabilities, Especially Invisible Disabilities, Provide Insight into How Libraries Can Frame Accessibility Webpages
Bibliographic record
Abstract
A Review of: Brunskill, A. (2020). “Without that detail, I’m not coming”: The perspectives of students with disabilities on accessibility information provided on academic library websites. College & Research Libraries, 81(5), 768–788. https://doi.org/10.5860/crl.81.5.768 Abstract Objective – To understand the needs and preferences of users with disabilities for libraries’ accessibility webpages (webpages dedicated to information on disability and accessibility). Design – Semi-structured interviews. Setting – A large public university in the United States of America. Subjects – 12 students who self-identify as having a disability. Methods – Participants were asked about their expectations (if any) and experiences using library accessibility webpages, how they felt they should be organized, and where and how they would expect to find such webpages. Two lists were printed out and provided to the participants. The first, compiled from a previous study, listed common website headings (categories) under which accessibility webpages had been found, and this aided participants in selecting where they would go to find such a webpage. The second listed common types of information found on accessibility webpages. Participants were asked to use the second list to come up with their five highest priority items for accessibility webpages to cover. Interviews were recorded, transcribed, and analyzed for responses to specific queries, but inductive coding was also used. Main Results – In most of the five response clusters of interest to the author (experience/expectation of such a page existing, navigation and language preferences, overall tone and feel for the website, organization for the page, and content for the page), answers were mixed. No consensus emerged with respect to participants’ expectation of an accessibility webpage existing, how they would find the page (including the best website heading), and what content the page should contain. Participants noted that language should be welcoming and inclusive and vetted for sensitivity. The physical layout of the library and information about ambiance and furniture was frequently noted as being an important and overlooked detail to include. Some services, such as shelf pulling and online chat, were highlighted as appealing to those with “invisible” disabilities. Conclusion – The needs and preferences of users with disabilities are varied and sometimes mutually conflicting. Based on the findings, fourteen recommendations are suggested, including providing detailed information about sensory aspects of the library, listing contact information (preferably to a named individual or group), providing useful headings within the page, and evaluating whether language on the website is welcoming.
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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 | 0.004 | 0.017 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.006 | 0.004 |
| Science and technology studies | 0.005 | 0.005 |
| Scholarly communication | 0.011 | 0.017 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.013 | 0.004 |
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".