Assistive Technology: A Global Perspective
Bibliographic record
Abstract
Assistive technology (AT) is a means of realizing the Sustainable Development Goals and a right affirmed by the United Nations Convention on the Rights of Persons with Disability. AT is an umbrella term encompassing assistive products and the systems and services required to deliver them. Assistive products include devices, instruments, equipment, and software, and may be especially produced or generally available. Assistive products support functioning and independence for people who have functional limitations including those associated with aging, disability, and other health conditions. AT services refer to the human factors which fit product to person, environment, and goals such as assessment, fitting, training, adaption, and outcome measurement. This entry takes a contemporary global perspective of AT. The entry summarizes the development of technology in relation to functional impairment and considers how we might understand and harness rapid technological developments. The complex AT ecosystem is discussed, articulating the people who use AT, the personnel who assess, fit, adapt, and maintain AT, the provision systems that enable access to AT, and the policy contexts which govern AT. Globally applicable approaches to collect data on, and scale access to, AT are presented.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.007 | 0.008 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.027 | 0.011 |
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".