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Record W1984944895 · doi:10.7202/030613ar

La patine et la connivence

2005· article· fr· W1984944895 on OpenAlexvenueno aff
Jacques Fontanille

Bibliographic record

VenueProtée · 2005
Typearticle
Languagefr
FieldComputer Science
TopicCultural Insights and Digital Impacts
Canadian institutionsnot available
Fundersnot available
KeywordsHumanitiesArtPhilosophy

Abstract

fetched live from OpenAlex

La patine est tout d’abord affaire de temps, et en cela elle procure à l’objet une surface (sémiotique) d’inscription pour les « empreintes » d’un ensemble d’usages (les énonciations antérieures et successives des objets). Elle participe donc d’une mémoire figurative des objets, car, tout comme le discours verbal le fait avec la langue, l’énonciation des objets les modifie, et inscrit ces modifications dans leur structure même, qui en garde mémoire. En outre, cette mémoire, en ancrant les objets dans une sorte de tradition matérielle, celle de la longue chaîne des énonciations successives, projette des systèmes de valeur qui motivent leur co-existence : la mémoire inscrite dans la patine de chacun d’eux, devient alors leur mémoire collective, première étape de l’interobjectivité. Mais, pour pouvoir parler d’« interobjectivité », il faut d’abord pouvoir parler d’« objets », c’est-à-dire d’« actants ». Et on s’aperçoit alors que la patine, en dotant les « choses » soumises aux temps et aux usages d’une « enveloppe » chargée de valeurs et de mémoire, les convertit d’abord en actants compétents. Cette « compétence » n’est pas seulement de type sémantique (les valeurs incarnées dans la matière par les usages), elle est aussi modale, en ce sens que la patine et l’usure, tout comme l’ergonomie, induisent des contraintes et des lignes de tendance, des formes qui modalisent l’usager et infléchissent l’usage.

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)0.002
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: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.016
Threshold uncertainty score0.052

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.005
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0070.043
Scholarly communication0.0140.009
Open science0.0010.008
Research integrity0.0030.005
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 head0.219
GPT teacher head0.353
Teacher spread0.135 · 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 designQualitative
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

Citations13
Published2005
Admission routes1
Has abstractyes

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