Celebrating Inclusive Libraries by Applying Universal Design: A Guide (book review)
Bibliographic record
Abstract
Carli Spina's admirably readable Creating inclusive libraries by applying universal design provides librarians with a practical, theoretically grounded introduction to Universal Design (UD) and Universal Design for Learning (UDL).This book guides librarians in understanding and applying UD and UDL principles to make their products, spaces, and services more inclusive and welcoming.The following quote captures a key theme in this book: "To remain relevant when serving […] a diverse group of people with widely varied needs, libraries will need to focus on the type of flexibility, equity, and attention to user experience at the heart of Universal Design" [1].UD is "an approach to design defined by its focus on the user and how it contemplates who the user is" (Spina) [1].Historically, it was based in the need to design spaces to reduce barriers, particularly for individuals with disabilities.This book argues that the principles of Universal Design can be applied more broadly to reducing barriers to library spaces, services, and products, and making them welcoming to people with widely varied needs.Extending the concept of inclusion to the educational sphere, UDL is a framework that adapts UD "concepts and principles so as to make them meaningful in a broad range of educational settings and scenarios" [1].Spina holds a JD from the University of Chicago Law School, an MLIS from Simmons GSLIS, and an MEd from the Harvard Graduate School of Education.She has contributed to work on equity, diversity, and inclusion in a variety of capacities, including serving in leadership roles on LITA's Diversity and Inclusion Committee, and the ASCLA Library Services to People with Visual or Physical Disabilities that Prevent Them from Reading Standard Print Interest Group.Her experience and educational background
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.007 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.005 | 0.006 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.016 | 0.008 |
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".