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Record W2071692372 · doi:10.1017/s0031819109000394

Human Nature, Personhood, and Ethical Naturalism

2009· article· en· W2071692372 on OpenAlexaff
John Hacker‐Wright

Bibliographic record

VenuePhilosophy · 2009
Typearticle
Languageen
FieldArts and Humanities
TopicPhilosophical Ethics and Theory
Canadian institutionsUniversity of Guelph
Fundersnot available
KeywordsPersonhoodDeliberationEpistemologyCreaturesValue (mathematics)NaturalismRationalityArgument (complex analysis)PhilosophyNorm (philosophy)SociologyEnvironmental ethicsLawComputer science

Abstract

fetched live from OpenAlex

Abstract John McDowell has argued that for human needs to matter in practical deliberation, we must have already acquired the full range of character traits that are imparted by an ethical upbringing. Since our upbringings can diverge considerably, his argument makes trouble for any Aristotelian ethical naturalism that wants to support a single set of moral virtues. I argue here that there is a story to be told about the normal course of human life according to which it is no coincidence that there is agreement on the virtues. Because we are creatures who arrive at personhood only by learning from others in a relation of dependency, we cannot help but see ourselves as creatures for whom non-instrumental rationality is the norm. Those who train others in personhood must view the trainee's interests as having a value independent of their interests and must imbue the trainee with a sense of that value. Extending and preserving the sense of self-worth that we must acquire if we are to acquire personhood requires we see ourselves as creatures who need something like the virtues.

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)0.006
metaresearch head score (Gemma)0.004
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 score0.006
Threshold uncertainty score0.030

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0040.044
Scholarly communication0.0050.004
Open science0.0010.003
Research integrity0.0030.003
Insufficient payload (model declined to judge)0.0030.000

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 head0.036
GPT teacher head0.288
Teacher spread0.251 · 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

Citations67
Published2009
Admission routes1
Has abstractyes

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