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Record W2975596338

Policing Indigenous Movements: Dissent and the Security State

2018· book· en· W2975596338 on OpenAlexaboutno aff
Andrew Crosby

Bibliographic record

Venuenot available
Typebook
Languageen
FieldSocial Sciences
TopicGlobal Peace and Security Dynamics
Canadian institutionsnot available
Fundersnot available
KeywordsDissentIndigenousState (computer science)Political scienceCriminologyState securityComputer securitySociologyLawComputer sciencePolitics
DOInot available

Abstract

fetched live from OpenAlex

"The book blends discussions of settler colonialism, policing and surveillance, with a detailed exposé of current security practices that targets Indigenous movements. Using the Access to Information Act, the book offers a unique view into the extensive networks of policing and security agencies. While some light has been shed on the surveillance of social movements in Canada, the book shows how policing agencies have been cataloguing Indigenous land defenders and other opponents of extractive capitalism, while also demonstrating how the norms of settler colonialism structure the ways in which police regard Indigenous movements as national security threats. The book examines four prominent case studies: the long-standing conflict involving the Algonquins of Barriere Lake; the struggle against the Northern Gateway Pipeline; the Idle No More movement; and the anti-fracking protests surrounding the Elsipogtog First Nation. Through these case studies, we offer a vivid demonstration of how policing agencies and the criminal justice system are central actors in maintaining settler colonialism. The book raises critical questions regarding the expansion of the security apparatus, the normalization of police surveillance targeting social movements, the relationship between police and energy corporations, and threats to civil liberties and collective action in an era of extractive capitalism and hyper surveillance."...

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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.049
Threshold uncertainty score0.098

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0090.015
Scholarly communication0.0060.003
Open science0.0010.003
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0030.001

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 head0.006
GPT teacher head0.271
Teacher spread0.265 · 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

Citations37
Published2018
Admission routes1
Has abstractyes

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