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Class Acts

2021· book· en· W4285350626 on OpenAlexaboutno aff
Michael Naas

Bibliographic record

VenueFordham University Press eBooks · 2021
Typebook
Languageen
FieldArts and Humanities
TopicPhilosophy, Ethics, and Existentialism
Canadian institutionsnot available
Fundersnot available
KeywordsClass (philosophy)Meaning (existential)Event (particle physics)SociologyPhilosophyEpistemology

Abstract

fetched live from OpenAlex

Class Acts looks at two often neglected aspects of Jacques Derrida’s work as a philosopher, namely, his public presentations and his teaching, along with the question of the “speech act” that links them, that is, the question of what one is doing when one speaks in public in these ways. The work is divided into two parts, each of which follows Derrida’s itinerary with regard to speech act theory from the 1970s through the 1990s. Part I, titled “Derrida in Montreal,” analyzes Derrida’s critique of John Austin and his own subsequent redefinition of speech act theory over the course of three public lectures or events (in 1971, 1979, and 1997), all three, for reasons I try to identify and explain, in Montreal. Part II. “The Open Seminar,” begins with an overview of Derrida’s teaching career and his famous “seminar” presentations, along with his own explicit reflections on pedagogy and educational institutions beginning in the mid-1970s. It then turns to the way Derrida interrogated and himself redeployed speech act theory in three recently published seminars (on life-death, theory and practice, and forgiveness). We ultimately come to see through this juxtaposition that, whether he was in a conference hall or a classroom, Derrida was always interested in the way in which spoken or written words might not just communicate some meaning or intent but give rise to something like an event. This is a book about the possibility of such events in Derrida’s work as a pedagogue and public intellectual.

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)0.010
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 score0.255
Threshold uncertainty score0.000

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.010
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0060.004
Scholarly communication0.0090.005
Open science0.0020.005
Research integrity0.0030.003
Insufficient payload (model declined to judge)0.2550.106

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 head0.076
GPT teacher head0.221
Teacher spread0.144 · 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

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