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Record W2498501348 · doi:10.1017/ccol0521631785.007

The Theory of Descriptions

2003· book-chapter· en· W2498501348 on OpenAlexaff
Peter Hylton

Bibliographic record

VenueCambridge University Press eBooks · 2003
Typebook-chapter
Languageen
FieldPsychology
TopicPhilosophy and Theoretical Science
Canadian institutionsMcMaster University
Fundersnot available
KeywordsQuinePhilosophyEpistemologyCriticismAnalytic philosophyPhenomenonContemporary philosophyLiteratureArt

Abstract

fetched live from OpenAlex

Russell's theory of descriptions was first published in his 1905 essay, “On Denoting”, which is surely one of the two or three most famous articles in twentieth-century analytic philosophy. It has been described as “a paradigm of philosophy”, and has been employed by many later analytic philosophers, such as Quine, although disputed by others, perhaps most notably Strawson. Writing in 1967, an astute commentator said: “In the forty-five years preceding the publication of Strawson's 'On Referring', Russell's theory was practically immune from criticism. There is not a similar phenomenon in contemporary analytic philosophy”. What is the theory which has excited such interest and acclaim? To put it briefly and more or less neutrally, it is a method of analyzing definite descriptions , also called singular descriptions , i.e., phrases, in English typically beginning with the word “the”, which pick out or purport to pick out a single (“definite”) object – e.g., “the man who broke the bank at Monte Carlo”, or “the first President of the USA”. Many philosophers who have accepted the theory of definite descriptions, including Russell himself, have also treated some or all proper names in similar fashion. They are taken to be disguised definite descriptions, and then subjected to the same analysis as overt definite descriptions. Definite descriptions may be contrasted with indefinite descriptions, which do not purport to pick out any particular number of objects – e.g., “any President of the USA”. Note that while the two phrases “the even prime number” and “any even prime number” in fact direct our attention to the same object – the number two – the first is a definite description, while the second is an indefinite description.

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)0.003
metaresearch head score (Gemma)0.005
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 score0.011
Threshold uncertainty score0.041

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.005
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.003
Science and technology studies0.0030.027
Scholarly communication0.0110.017
Open science0.0030.004
Research integrity0.0030.004
Insufficient payload (model declined to judge)0.0100.004

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 head0.040
GPT teacher head0.229
Teacher spread0.189 · 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

Citations10
Published2003
Admission routes1
Has abstractyes

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