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Record W4313043996 · doi:10.51952/9781447321781.fm001

Front Matter

2016· paratext· en· W4313043996 on OpenAlexaboutno aff
Chris Cunneen, Juan Tauri

Bibliographic record

VenuePolicy Press eBooks · 2016
Typeparatext
Languageen
FieldSocial Sciences
TopicIndigenous Health, Education, and Rights
Canadian institutionsnot available
Fundersnot available
KeywordsFront (military)PhysicsComputer scienceMeteorology

Abstract

fetched live from OpenAlex

Indigenous Criminology is the first book to explore a distinctly Indigenous approach to criminology. It is based on comparative research across the settler colonial states of Aotearoa New Zealand, Australia, Canada and the United States. The book draws on critical Indigenous and decolonial literature to argue for the importance of prioritising Indigenous knowledge in understanding contemporary Indigenous over-representation in the criminal justice system. Indigenous Criminology sets out the significance of colonialism as a key foundational concept to developing a critical Indigenous criminology. It analyses how colonialism impacts on the current operations of criminal justice. The book explores a number of explicit issues including the policing, sentencing and punishment of Indigenous people. It considers the impact of crime control specifically on Indigenous women and discusses the effects on Indigenous people of globalisation and crime control. The book concludes with a reflection on critical issues in the development of an Indigenous criminology, including the need to take seriously the voices of Indigenous peoples and the rights embedded in the United Nations Declaration on the Rights of Indigenous Peoples.

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 categoriesScience and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.391
Threshold uncertainty score0.998

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 studies0.0030.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0070.060

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 head0.035
GPT teacher head0.355
Teacher spread0.320 · 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; both teacher heads agree on what is shown here.

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

Citations0
Published2016
Admission routes1
Has abstractyes

Explore more

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