Frailty's Place in Ethics and Law: Some Thoughts on Equality and Autonomy and on Limits and Possibilities for Aging Citizens
Bibliographic record
Abstract
Consideration of ethical and legal themes relating to frailty must engage with the concern that frailty is a pejorative concept that validates and reinforces the disadvantage and vulnerability of aging adults. In this chapter, we consider whether a greater focus on frailty may indeed be part of the solution to the disadvantages that aging adults face in achieving equality and maintaining their autonomy within systems that have used their frailty to deny them equality and autonomy. First, by examining equality both as an ethical norm and as a requirement for protections against discrimination, we raise questions about the grounds on which health providers and health systems can be required to give equal concern and respect to the needs of frail older persons. Second, we explore autonomy and identify the tension between meaningful self-determination and prevailing ethical and legal norms associated with informed choice. Third, we argue that a proper understanding of frailty is essential within both of these themes; it respects equality by enabling health providers and systems to identify and address the distinct care needs of aging adults and helps to align informed choice theory with appropriate processes for decision-making about those needs.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.002 | 0.012 |
| Scholarly communication | 0.004 | 0.008 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.005 | 0.006 |
| Insufficient payload (model declined to judge) | 0.002 | 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".