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Record W3102499308 · doi:10.1080/1369183x.2020.1841613

Examining the ‘National Risk Assessment for Detention’ process: an intersectional analysis of detaining ‘dangerousness’ in Canada

2020· article· en· W3102499308 on OpenAlexaffabout
Stephanie J. Silverman, Esra Kaytaz

Bibliographic record

VenueJournal of Ethnic and Migration Studies · 2020
Typearticle
Languageen
FieldSocial Sciences
TopicMigration, Refugees, and Integration
Canadian institutionsYork University
Fundersnot available
KeywordsImmigration detentionPrisonImmigrationContext (archaeology)Agency (philosophy)Political scienceCriminologyNational securityLawPsychologySociologyGeography

Abstract

fetched live from OpenAlex

Canada Border Services Agency (CBSA) officers use the National Risk Assessment for Detention (NRAD) process to evaluate the ‘riskiness’ of immigration detainees. The NRAD’s key tool is a 2-page document laying out ‘risk factors’ with corresponding points that add up to scores of ‘dangerousness’ allegedly posed by non-citizens. CBSA officers then recommend detention in either a provincial prison or a lower security ‘immigration holding centre’. In a national context of no legislated upper time limits on detention periods, and where telephonic and other access to incarceration sites is impeded, the NRAD form’s outcome portends serious, long-term consequences.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.913
Threshold uncertainty score0.961

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.159
GPT teacher head0.422
Teacher spread0.263 · 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 designObservational
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

Citations8
Published2020
Admission routes2
Has abstractyes

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