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Record W4385156407

Any Sum of Parts which are Water is Water

2011· article· en· W4385156407 on OpenAlexaff
Henry Laycock

Bibliographic record

VenuePhilPapers (PhilPapers Foundation) · 2011
Typearticle
Languageen
FieldPsychology
TopicPhilosophy and Theoretical Science
Canadian institutionsQueen's University
Fundersnot available
KeywordsEnvironmental science
DOInot available

Abstract

fetched live from OpenAlex

Mereological entities often seem to violate 'ordinary' ideas of what a concrete object can be like, behaving more like sets than like Aristotelian substances.However, the mereological notions of 'part', 'composition', and 'sum' or 'fusion' appear to find concrete realisation in the actual semantics of mass nouns.Quine notes that 'any sum of parts which are water is water'; and the wine from a single barrel can be distributed around the globe without affecting its identity.Is there here, as some have claimed, a 'natural' or 'innocent' form of mereology?The claim rests on the assumption that what a mass noun such as 'wine' denotes -the wine from a single barrel , for example -is indeed a unit of a special type, the sum or fusion of its many 'parts'.The assumption is, however, open to question on semantic grounds.I. Innocence, guilt, and the utterance of Quine 1.0 Mereology.Mereologists posit a variety of contentious principles of composition, whereby diverse objects -wholes, 'fusions' or 'sums', analogous to sets but without a membership relation -may be constructed on the basis of specified ranges of objects, abstract or concrete, assigned the roles of 'parts', parthood in this context being akin to set-theoretical inclusion.The question of whether, in any particular axiomatized system, the definitions can be somehow plausibly mapped into any natural-language understandings of 'object', 'whole' and 'part' is a further question, as is the question of whether there ('really') are objects, recognisable independently of the mereological system, which actually satisfy its axioms.Naturally, the mereologist is free to deny that her favoured system is contentious; she may urge that fusions of the kind contrived

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)0.001
metaresearch head score (Gemma)0.001
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 score0.008
Threshold uncertainty score0.026

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0030.013
Scholarly communication0.0030.009
Open science0.0010.003
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0080.001

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 head0.046
GPT teacher head0.276
Teacher spread0.230 · 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
Published2011
Admission routes1
Has abstractyes

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