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Record W2165213075 · doi:10.7202/011063ar

Littéralement dépourvu de sens

2005· article· fr· W2165213075 on OpenAlexvenueno aff
Peter J. McCormick

Bibliographic record

VenuePhilosophiques · 2005
Typearticle
Languagefr
FieldArts and Humanities
TopicLinguistics and Discourse Analysis
Canadian institutionsnot available
Fundersnot available
KeywordsHumanitiesPhilosophy

Abstract

fetched live from OpenAlex

Dire précisément ce que signifient littéralement certaines expressions est souvent important. La compréhension satisfaisante de nombreuses expressions normatives en effet, qu’elles soient juridiques, morales, religieuses, poétiques ou autres, suppose de comprendre ce qu’elles signifient à la fois littéralement et non littéralement. Malgré des recherches pourtant sérieuses et durables sur la nature du « sens littéral », depuis les anciennes théories religieuses jusqu’aux théories linguistiques et philosophiques contemporaines, une explication généralement satisfaisante des significations supposées littérales des phrases normatives peut s’avérer étonnamment insaisissable. À partir des échanges serrés entre Donald Davidson, Michael Dummett et Ian Hacking, j’aborde un cas de compréhension du littéral dans un discours normatif artistiquement représenté qui est tout aussi difficile à éclaircir. À la différence de Davidson, toutefois, je ne me concentrerai pas sur les aspects qui sont les conditions de vérité des significations littérales supposées des contenus propositionnels de phrases bien assurées et présentées de manière littéraire. J’aimerais plutôt attirer une attention renouvelée sur plusieurs aspects problématiques des significations présumées littérales, spécialement dans des phrases interrogatives présentées sous un jour littéraire lors de conversations normatives lourdes d’un poids éthique.

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

Direct model labels (unvalidated)

Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.

Model armCategoriesStudy designConfidence
gemmano category
Domain: not available · Genre: Editorial
About the Canadian research system: no · About a Canadian topic: no
Not applicablelow
gptno category
Domain: not available · Genre: Commentary
About the Canadian research system: no · About a Canadian topic: no
Theoretical or conceptuallow
models splitAgreement compares identical category sets and study designs across arms.

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)0.002
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: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.019
Threshold uncertainty score0.064

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.009
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0030.009
Scholarly communication0.0060.009
Open science0.0010.004
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.0190.005

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 head0.213
GPT teacher head0.366
Teacher spread0.153 · 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

Labeled directly by 2 models reading the full record.

The models applied no category: nothing in the taxonomy fit this work.

The models disagree on parts of this classification; every voice is preserved in the section at the end of the page.

Study designNot applicable · Theoretical or conceptual
Domainnot available
GenreEditorial · Commentary

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
Published2005
Admission routes1
Has abstractyes

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