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Record W2774515141 · doi:10.11157/sites-vol14iss1id345

Carceral Recognition and the Colonial Present at the Okimaw Ohci Healing Lodge

2017· article· en· W2774515141 on OpenAlexafffundabout
Margaret Rose Boyce

Bibliographic record

VenueSites a journal of social anthropology and cultural studies · 2017
Typearticle
Languageen
FieldSocial Sciences
TopicIndigenous Health, Education, and Rights
Canadian institutionsMcMaster University
FundersSocial Sciences and Humanities Research Council of CanadaMcMaster University
KeywordsPrisonIndigenousColonialismState (computer science)PoliticsCriminologyMandatePolitical scienceImprisonmentLawSociologyEcology

Abstract

fetched live from OpenAlex

Glen Coulthard’s 2014 book, Red Skin, White Masks is a much needed critique of the Canadian state’s increasing use of colonial recognition politics. I suggest that Coulthard’s approach is also well-attuned to interrogate current forms of prison reform in Canada. At stake is the possibility that unchecked recognition-based policies in Correctional Service of Canada’s (CSC) mandate – such as the utilization of ‘traditional healing’ in penal programming and the construction of prisons designed solely for Indigenous inmates –undermine the needs of Indigenous people in prison, while propagating settler colonialism through the often invisible mechanisms of the prison system. By analyzing the Okimaw Ohci Healing Lodge federal prison for Indigenous women, in Maple Creek, Saskatchewan, I posit the emergence of a carceral recognition politics in Canadian prisons: a strategy whereby the penal system parades its willingness to accommodate Indigenous difference in order to reconcile Indigenous peoples with the authority of the State – often through the implementation of colonial teleologies towards a supposedly non-colonial present – while simultaneously developing a durable and comprehensive prison system for the more effective incarceration of federally sentenced Indigenous women.

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: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.936
Threshold uncertainty score0.403

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0310.038
Scholarly communication0.0090.003
Open science0.0010.005
Research integrity0.0020.005
Insufficient payload (model declined to judge)0.0050.000

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 head0.072
GPT teacher head0.403
Teacher spread0.331 · 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 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

Citations2
Published2017
Admission routes3
Has abstractyes

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