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Record W1037176821

Human-Machinic Assemblages: Technologies, Bodies, and the Recuperation of Social Reproduction in the Crisis Era

2015· article· en· W1037176821 on OpenAlexaboutno aff
Elise Thorburn

Bibliographic record

VenueScholarship@Western (Western University) · 2015
Typearticle
Languageen
FieldArts and Humanities
TopicContemporary Literature and Criticism
Canadian institutionsnot available
Fundersnot available
KeywordsReproductionEnvironmental crisisPolitical scienceBusinessEconomyEnvironmental ethicsEconomicsBiologyEcology
DOInot available

Abstract

fetched live from OpenAlex

This dissertation argues that class composition, as defined and theorised by Operaismo and Autonomist thinkers, has had both a major and a minoritarian form. In fact class composition in its major form has always been subtended by a minor current. I examine both historical (the 1905 Russian Soviets, the 1919 Turin factory councils, the Italian social movements of the 1970s) and contemporary examples (the occupation of Tahrir Square in Egypt, the Indignados movement in Spain, and Occupy Wall Street in 2011, as well as the 2012 Quebec student strike) of class composition. From these examples I then argue that the minor current of class composition is rooted in social reproduction – both its crisis and its recuperation. And further that this minor current expands throughout history, growing to command greater attention within social and labour movements. Further, this dissertation argues that contemporary social movements appear today as an assemblage, a human-machinic assemblage, which enact social reproduction in crisis and recuperation through both embodied and technologized forms. I demonstrate the ways in which technologies of communication are implicated in forms of securitised and commodified social reproduction, but also open up new and powerful possibilities for autonomous and liberatory social reproduction. This dissertation relies on a merger of conceptual, theoretical, and field research and benefits from the author’s direct involvement in social and political struggles.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.416
Threshold uncertainty score0.473

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.131
GPT teacher head0.314
Teacher spread0.183 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
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
Published2015
Admission routes1
Has abstractyes

Explore more

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