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Colonial Processes, Indigenous Peoples, and Criminal Justice Systems

2013· book· en· W1954558448 on OpenAlexaboutno aff
Chris Cunneen

Bibliographic record

VenueOxford University Press eBooks · 2013
Typebook
Languageen
FieldSocial Sciences
TopicIndigenous Health, Education, and Rights
Canadian institutionsnot available
Fundersnot available
KeywordsIndigenousCriminal justiceCriminologyColonialismPolitical sciencePoliticsEconomic JusticePopulationTheory of criminal justiceRepresentation (politics)Corporate governanceLawSociology

Abstract

fetched live from OpenAlex

Colonial processes, indigenous people, and criminal justice systems interact. There are commonalities in the experiences of Indigenous peoples in the white settler societies of Australia, Canada, New Zealand, and the United States. Understanding of the over-representation of Indigenous people in crime and victimization statistics needs to be contextualized within the broader framework of the effects of colonization. These effects include long-term social and economic marginalization, and limited recognition of indigenous law and governance. Current criminal justice processes (including risk assessment) continue to single out indigenous peoples as a “crime-prone” population. Indigenous demands for greater recognition of Aboriginal law and greater control over criminal justice decision-making must be taken seriously. Neo-liberalism and “law and order” politics are likely further to entrench the over-representation of indigenous peoples within western criminal justice systems.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.982
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0080.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.000
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 head0.020
GPT teacher head0.245
Teacher spread0.225 · 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
GenreOther

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

Citations30
Published2013
Admission routes1
Has abstractyes

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