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Record W4388846187 · doi:10.4324/9780429020858-15

Indigenous Identity and Correctional Programming

2023· book-chapter· en· W4388846187 on OpenAlexaboutno aff
Stephanie Wellman

Bibliographic record

Venuenot available
Typebook-chapter
Languageen
FieldSocial Sciences
TopicCriminal Justice and Corrections Analysis
Canadian institutionsnot available
Fundersnot available
KeywordsIndigenousIdentity (music)SociologyCriminologyArtEcologyBiologyAesthetics

Abstract

fetched live from OpenAlex

This chapter, which emerged from Wellman’s graduate research in criminology, focuses on how Indigenous men and women continue to fight against Canada’s colonization while incarcerated within the Canadian prison system. The chapter details how Indigenous people are routinely denied access to culture and spirituality within prisons and the role that Indigenous-specific prison programming attempts to play in addressing this. It also raises questions as to whether the prison itself is set up to further disconnect Indigenous people from being Indigenous and fostering the erasure of Indigenous identity from the Canadian settler state, ultimately continuing the “civilizing” project. Through her interviews with a number of former prisoners, Wellman argues that while the Correctional Service of Canada has developed several “Indigenous-specific” programs in federal institutions, access to them is always tenuous, and most proffer a “pan”-Indigenous perspective to culture and traditions not specific to a prisoner’s nation. While Stephanie argues that such programming represents a furthering of the colonial project, at the same time the men interviewed for the study maintained an affirmation of their Indigeneity while inside prison.

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)0.000
metaresearch head score (Gemma)0.001
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 score0.315
Threshold uncertainty score0.627

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0100.008
Scholarly communication0.0030.002
Open science0.0010.002
Research integrity0.0000.001
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 head0.053
GPT teacher head0.332
Teacher spread0.279 · 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

Citations0
Published2023
Admission routes1
Has abstractyes

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