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Record W2218861156 · doi:10.1159/000381235

Frailty's Place in Ethics and Law: Some Thoughts on Equality and Autonomy and on Limits and Possibilities for Aging Citizens

2015· review· en· W2218861156 on OpenAlexafffund
Mary McNally, William Lahey

Bibliographic record

VenueInterdisciplinary topics in gerontology and geriatrics · 2015
Typereview
Languageen
FieldEconomics, Econometrics and Finance
TopicHealth Systems, Economic Evaluations, Quality of Life
Canadian institutionsDalhousie University
FundersNova Scotia Health Research Foundation
KeywordsAutonomyDisadvantageEconomic JusticeVulnerability (computing)Norm (philosophy)Health carePsychologySocial psychologyLaw and economicsSociologyPublic relationsPolitical scienceLawComputer science

Abstract

fetched live from OpenAlex

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.

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.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.012
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.452
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0120.001
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0030.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.550
GPT teacher head0.532
Teacher spread0.018 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designTheoretical or conceptual
Domainnot available
GenreReview

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".

Quick stats

Citations14
Published2015
Admission routes2
Has abstractyes

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