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Record W2794107314 · doi:10.1017/s0008423917001482

Contextualizing the Crisis: The Framing of Syrian Refugees in Canadian Print Media

2018· article· en· W2794107314 on OpenAlexaffabout
Rebecca Wallace

Bibliographic record

VenueCanadian Journal of Political Science · 2018
Typearticle
Languageen
FieldSocial Sciences
TopicTerrorism, Counterterrorism, and Political Violence
Canadian institutionsQueen's University
Fundersnot available
KeywordsFraming (construction)RefugeeDepictionSyrian refugeesRefugee crisisPolitical scienceMedia studiesPrint mediaNews mediaNewspaperSociologyGeographyLawArtLiterature

Abstract

fetched live from OpenAlex

Abstract This project examines the framing of the Syrian refugee crisis in Canadian print media from January 1, 2012, to December 31, 2016, in eight English-language major dailies. Using automated coding to uncover central themes in the coverage, this analysis explores the changes in news frames over the course of the conflict and the concomitant federal election in Canada, as well as across regional and national news sources. The results indicate that the conflict frame dominates the coverage of Syrian refugees in the pre-election period but shifts markedly following the release of the iconic Alan Kurdi photo toward a more humanizing depiction of refugee families and their resettlement. This analysis speaks to the importance of news media in reflecting and reproducing depictions of refugees among the Canadian public, highlighting the value of examining changes in the portrayals of refugees over time and across news outlets.

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)0.003
metaresearch head score (Gemma)0.011
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 score0.045
Threshold uncertainty score0.322

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.011
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0120.011
Science and technology studies0.0140.008
Scholarly communication0.0110.003
Open science0.0010.004
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0080.000

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 head0.027
GPT teacher head0.335
Teacher spread0.308 · 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

Citations89
Published2018
Admission routes2
Has abstractyes

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Same venueCanadian Journal of Political ScienceSame topicTerrorism, Counterterrorism, and Political ViolenceFrench-language works237,207