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Record W2793043356 · doi:10.1111/phin.12200

Reading and Character: Weil and McDowell on Naïve Realism and Second Nature

2018· article· en· W2793043356 on OpenAlexaff
Warren Heiti

Bibliographic record

VenuePhilosophical Investigations · 2018
Typearticle
Languageen
FieldArts and Humanities
TopicPhilosophy and Literary Analysis
Canadian institutionsVancouver Island University
Fundersnot available
KeywordsAnalogyDualismCharacter (mathematics)RealismPhilosophyReading (process)Action (physics)Meaning (existential)EpistemologyValue (mathematics)LinguisticsPhysicsMathematicsQuantum mechanicsGeometry

Abstract

fetched live from OpenAlex

Abstract Both Simone Weil and John McDowell analogize value or meaning to sensations such as colour or heat, and this analogy is a strategy for resisting anti‐realism. However, McDowell's analogy tacitly accepts the very dualism which he is criticizing, while Weil's analogy is both more naïve and more radical than his. Like McDowell, Weil argues that virtuous character is the actualization of a second nature, but she emphasizes the role of the body in this process. Fully trained, the agent's body is a transparent medium through which she reads circumstances – and through which the circumstances, clearly perceived, express themselves in action.

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)0.015
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.009
Threshold uncertainty score0.048

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.015
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0030.001
Science and technology studies0.0060.059
Scholarly communication0.0090.011
Open science0.0010.004
Research integrity0.0060.007
Insufficient payload (model declined to judge)0.0050.000

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 head0.033
GPT teacher head0.247
Teacher spread0.214 · 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 designNot applicable
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
Published2018
Admission routes1
Has abstractyes

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