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Record W4400424844 · doi:10.29173/crossings208

Protectors or Enforcers?

2024· article· en· W4400424844 on OpenAlexaffabout
Waniza Wasi

Bibliographic record

VenueCrossings An Undergraduate Arts Journal · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicGlobal Peace and Security Dynamics
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsChemistryPharmacologyBusinessMedicine

Abstract

fetched live from OpenAlex

This essay examines the complex relationship between contemporary law enforcement practices and Black, Indigenous, and racialized communities in Canada, focusing on hyper-masculine subcultures and militarized tactics. Using case studies, such as the death of Ejaz Chaudry and the criminalization of Wet'suwet'en land defenders, this paper analyzes the historical and colonial roots shaping policing practices. The study finds persistent over-policing and discriminatory practices on marginalized communities, emphasizing the urgent need for reform. Exploring the interplay of hyper-masculinity, militarization, and colonial biases, the essay discusses how symbols like the thin blue line contribute to an 'us versus them' mentality, reinforcing militaristic culture. The transnational dimensions of police militarization, influenced by historical and contemporary ties to settler-colonial practices, reveal how shared colonial legacies contribute to the perpetuation of militaristic approaches in law enforcement. Cases like Chaudry and Wet'suwet'en land defenders highlight the devastating consequences of militarized responses, urging comprehensive reforms. This essay acknowledges that while guardian approaches are more favorable in lieu of the outdated warrior mindset, the former community-oriented models still possess limitations. Despite this recognition, the essay contributes to the discourse on redefining policing practices, rebuilding community relations, and fostering a more just, equitable, and community-focused future in law enforcement.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies, Scholarly communication
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.716
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0030.001
Scholarly communication0.0060.001
Open science0.0000.000
Research integrity0.0000.000
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 head0.044
GPT teacher head0.374
Teacher spread0.330 · 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
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
Published2024
Admission routes2
Has abstractyes

Explore more

Same venueCrossings An Undergraduate Arts JournalSame topicGlobal Peace and Security DynamicsFrench-language works237,207