Give Us Vision, Lest We Perish: Engaging Disability at the National Library of Jamaica
Bibliographic record
Abstract
The World Health Organization (WHO) estimated that 15% of the world’s population has a disability (WHO, 2011, p. 8). In Jamaica, the 2014 Disabilities Act affirms that people with disabilities have the right to education and training to ensure their ability to effectively and equally be included in all aspects of national life. While the true figures are underreported, a 2011 census found that 487,677 Jamaicans experience hearing problems. Of that figure, 5,628 persons range from being deaf to significantly hearing impaired (Statistical Institute of Jamaica, 2011). As the keeper of the nation’s knowledge, the National Library of Jamaica (NLJ) must be accessible to all members of the nation, regardless of disability or physical limitations. In April 2018, the NLJ embarked on an initiative to enhance engagement of people with disabilities through a sign language training initiative for staff. For this pilot project, 14 staff members from various departments participated in weekly sign language training sessions for a period of 12 weeks. This training series is part of a wider initiative to improve accessibility at the NLJ for both staff and patrons. With a workforce that includes employees with disabilities, the NLJ has been engaged in the work of improving inclusion and engagement of individuals with disabilities. This paper outlines the existing challenges facing a Jamaican government entity as it moves to improve inclusivity, ongoing programmes, and outreach efforts to improve information literacy. This is being accomplished through partnerships with organizations working within Jamaica’s Deaf community and through plans for designing a new, inclusive, and purpose-built facility to house the national collection.
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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 | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.019 | 0.003 |
| Scholarly communication | 0.010 | 0.006 |
| Open science | 0.002 | 0.010 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.019 | 0.006 |
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".