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Record W2411706576

Iterated Modalities, Meaning and A Priori Knowledge

2011· article· en· W2411706576 on OpenAlexfundno aff
Dominic Gregory

Bibliographic record

VenueWhite Rose Research Online (University of Leeds, The University of Sheffield, University of York) · 2011
Typearticle
Languageen
FieldPsychology
TopicPhilosophy and Theoretical Science
Canadian institutionsnot available
FundersUniversity of OxfordYork UniversityPrinceton University
KeywordsModalitiesModal logicIterated functionModality (human–computer interaction)MetaphysicsEpistemologyMeaning (existential)A priori and a posterioriRange (aeronautics)Computer scienceModalPhilosophyMathematicsArtificial intelligenceSociologySocial science
DOInot available

Abstract

fetched live from OpenAlex

IHere are some well-known principles featuring iterated modalities: 1 (B) If Φ, then necessarily possibly Φ.(4) If necessarily Φ, then necessarily necessarily Φ.(5) If possibly Φ, then necessarily possibly Φ.The Kneales report that C.I. Lewis, the founder of modern modal logic, was inclined to deny that each instance of the above principles holds, 2 while Bennett remarks that their universal generalisations "have an unusually irritating quality, in that there appear to be at first sight powerful reasons for rejecting [them], and at the same time equally powerful ones for rejecting their contradictories".3 Prior notes that "many people would find [the view that (5) always obtains] very dubious", although he is tempted to accept the universal forms of (B), (4), and (5), because modal logics without formal analogues of those principles are "clumsy".4 More recently, Armstrong once denied that (B) and ( 5) always hold, 5 while we will see below that Chandler and Salmon have force-Imprint Philosophers' dominic gregory

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)0.014
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 score0.033

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.014
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0020.021
Scholarly communication0.0040.017
Open science0.0020.004
Research integrity0.0020.004
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 head0.120
GPT teacher head0.296
Teacher spread0.176 · 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

Citations3
Published2011
Admission routes1
Has abstractyes

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