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Record W7084096098 · doi:10.4000/14l3u

Derrida à Montréal

2019· book· fr· W7084096098 on OpenAlexaboutno aff

Bibliographic record

VenuePresses de l’Université de Montréal eBooks · 2019
Typebook
Languagefr
FieldEconomics, Econometrics and Finance
TopicEconomic, Social, and Health Studies
Canadian institutionsnot available
Fundersnot available
KeywordsSubject (documents)Context (archaeology)Identity (music)Perspective (graphical)Point (geometry)Relation (database)

Abstract

fetched live from OpenAlex

Derrida à Montréal n’est pas le titre d’une pièce de théâtre, mais celui d’un essai qui suit, en trois actes, trois événements singuliers qui ont eu lieu à Montréal et auxquels Jacques Derrida a participé en 1971, en 1979 et en 1997. Au « Premier Acte », Michael Naas relit de près la première communication du philosophe, « Signature événement contexte », un texte qui prend très au sérieux – et les critique tout à la fois – la théorie des speech acts de John L. Austin et les questions du contexte, de la présence, de l’écriture, de l’événement et de la signature qui lui sont liées. Au « Deuxième Acte », on retrouve Derrida traitant de ces mêmes questions, mais d’un point de vue politique où il s’intéresse aux « Déclarations d’Indépendance ». Enfin, au « Troisième Acte », Derrida poursuit cette discussion ininterrompue qui se concentre, une fois de plus, sur ces mêmes aspects, mais à la lumière de la notion d’événement. C’est comme si Montréal avait chaque fois été la scène rêvée où Derrida avait pu explorer ces questions pour lui cruciales.

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)0.002
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: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.654
Threshold uncertainty score0.785

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0080.003
Scholarly communication0.0050.002
Open science0.0010.003
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.2350.044

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 head0.018
GPT teacher head0.184
Teacher spread0.167 · 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
Published2019
Admission routes1
Has abstractyes

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