MétaCan
Menu
Back to cohort
Record W2130536036 · doi:10.1177/0964663907073446

In the Shadow of Canada’s Camps

2007· article· en· W2130536036 on OpenAlexaffabout
Martin French

Bibliographic record

VenueSocial & Legal Studies · 2007
Typearticle
Languageen
FieldSocial Sciences
TopicTorture, Ethics, and Law
Canadian institutionsQueen's University
Fundersnot available
KeywordsShadow (psychology)State (computer science)National securityPoliticsState of exceptionPolitical scienceLegislationPolitical economyGovernment (linguistics)DemocracySpectacleConvergence (economics)LawPublic administrationSociologyEconomicsEconomic growth

Abstract

fetched live from OpenAlex

States engaged in the war on terror have pursued war-time domestic security policies, as reflected by special anti-terror legislation enacted, for instance, in Canada, the United States, and the United Kingdom. Taking Canada as a case study, this article argues that the pursuit of these policies exacerbates existent racial fissures in the social body. Using elements of Giorgio Agamben’s theory of the state of exception as an analytical framework, this article interprets empirical interview and survey data, as well as the Canadian government’s national security policy. It highlights some of the surveillance methods used by Canadian security forces and concludes that the convergence of these methods with the spectacle of extraordinary detention evinces a shift towards totalitarianism. For some, it is not the conditions of parliamentary democracy that constitute the backdrop of political life, but the conditions of the detention camp.

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)0.009
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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.145
Threshold uncertainty score0.991

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.009
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0340.020
Scholarly communication0.0100.003
Open science0.0020.004
Research integrity0.0030.007
Insufficient payload (model declined to judge)0.0120.001

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 head0.061
GPT teacher head0.390
Teacher spread0.329 · 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

Citations29
Published2007
Admission routes2
Has abstractyes

Explore more

Same venueSocial & Legal StudiesSame topicTorture, Ethics, and LawFrench-language works237,207