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Record W2040783895 · doi:10.1017/s0260210511000271

Highways, heroes, and secular martyrs: the symbolics of power and sacrifice

2011· article· en· W2040783895 on OpenAlexaboutno aff
Tina Managhan

Bibliographic record

VenueReview of International Studies · 2011
Typearticle
Languageen
FieldSocial Sciences
TopicGender, Security, and Conflict
Canadian institutionsnot available
Fundersnot available
KeywordsThe ImaginaryPoliticsRepatriationSacrificeState (computer science)TorturePower (physics)SociologyLiberalismLawDemiseAestheticsGender studiesPolitical scienceHistoryArtPsychoanalysisHuman rights

Abstract

fetched live from OpenAlex

Abstract This article examines the subtle and not so subtle shifts in Canadian political culture that have taken place in, through and alongside the so-called ‘return’ of the Canadian warrior. It begins from the contention that while the racialised dimensions of the post 9/11 Canadian security state have been well analysed elsewhere, the gendered dimensions have not been fully explored. This article explores the re-emergence of a sacrificial imaginary in Canadian culture through an examination of seemingly irreconcilable accounts that have emerged of the Canadian security state – one that reads ‘Canada’ through the story of the torture and repatriation of Canadian citizen, Maher Arar, and one that tells the story of ‘Canada at War’ through the warrior's return. It examines both in terms of the tensions and instabilities they reveal in the Western liberal imaginary and in terms of the ways in which they collectively operate to redefine the aesthetic borders of the Canadian political community. The article argues that the sacralisation of violence which has refound this political community has been enabled by a remasculinised aesthetic that delimits the ‘progressive liberalism’ which animated the Canada of Old – ostensibly in order to protect it.

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)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.768
Threshold uncertainty score0.466

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.003
Science and technology studies0.0100.041
Scholarly communication0.0080.002
Open science0.0010.002
Research integrity0.0010.001
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 head0.072
GPT teacher head0.348
Teacher spread0.276 · 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 designTheoretical or conceptual
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

Citations27
Published2011
Admission routes1
Has abstractyes

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