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Record W3131361147 · doi:10.7202/1075126ar

L’agrégation, le programme : la chance de La vie la mort

2021· article· fr· W3131361147 on OpenAlexvenueno aff
Michael Naas

Bibliographic record

VenuePhilosophiques · 2021
Typearticle
Languagefr
FieldArts and Humanities
TopicHistorical Studies and Socio-cultural Analysis
Canadian institutionsnot available
Fundersnot available
KeywordsHumanitiesPhilosophy

Abstract

fetched live from OpenAlex

Cet essai porte sur le séminaire La vie la mort (1975-1976) et sur la notion double de « programme » qui l’informe. Dans ce séminaire, Derrida juxtapose en effet une lecture de la notion de « programme », utilisée par le biologiste français François Jacob dans sa description du fonctionnement de l’ADN, à une réflexion sur le « programme » d’agrégation en France qui avait cette année-là pour thème « Vie et mort ». Cet article commence donc par examiner le rôle crucial joué par l’examen d’agrégation dans la production, voire la reproduction, de la philosophie en tant que discipline en France. Il analyse ensuite la lecture de La logique du vivant que fait Derrida dans ce séminaire à partir de ces deux notions supposément distinctes de « programmes » : un programme soi-disant inflexible et partagé par tous les êtres vivants, celui de l’ADN, et un programme soi-disant plus libre et plus souple, celui de la culture et des institutions humaines comme celles de l’agrégation. En résulte une refonte complète des formes de production et de reproduction en jeu aussi bien du côté de notre compréhension de la génétique que de l’éducation.

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)0.003
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 score0.020
Threshold uncertainty score0.054

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0050.016
Scholarly communication0.0050.004
Open science0.0010.003
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0130.001

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 head0.103
GPT teacher head0.321
Teacher spread0.217 · 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 designNot applicable
Domainnot available
GenreOther

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
Published2021
Admission routes1
Has abstractyes

Explore more

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