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Record W3217762930 · doi:10.22230/cjc.2021v46n4a3807

The Representation of Syrian Refugees in Canadian Online News Media: A Focus on the Topos of Burdening

2021· article· en· W3217762930 on OpenAlexvenueaboutno aff
Manar Mustafa, Zahariah Pilus, Maskanah Mohammad Lotfie

Bibliographic record

VenueCanadian Journal of Communication · 2021
Typearticle
Languageen
FieldComputer Science
TopicHate Speech and Cyberbullying Detection
Canadian institutionsnot available
Fundersnot available
KeywordsTopos theoryRepresentation (politics)DepictionRefugeeSyrian refugeesNews mediaFocus (optics)Political sciencePublic discourseSociologyMedia studiesLinguisticsLawArtLiteraturePhilosophy

Abstract

fetched live from OpenAlex

Background: This study focuses on the representation of Syrian refugees in Canadian online news media. It examines 375 articles selected from three of the most visited Canadian news sites, namely the Toronto Star, which favours the Liberal Party, and the Toronto Sun and National Post, which favour the Conservative Party. Analysis: The basis of this research is a topoi analysis, whereby instances of the topos of burdening are identified, examined, and categorized as either positive or negative. Conclusion and implications: A distinction is drawn between the depiction of Syrian refugees in conservative- and liberal-leaning news sources. The findings aim to provide some insight into the possible impact of media representation on both the Syrian refugees and the Canadian public.

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)0.007
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 score0.154
Threshold uncertainty score0.311

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0100.010
Science and technology studies0.0090.004
Scholarly communication0.0070.001
Open science0.0010.003
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0050.000

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 head0.021
GPT teacher head0.265
Teacher spread0.243 · 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

Citations4
Published2021
Admission routes2
Has abstractyes

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Same venueCanadian Journal of CommunicationSame topicHate Speech and Cyberbullying DetectionFrench-language works237,207