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Record W3107534473 · doi:10.1111/phpr.12751

Natural goodness without natural history

2020· article· en· W3107534473 on OpenAlexaff
Parisa Moosavi

Bibliographic record

VenuePhilosophy and Phenomenological Research · 2020
Typearticle
Languageen
FieldNeuroscience
TopicPsychology of Moral and Emotional Judgment
Canadian institutionsYork University
Fundersnot available
KeywordsNatural (archaeology)EpistemologyGoodness of fitNaturalismPhilosophyMathematicsStatistics

Abstract

fetched live from OpenAlex

Abstract Neo‐Aristotelian ethical naturalism purports to show that moral evaluation of human action and character is an of evaluation of natural goodness —a kind of evaluation that applies to living things in virtue of their nature and based on their form of life. The standard neo‐Aristotelian view defines natural goodness by way of generic statements describing the natural history , or the ‘characteristic’ life, of a species. In this paper, I argue that this conception of natural goodness commits the neo‐Aristotelian view to a problematic anti‐individualism that results in the wrong assessment of individuals with uniquely adaptive adjustments. I then offer an alternative account of natural goodness that avoids this problem. Instead of relying on generic statements about a species, my account defines natural goodness based on counterfactual conditionals describing the modal properties of a single individual. I argue that this modal‐explanatory account gives a conception of natural goodness that is more intuitively plausible and better suited to capture the diversity and plasticity distinctive of life.

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)0.001
Version: codex-gemma-dda1882f352aValidation 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: Empirical
Teacher disagreement score0.440
Threshold uncertainty score0.492

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
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 integrity0.0000.001
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 head0.549
GPT teacher head0.384
Teacher spread0.165 · 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.

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

Citations18
Published2020
Admission routes1
Has abstractyes

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