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Record W3033342401 · doi:10.1017/s1358246119000250

Virtues as Perfections of Human Powers: On the Metaphysics of Goodness in Aristotelian Naturalism

2020· article· en· W3033342401 on OpenAlexaff
John Hacker‐Wright

Bibliographic record

VenueRoyal Institute of Philosophy Supplement · 2020
Typearticle
Languageen
FieldArts and Humanities
TopicPhilosophical Ethics and Theory
Canadian institutionsUniversity of Guelph
Fundersnot available
KeywordsNaturalismMetaphysicsEssentialismEpistemologyPhilosophyWonderNatural (archaeology)

Abstract

fetched live from OpenAlex

Abstract The central idea of Philippa Foot’s Natural Goodness is that moral judgments belong to the same logical kind of judgments as those that attribute natural goodness and defect to plants and animals. But moral judgments focus on a subset of human powers that play a special role in our lives as rational animals, namely, reason, will, and desire. These powers play a central role in properly human actions: those actions in which we go for something that we see and understand as good. Many readers of Foot resolutely ignore what she says about the human good being sui generis and obstinately continue to read her as advocating a version of naturalism grounded in empirical study of human nature. One might wonder how else it could count as a naturalistic view unless we could square the view with nature as studied by the empirical sciences. In this paper, I propose a metaphysical response to this question: help can come from turning to recent defenses of Aristotelian essentialism. Foot’s naturalism can square with nature as interpreted through the lens of Aristotelian essentialism. On such a view, the virtues are perfections of human powers including reason, will, and desire.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.379
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.076
GPT teacher head0.281
Teacher spread0.206 · 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
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

Citations10
Published2020
Admission routes1
Has abstractyes

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