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Record W2783093730 · doi:10.1386/eme.14.1-2.7_1

Megamachines: From Mumford to Guattari

2015· article· en· W2783093730 on OpenAlexaff
Gary Genosko

Bibliographic record

VenueExplorations in Media Ecology · 2015
Typearticle
Languageen
FieldArts and Humanities
TopicCybernetics and Technology in Society
Canadian institutionsOntario Tech University
Fundersnot available
KeywordsDeleuze and GuattariAssemblage (archaeology)HumanismSociologyUrbanismDimension (graph theory)AestheticsSubjectivityArchitectureEpistemologyPhilosophyArtHistoryArchaeologyVisual artsTheology

Abstract

fetched live from OpenAlex

Abstract This article builds a resource base for an understanding of philosopher and analyst Félix Guattari’s urbanism. By reviewing his deployments of Lewis Mumford’s concept of megamachines, and detailing his rejection of humanism and positive assessments of human–machine entanglements, I show that Guattari’s sense of the urban is defined as a machine that produces different kinds of subjectivities within an animistic assemblage of built structures. Further cross-references are pursued between Mumford’s criticisms of Marshall McLuhan and Teilhard de Chardin, and the fertile technological overlap between McLuhan and Gilles Deleuze’s views of the screen in film and television. Guattari’s brand of post-humanism includes a recoded Mumfordian megamachine as a form of machinic enslavement that integrates humans–machines while downplaying the social dimension of subjugation.

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: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.012
Threshold uncertainty score0.063

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0060.028
Scholarly communication0.0080.009
Open science0.0010.005
Research integrity0.0030.003
Insufficient payload (model declined to judge)0.0110.001

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 head0.092
GPT teacher head0.268
Teacher spread0.176 · 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 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

Citations24
Published2015
Admission routes1
Has abstractyes

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