How Can Ethics Support Innovative Health Care for an Aging Population?
Bibliographic record
Abstract
The rapidly expanding aging population presents an urgent global challenge cutting through just about every dimension of worldly life, including the social, political, cultural, and economic. Developing innovations in health and assistive technology (AT) are poised to support effective and sustainable health care in the face of this challenge, yet there is scant (but growing) discussion of the ethical issues surrounding AT for older persons with dementia. Demands for ethical frameworks that can respond to frontline dilemmas regarding AT development and provision, and how the needs of aging persons themselves are defined throughout this development process, are increasing. This article suggests that fulfilling the promises of AT to provide effective and ethically informed solutions may demand shifting away from standard bioethical analyses that centralize the principle of respect for autonomy. An autonomy-centric paradigm is dubiously equipped to theorize the foundational ethical issues in dementia care and to effectively guide AT development and implementation. An agency-centered approach to dementia care, which could engage more adaptively with the perspectives and choices of older persons themselves while offering strong support to AT research and stakeholders, may offer an attractive alternative.
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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 | 0.067 | 0.099 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.011 | 0.087 |
| Scholarly communication | 0.016 | 0.019 |
| Open science | 0.003 | 0.012 |
| Research integrity | 0.014 | 0.014 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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".