Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Background: Health disparities are preventable differences in the opportunities to achieve optimal health that are experienced by socially disadvantaged populations. Older people are at a greater risk of experiencing health disparities than younger people. Technology has great potential for reducing disparities, particularly as we improve our understanding of the role it plays in social processes of aging. The next generation of assistive technologies should be informed by research on how best to ensure that they can be easily and effectively integrated with educational, health and social services, and that their benefits can be distributed equitably across all populations of persons who are ageing. Method: This author conducted a scoping review of the literature on the relationship between assistive technology and social determinants of healthy ageing. A search was conducted for journal publications of original research studies and reviews in the English language. Search engines included PubMed (Medline), CINAHL (Ebsco), PsycINFO and Web of Science, using the following parameters: aging population (including elderly and seniors); assistive technology (including communication technology and health technology); health disparities (including health inequities, social isolation, and social determinants of health). Key results: Two social constructs are central to social relationships and physical health in ageing: social support and social integration. Social support refers to a social network's provision of psychological and material resources intended to benefit an individual's ability to cope with stress. Social integration is defined as participation in a broad range of social relationships. It is a multidimensional construct thought to include a behavioral component and a cognitive component. Assistive technology (AT) is capable of influencing both of these
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 it