Ethical Issues Related to IT Adoption by Elderly Persons with Cognitive Impairments
Bibliographic record
Abstract
Ethical issues arise when the risks and benefits of technology use are unclear or controversial, or their access inequitable. This paper presents a preliminary framework for understanding ethical issues related to IT development and adoption by elderly persons with cognitive impairments and their caregivers. The development of the framework relied on a hybrid qualitative approach that draws on several data sources: 1) systematic literature review, 2) focus groups with IT users, and 3) a reflexive researcher-learning diary.Preliminary findings were synthesized into a coherent model that views IT adoption as the outcome of complex interactions between different factors: 1) Personal factors that include the cognitive abilities of the users, as well as their physical and sensory limitations, and 2) Environmental factors that are related to the technology, the caregivers, and the support networks of the user with cognitive impairment. Findings from this project will help better understand, balance, and responsibly address the competing ethical issues at play in technology development and adoption by elderly persons with cognitive impairments and their caregivers.
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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 | 0.074 | 0.146 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.008 | 0.019 |
| Scholarly communication | 0.007 | 0.006 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".