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Record W3043551908

Racialized victims of police violence and Canadian media : racial victim blaming and absolving the police

2019· article· en· W3043551908 on OpenAlexaboutno aff
Matthew Bruce Allain

Bibliographic record

VenueSaint Mary's University Institutional Repository (Saint Mary's University) · 2019
Typearticle
Languageen
FieldSocial Sciences
TopicPolicing Practices and Perceptions
Canadian institutionsnot available
Fundersnot available
KeywordsCriminologyPolice brutalityRacial profilingPolitical scienceRace (biology)SociologyLawGender studies
DOInot available

Abstract

fetched live from OpenAlex

The purpose of this thesis was to determine whether Canadian news media relied on racist tropes and stereotypes of black people in their portrayal of black men who had died as the result of police violence.Additionally, the thesis wanted to identify the different uses of language that news media uses to absolve the institution of policing.For this thesis, news media articles published by Canadian outlets that pertained to Canadian cases of black men dying because of direct police violence or death exasperated by police violence had their content analyzed.The articles were made up from regional and national outlets and they were themed and coded to identify specific uses of phrases and words that speak to premature or unfounded absolving of the police and victim blaming with overt racist tropes and stereotypes.What the methods found was that Canadian media often includes irrelevant information pertaining to the victim that is used to implicitly blame the victim for their fate.The thesis also found that specific language tactics were used by these articles to reduce the violence done by the police officers and to remove the officer from the ordeal entirely.This thesis wants to contribute to the literature on the media portrayals of racial minorities and the ways in which implicit racist practices are embedded in societal institutions.The thesis also wanted to shed light on racism and discrimination within Canada that may not be apparent in contemporary society.

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
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.620
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0030.002
Scholarly communication0.0000.001
Open science0.0010.000
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 head0.011
GPT teacher head0.226
Teacher spread0.215 · 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
Published2019
Admission routes1
Has abstractyes

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