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Record W2758535329 · doi:10.1080/10282580.2017.1377057

Resisting ‘progressive’ carceral expansion: lessons for abolitionists from anti-colonial resistance

2017· article· en· W2758535329 on OpenAlexaffabout
Bronwyn Dobchuk-Land

Bibliographic record

VenueContemporary Justice Review · 2017
Typearticle
Languageen
FieldSocial Sciences
TopicCriminal Justice and Corrections Analysis
Canadian institutionsUniversity of Winnipeg
Fundersnot available
KeywordsIndigenousColonialismCorporate governanceResistance (ecology)Government (linguistics)Community policingCrime preventionKinshipPoliticsCriminologyPolitical sciencePublic administrationSociologyLawBusiness

Abstract

fetched live from OpenAlex

This article documents a government-led strategy to more closely integrate policing with community-based ‘crime prevention’ programming in the city of Winnipeg, Manitoba, Canada. These initiatives have targeted neighborhoods with large Indigenous populations. In this article I illustrate how community-level conflicts over responses to ‘crime’ are also sites of settler colonial conflict, and how settler colonial governance is reproduced and resisted through the governance of crime. Interviews with politicians, policy-makers, bureaucrats in the crime prevention branch of the provincial government, and directors and employees at community-based organizations suggest that the pursuit of the government strategy of integrated crime prevention and suppression has been more a project of attempting to ‘manage’ urban Indigenous people than serve their interests. As a contribution to abolitionist thought and theory, this article profiles sites of conflict between community police and community-based organizations over definitions of the ‘crime’ problem in city-center Winnipeg. These examples highlight a kinship between carceral abolitionist and decolonial politics.

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)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.897
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0070.000
Scholarly communication0.0000.001
Open science0.0010.000
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 head0.131
GPT teacher head0.430
Teacher spread0.299 · 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 designNot applicable
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

Citations21
Published2017
Admission routes2
Has abstractyes

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