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Record W2328366581 · doi:10.1177/1462474516641375

Genocidal carcerality and Indian residential schools in Canada

2016· article· en· W2328366581 on OpenAlexaffabout
Andrew Woolford, James Gacek

Bibliographic record

VenuePunishment & Society · 2016
Typearticle
Languageen
FieldSocial Sciences
TopicCambodian History and Society
Canadian institutionsUniversity of Manitoba
Fundersnot available
KeywordsGenocideTypologyColonialismCriminologyContext (archaeology)SociologyGeographyGender studiesPolitical scienceSocial scienceAnthropologyLawArchaeology

Abstract

fetched live from OpenAlex

This paper contributes to the criminology of genocide through examination of settler colonial destruction within the broader context of what we term ‘genocidal carcerality’. We employ this term to examine the ways in which space is implicated in the physical, biological, and cultural destruction of group life. In this paper, our purpose is not to create a typology of genocidal carcerality, but rather to demonstrate the multiplicity of spatial strategies at work within any genocidal context, with specific focus on Indian Residential Schools. In so doing, we critique attempts to reduce genocidal carcerality to a single spatial form, such as the camp. We illustrate our main points through a case study of the Fort Alexander Indian Residential School in Manitoba, Canada.

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: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.077
Threshold uncertainty score0.562

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.004
Science and technology studies0.0270.012
Scholarly communication0.0040.001
Open science0.0020.006
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0040.000

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 head0.012
GPT teacher head0.240
Teacher spread0.229 · 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

Citations50
Published2016
Admission routes2
Has abstractyes

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