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Record W2139179511 · doi:10.29173/irie313

Occupy the Heterotopia

2012· article· en· W2139179511 on OpenAlexvenueno aff
James K. Anderson, Kiran Bharthapudi, Hao Cao

Bibliographic record

VenueThe International Review of Information Ethics · 2012
Typearticle
Languageen
FieldSocial Sciences
TopicSpatial and Cultural Studies
Canadian institutionsnot available
Fundersnot available
KeywordsHeterotopia (medicine)SociologyConsciousnessCapitalismAutonomyDemocracyCollective unconsciousPosthumanUtopiaNeoliberalism (international relations)EpistemologyPolitical economyPolitical sciencePhilosophyPsychoanalysisLawPoliticsPsychology

Abstract

fetched live from OpenAlex

In this essay, Foucault's concept “of other spaces” – or, heterotopia – is used to examine the Occupy Wall Street (OWS) movement in the context of systemic crisis. Neoliberalism is marked by innovations that amplify and accelerate contradictions, unfolding the false utopia of finance capitalism. Information and communication technologies (ICTs) helped hyper-financialize the economy, enrich banksters and extend inequalities. Conversely, high-tech developments allow for decentralized decision-making and more direct democracy, paralleling the ethics of OWS. New ICTs compress TimeSpace, opening doors for empathic connections, generating conditions for elevation of collective superstructural consciousness. This paper explores how these conditions create – and are recreated by – heterotopic spaces. Drawing on Foucault's method of heterotopology we throw light on the potential of OWS to prefigure another world, analyzing endeavors to promote cooperative autonomy, and raise consciousness in and through mediated environments, always contested, ever in flux, and inevitably over-(but never pre-)determined.

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)0.004
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 score0.008
Threshold uncertainty score0.026

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0060.052
Scholarly communication0.0080.010
Open science0.0010.007
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0080.001

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 head0.087
GPT teacher head0.407
Teacher spread0.321 · 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

Citations2
Published2012
Admission routes1
Has abstractyes

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