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Record W4414240829 · doi:10.22329/cjpp.v5i1.8192

Healthy enough? A capability approach to sufficiency and equality

2023· article· en· W4414240829 on OpenAlexaff
Jay Drydyk

Bibliographic record

VenueCanadian Journal of Practical Philosophy · 2023
Typearticle
Languageen
FieldSocial Sciences
TopicSocial Policy and Reform Studies
Canadian institutionsCarleton University
Fundersnot available
KeywordsNothingEgalitarianismCapability approachImperfectPoliticsDiversity (politics)Economic JusticeDomain (mathematical analysis)

Abstract

fetched live from OpenAlex

Sufficiency’ approaches to social and global justice stress that everyone must have enough. According to some advocates of this approach, only sufficiency is important, not equality. Martha Nussbaum, who is often classified as a sufficiency advocate, has defied this stricture against egalitarianism by contending that, in several domains, nothing is adequate short of equality. She cites political freedoms as her most persuasive example and suggests that the same may be true of the capability for health care. However, she does not explore this idea in depth: the idea that, in the domain of health, nothing short of equal capabilities is adequate. I explore this by clarifying the main concepts, such as adequacy and capability, in the domain of health. By these means I address three further questions. First, which is primary and which is derivative: capability for health care or capability for health? Second, does duration matter? If we can understand adequate health at a moment, in terms of ranges of physiological and psychological functioning, does adequacy not also imply durability? If so, then, third, is it possible to specify the length of an adequately healthy life, at least as a reasonable expectation? I argue that, due to human diversity and the imperfect state of medical knowledge, we cannot form a reasonable expectation of the length of an adequately healthy life for each person. Nevertheless, duration still matters. Therefore, we must recognize inadequately healthy lives in the only way that we can, by recognizing social disparities in health outcomes. In this sense, nothing short of equality is adequate.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.007
metaresearch head score (Gemma)0.008
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.008
Threshold uncertainty score0.037

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.008
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0040.045
Scholarly communication0.0080.014
Open science0.0010.008
Research integrity0.0040.006
Insufficient payload (model declined to judge)0.0060.001

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.

Opus teacher head0.170
GPT teacher head0.417
Teacher spread0.247 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
Domainnot available
GenreEmpirical

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

Citations0
Published2023
Admission routes1
Has abstractyes

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