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Record W2567441380 · doi:10.1111/hith.10827

FOUCAULT'S ICONIC AFTERLIFE: THE POSTHUMOUS REACH OF WORDS AND THINGS

2016· article· en· W2567441380 on OpenAlexaff
Nancy Partner

Bibliographic record

VenueHistory and Theory · 2016
Typearticle
Languageen
FieldSocial Sciences
TopicFoucault, Power, and Ethics
Canadian institutionsMcGill University
Fundersnot available
KeywordsAfterlifeMichel foucaultIconicityTRACE (psycholinguistics)Power (physics)Meaning (existential)PhilosophyNounForegroundingLiteratureEpistemologyAestheticsSociologyArtLinguisticsPoliticsLaw

Abstract

fetched live from OpenAlex

ABSTRACT The lasting influence of Michel Foucault's work is both instantly recognizable in that his very name can be invoked as a noun or adjective (“Foucauldian”), as a critical stance or attitude without further elaboration, and yet his signature concepts have been flattened, stretched, exaggerated, and thinned as they have been applied by his most enthusiastic followers. Although Foucault has entered the canon of philosophers, he also became iconic, most notably with the typographic icon, power/knowledge, a (possibly unwanted) achievement of recognition and compression virtually unknown to other philosophers. In this essay, I consider the Foucault of the philosophical canon, and I trace some of the main routes of the iconic Foucault into acceptance or nonacceptance by the academic disciplines, notably history and anthropology, and numerous other unexpected venues where variants of Foucault's ideas have found surprising homes. I also contemplate the meaning of the status of “iconicity” as it has been analyzed by sociologists, and the possibility that iconic misreadings of Foucault's concepts have been extraordinarily “good to think with” by his critics.

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)0.010
metaresearch head score (Gemma)0.023
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.990
Threshold uncertainty score0.065

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0100.023
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0100.077
Scholarly communication0.0080.009
Open science0.0010.005
Research integrity0.0030.008
Insufficient payload (model declined to judge)0.0030.001

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 head0.018
GPT teacher head0.256
Teacher spread0.238 · 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.

Study designTheoretical or conceptual
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

Citations3
Published2016
Admission routes1
Has abstractyes

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