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Record W2768391327 · doi:10.1111/anti.12370

Autoconstruction 2.0: Social Media Contestations of Racialized Violence in Complexo do Alemão

2017· article· en· W2768391327 on OpenAlexaff
Carolyn Prouse

Bibliographic record

VenueAntipode · 2017
Typearticle
Languageen
FieldSocial Sciences
TopicAnthropological Studies and Insights
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsCriminalizationSocial mediaSociologyDigital mediaWitnessState (computer science)CriminologyMedia studiesPolitical scienceGender studiesLaw

Abstract

fetched live from OpenAlex

Abstract Activists and journalists in Complexo do Alemão, Rio de Janeiro are using social media to intervene in the violence that shapes their communities. In this article I draw on critical urban and digital media theory to understand how militarized policing, the spatialization of race, and discourses of criminalization influence favela populations. I examine how these discursive and material violences are motivating residents to autoconstruct new digital communities. Through digital autoconstruction, journalists and activists are using social media technologies to safely direct mobility, to witness police violence, and to unsettle socio‐spatial imaginaries of endemic crime. As such, they are deploying digital practices to disrupt material, epistemological, and discursive mechanisms of social control. These actions show that digital technologies are always‐already embodied and take shape through material histories, such as those of racialized state violence. Journalists and activists in Complexo do Alemão ultimately demonstrate that targets of violence are not simply victims of digital and violent surveillance, but are active in creating new digital relationships of care across diverse scales, transforming these technologies in the process.

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)0.000
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.819
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0020.002
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.085
GPT teacher head0.398
Teacher spread0.314 · 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.

Study designObservational
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

Citations14
Published2017
Admission routes1
Has abstractyes

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