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Record W2809414005

"They don't have a platform here": Exploring police perceptions of the Black Lives Matter movement in Canada

2018· dissertation· en· W2809414005 on OpenAlexaboutno aff
Noor Sandhu

Bibliographic record

VenueSummit (Simon Fraser University) · 2018
Typedissertation
Languageen
FieldSocial Sciences
TopicPolicing Practices and Perceptions
Canadian institutionsnot available
Fundersnot available
KeywordsMovement (music)PerceptionPolitical scienceCriminologySociologyPsychologyArtAesthetics
DOInot available

Abstract

fetched live from OpenAlex

Recent high-profile lethal use of force incidents in the United States involving White police officers and Black males have cast unfavorable international attention on the policing profession. Research indicates that Black people are disproportionately represented at all levels of the criminal justice system within Canada and the United States; their relationship with the police in particular has been adverse throughout history (Warde, 2012; Kahn & Martin, 2016). The current qualitative analysis explored the thoughts, perceptions and experiences of municipal police officers in the GVR and examined the following research questions: (1) To what degree, if any, has the recent BLM movement affected municipal policing in the GVR? and; (2) What can municipal policing agencies in the Vancouver area do to distance themselves from the BLM movement and anti-police rhetoric that is occurring in many parts of the United States? The BLM movement is present in Canada, but the anti-police rhetoric currently spreading throughout the United States is not. Officers described a positive relationship with community members in the GVR further stating that interactions between themselves and the community have not changed since the emergence of the BLM movement. These findings indicate that the BLM movement is not a “one-size fits all” movement. The overall positive nature of community-police relations in this region exist regardless of the community’s exposure to an increase in controversial police behaviour.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.810
Threshold uncertainty score0.999

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 studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.036
GPT teacher head0.271
Teacher spread0.236 · 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 designObservational
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
Published2018
Admission routes1
Has abstractyes

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