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Record W2612433860

A Remark on Attitudes De Dicto and De Se

2017· article· es· W2612433860 on OpenAlexvenueno aff
Shuguo Tang

Bibliographic record

VenueAporia · 2017
Typearticle
Languagees
FieldSocial Sciences
TopicPolitical Philosophy and Ethics
Canadian institutionsnot available
Fundersnot available
KeywordsFocus (optics)EpistemologyConstruct (python library)Object (grammar)Order (exchange)PhilosophySociologyComputer scienceLinguistics
DOInot available

Abstract

fetched live from OpenAlex

This is a two-fold response to the theory of attitudes presented by David Lewis in his paper A ttitudes De Dicto and De Se . Lewis’ theory is on the specification of attitudes. On the one hand, it is obvious in his text that Lewis attempts to specify the objects of attitudes uniformly. I will argue that the attempt fails. The reason is that from Lewis’ formulation of an attitude, we cannot read the object of it. On the other hand, Lewis’ account could have been a theory on the specification of attitudes without any commitment on what the objects of attitudes are. I will argue that this does not hold either. In order to do that, I will construct pairs of cases in which the attitude in one case has the same formulization as in the other case according to Lewis’ theory. I will argue that in one such pair of cases, the focus of the attitude in one case can be different from that in the other, while the Lewisian theory of attitudes does not help to specify an attitude’s focus .

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)0.005
metaresearch head score (Gemma)0.009
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 score0.016
Threshold uncertainty score0.053

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.009
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0040.012
Scholarly communication0.0030.008
Open science0.0010.003
Research integrity0.0030.008
Insufficient payload (model declined to judge)0.0160.003

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 head0.086
GPT teacher head0.420
Teacher spread0.334 · 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
Published2017
Admission routes1
Has abstractyes

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