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Record W2913155314 · doi:10.1177/1464884919825503

Intersecting violence: Representations of Somali youth in the Canadian press

2019· article· en· W2913155314 on OpenAlexaffabout
Yasmin Jiwani, Ahmed Al‐Rawi

Bibliographic record

VenueJournalism · 2019
Typearticle
Languageen
FieldSocial Sciences
TopicJewish and Middle Eastern Studies
Canadian institutionsSimon Fraser UniversityConcordia University
Fundersnot available
KeywordsSomaliRadicalizationImmigrationCriminologyGender studiesNarrativeRepresentation (politics)TerrorismSociologyPolitical scienceHistoryLawArtPoliticsLiterature

Abstract

fetched live from OpenAlex

This article examines the press coverage accorded to Canadian youth of Somali origin in the Canadian press using two methodological procedures. Charting the representational clusters that cohere around Canadian Black male youth of Somali heritage reveals the circulation of stereotypical tropes that are mostly circumscribed within the framework of crime, terrorism, and violence, reflecting the intersection of stereotypes commonly ascribed to Muslims and to Black males. In the case of the Canadian Somali youth, this representation encompasses major narratives such as ‘radicalization and terror’, ‘immigration and belonging’, ‘surveillance and safety’, and ‘gang violence’ and, to a lesser extent, positive stories. To corroborate the first level of analysis, the computational analyses reveal four main topics and associations that are similar to the above findings, providing insight into the way Canadian Somali youth, especially men, are facing different challenges in their lived experiences in Canada.

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)0.002
metaresearch head score (Gemma)0.005
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: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.076
Threshold uncertainty score0.551

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.005
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0060.012
Science and technology studies0.0240.011
Scholarly communication0.0110.002
Open science0.0020.005
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0060.000

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 head0.048
GPT teacher head0.325
Teacher spread0.277 · 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

Citations15
Published2019
Admission routes2
Has abstractyes

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