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Record W3137938654 · doi:10.3138/tric.41.1.88

Citizen in Exception: Omar Khadr and the Performative Gap in the Law

2020· article· en· W3137938654 on OpenAlexvenueaboutno aff
Matt Jones

Bibliographic record

VenueTheatre Research in Canada · 2020
Typearticle
Languageen
FieldSocial Sciences
TopicTorture, Ethics, and Law
Canadian institutionsnot available
Fundersnot available
KeywordsLawPerformative utterancePerformativityBelligerentSociologyImprisonmentPolitical scienceMunicipal lawState of exceptionPoliticsTribunalState (computer science)Stateless protocolCommon lawPhilosophyGender studies

Abstract

fetched live from OpenAlex

In May 2015, former Guantanamo Bay detainee Omar Khadr was released from the Bowden Institution in Alberta. Khadr’s return to society followed 14 years of incarceration for an act that he may not have committed, which may not have been a crime, which took place while he was technically a child, and which was judged by a military tribunal that has questionable status in Canadian law. This article argues that Khadr’s long imprisonment was a political decision by US and Canadian authorities that required them to use performativity to suspend the law, depriving Khadr of his rights under American law, the Canadian Charter, and various protocols of international law. This use of performance to undermine law exposes a performative gap in the law: a space in the law that allows it to be moved and shaped by performative acts. Through these acts, Khadr became effectively stateless for a period in time: a citizen-in-exception. Building from Giorgio Agamben’s theory of the state of exception, this paper draws out the role played by performativity in the suspension of law by law. Importantly, the process that led to Khadr’s situation was racially charged from beginning to end. His situation is one manifestation of the way that Muslims have been “cast out” of Western law, as Sherene Razack puts it, since 9/11.

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)0.007
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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: none
Teacher disagreement score0.893
Threshold uncertainty score0.505

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0070.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.199
GPT teacher head0.396
Teacher spread0.196 · 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
Published2020
Admission routes2
Has abstractyes

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