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Record W4385466146 · doi:10.1177/26326663231188203

Decolonizing prisons: Indigenized programming and a critique of critical prison studies

2023· article· en· W4385466146 on OpenAlexafffundabout
Justin Everett Cobain Tetrault

Bibliographic record

VenueIncarceration · 2023
Typearticle
Languageen
FieldSocial Sciences
TopicCriminal Justice and Corrections Analysis
Canadian institutionsUniversity of Alberta
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsIndigenousGenocidePrisonSociologyColonialismPremiseSpiritualityCriminologyPolitical scienceLawEpistemologyMedicine

Abstract

fetched live from OpenAlex

Critical prison studies (CPS) is increasingly influential in scholarly discussions about decolonizing prisons. Proponents of CPS largely oppose the idea that cultural prison programs are decolonial, which include courses teaching Indigenous cultures and colonial history, prisons facilitating spirituality, involving Elders and communities in rehabilitation, and specialized prisons called "healing lodges." Most CPS scholars writing on the topic disparage these initiatives as assimilationist and thus a weapon of cultural genocide. For these scholars, decolonizing prisons is impossible. CPS arguments against Indigenized programming are premised on abolitionist theory rather than a discernible decolonial method centring the perspectives of Indigenous peoples affected by prisons. I explore the accuracy and utility of CPS scholars' arguments against Indigenized programming, drawing from 587 interviews with incarcerated men and women detained inside six prisons across Western Canada. Almost 40% of these participants identified as Indigenous. Indigenous interviewees nearly universally praised Indigenized programs for how they can help heal and empower those affected by colonial violence. Participants desired more cultural programming and easier access to such resources. More research is needed on how prisons develop and implement cultural programming, but existing empirical works suggest that these initiatives, while flawed, support the dignity of incarcerated Indigenous peoples. My critique is a call for criminologists writing on Indigenous issues to consider the ambiguity and tensions of decolonial processes and to premise their arguments foremost on methods centring Indigenous peoples affected by incarceration.

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)0.002
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 score0.520
Threshold uncertainty score0.423

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
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 head0.069
GPT teacher head0.434
Teacher spread0.365 · 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

Citations5
Published2023
Admission routes3
Has abstractyes

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