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Record W2747223129 · doi:10.1080/18902138.2017.1368277

National (in)security and the shifting affective fields of terror in the case of Omar Khadr

2017· article· en· W2747223129 on OpenAlexaffabout
Natalie Kouri-Towe

Bibliographic record

VenueNORMA · 2017
Typearticle
Languageen
FieldSocial Sciences
TopicMigration, Refugees, and Integration
Canadian institutionsConcordia University
Fundersnot available
KeywordsTerrorismInnocenceFraming (construction)CriminologyRacializationNational securityPrisonMasculinityRepatriationLawPolitical scienceSociologyGender studiesHistoryPolitics

Abstract

fetched live from OpenAlex

Omar Khadr, the Canadian teen accused of war crimes in Afghanistan in 2002, was the only minor held in Guantanamo Bay until his repatriation to Canada in 2012. Throughout his 13 years in U.S. detention and Canadian prison, Khadr remained a highly debated and contentious figure in the Canadian public, depicted as both a victim and villain through the circulation of his dual image as an adolescent boy alongside his photograph as a bearded adult. Although evidence was never presented to the Canadian public that Khadr was a threat to Canada’s national security, his treatment by the federal government and his framing in Canadian news media depicted Khadr as a terrorist. Looking at the relationship between the circulation of Khadr’s dual image and representations of him as a victim/villain, this paper argues that discourses of national security, the construction of dangerous masculinity in the racialization of Arabs and Muslims, and the affects of fear and anxiety circulating in the perceived threat of terror and terrorism shaped a contradictory representation of Khadr as a terrorist threat to the nation, and conversely, as a victim whose innocence relied on his status as a child.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.603
Threshold uncertainty score0.982

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.020
GPT teacher head0.340
Teacher spread0.320 · 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.

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

Citations1
Published2017
Admission routes2
Has abstractyes

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