A relational perspective on autonomy for older adults residing in nursing homes
Bibliographic record
Abstract
AIM: To review critically the traditional concept of autonomy, propose an alternative relational interpretation of autonomy, and discuss how this would operate in identifying and addressing ethical issues that arise in the context of nursing home care for older adults. BACKGROUND: Respect for patient autonomy has been the cornerstone of clinical bioethics for several decades. Important though this principle is, there is debate on how to interpret the core concept of autonomy. We review the appeal of the traditional approach to autonomy in health care and then identify some of the difficulties with this conception. METHODS: We use philosophical methods to explain and discuss the traditional and relational conceptions of autonomy and we illuminate our discussion with examples of various contextual applications. CONCLUSION: We support the relational conception of autonomy as offering a richer, more contextualized understanding of autonomy which attends to the social, political and economic conditions that serve as background to an agent's deliberations. To illuminate these ideas, we discuss the situation of frail older adults who frequently find their autonomy limited not only by their medical conditions but also by cultural prejudices against the aged and by the conditions commonly found within the nursing homes in which many reside. We propose ways of improving the relational autonomy of this population.
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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 | 0.006 | 0.022 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.007 | 0.015 |
| Scholarly communication | 0.003 | 0.006 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.019 | 0.025 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".