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Record W2795726416 · doi:10.1111/imig.12450

Safe Country of Origin: Constructing the Irregularity of Asylum Seekers in Canada

2018· article· en· W2795726416 on OpenAlex
Idil Atak

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueInternational Migration · 2018
Typearticle
Languageen
FieldPsychology
TopicMigration, Health and Trauma
Canadian institutionsToronto Metropolitan University
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsRefugeePersecutionTortureUnintended consequencesPolitical scienceGovernment (linguistics)Comprehensive Plan of ActionTimelineAsylum seekerCriminologyLawHuman rightsPublic administrationSociologyGeographyPolitics

Abstract

fetched live from OpenAlex

Abstract This article discusses the role of Canada's Designated Country of Origin (DCO) policy in the illegalization of asylum seekers. The policy allows the government to designate countries in which it is presumed that citizens do not face risks of persecution, torture, or similar abuse. Refugee claimants from DCOs are thus subject to accelerated processing timelines with reduced rights. Canada has implemented the policy as a way to deal with a backlog of asylum applications, increase efficiency, and exclude fraudulent refugee claims. Based on a primary field research conducted between October 2015 and May 2017 in three provinces, Quebec, Ontario, and British Columbia, this article argues that the DCO policy is likely to have the unintended effect of shifting asylum seekers into an irregular status.

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.

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)0.000
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.125
Threshold uncertainty score0.688

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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)0.0010.000

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 head0.015
GPT teacher head0.303
Teacher spread0.288 · 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