Editorial: Canadian Association on Gerontology Policy Statement on Assistive Devices for Seniors
Bibliographic record
Abstract
Statement of the Problem:Canada has no consistent policy on technology-related assistance for individuals with disabilities and/or physical limitations, or on financial assistance with the acquisition of such devices.Evidence suggests that financing is a major barrier to the use of assistive devices (LaPlante, Hendershot, & Moss, 1997;Kozarevic & Israel, 1987).This barrier has resulted in a lack of systematic reporting requirements for assistive devices services among direct-service programs, a lack of uniform classification of assistive devices expenditures, and blurred distinctions between assistive and mainstream technology (Mendelsohn, 1997).Scope: Assistive devices include "any item, piece of equipment, or product system, whether acquired commercially off the shelf, modified, or customized, that is used to increase, maintain, or improve functional capabilities of individuals with disabilities" (U.S. Technology Related Assistance for Individuals with Disabilities Act of 1988, Tech Act, 29 USC Sec.2201).Categories of assistive devices used by seniors include those for mobility, personal care, home skills, and leisure activities (Axell & Yasuda, 1993).There is insufficient evidence to support or refute the claim that assistive devices promote independence for seniors.However, it is known that assistive devices are commonly used by seniors; for example, nearly 35 per cent of Canadians 75 years and older use one or more devices, with vision aids being used by 90 per cent, and mobility and hearing aids increasing in use after 50 years of age to about 50 and 60 per cent respectively (Forbes, Hayward, & Agwani, 1993). Analysis of the Evidence:The fact that seniors who require assistive devices frequently either do not receive or do not use them suggests a lack of effectiveness in promoting seniors' independence through this means.Low education (Forbes et al., 1993), rural residence (Forbes et al., 1993;Kozarevic & Israel, 1987), social isolation (Forbes et al., 1993), female gender (Forbes et al., 1993;Kozarevic & Israel, 1987), membership in populations known to be underserved by systems for health and welfare (i.e., aboriginals and rural residents) (Galvin, 1997), and advanced age (Kozarevic & Israel, 1987) are associated with non-use and/or under-use by those who require assistive devices.However, it is important to note
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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 | 0.009 | 0.033 |
| Meta-epidemiology (narrow) | 0.005 | 0.002 |
| Meta-epidemiology (broad) | 0.005 | 0.004 |
| Bibliometrics | 0.006 | 0.004 |
| Science and technology studies | 0.007 | 0.004 |
| Scholarly communication | 0.009 | 0.005 |
| Open science | 0.006 | 0.002 |
| Research integrity | 0.045 | 0.036 |
| Insufficient payload (model declined to judge) | 0.016 | 0.017 |
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".