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Record W3107181791 · doi:10.3389/fhumd.2020.588961

Never Letting a Good Crisis Go to Waste: Canadian Interdiction of Asylum Seekers

2020· article· en· W3107181791 on OpenAlexafffundabout
Sean Rehaag, Janet Song, Alexander Toope

Bibliographic record

VenueFrontiers in Human Dynamics · 2020
Typearticle
Languageen
FieldSocial Sciences
TopicCanadian Policy and Governance
Canadian institutionsYork University
FundersSocial Sciences and Humanities Research Council of CanadaYork University
KeywordsRefugeeInterdictionPolitical scienceGovernment (linguistics)Comprehensive Plan of ActionPoliticsLawEngineering

Abstract

fetched live from OpenAlex

This article examines two moments of crisis at Canada’s border with the United States: the aftermath of September 11th, 2001 and the COVID-19 pandemic. The Canadian government leveraged both crises to offshore responsibilities for refugees onto the US. In the first case, Canada took advantage of US preoccupations with border security shortly after 9/11 to persuade the US to sign the Canada-US Safe Third Country Agreement (“STCA") – an agreement that allows Canada to direct back asylum seekers who present themselves at ports-of-entry on the Canada-US border. In the second case, Canada used heightened anxieties about international travel during the COVID-19 pandemic to persuade the US to block irregular border crossings that asylum seekers were increasingly using to circumvent the STCA. After reviewing Canada’s successful use of these moments of crisis to persuade the US to take on additional responsibilities for refugees for whom Canada would have otherwise been responsible, the article discusses a recent Canadian Federal Court decision that may make all this political maneuvering moot. This decision found that Canada cannot send asylum seekers back to the US without violating constitutional rights to life, liberty, and security of the person. Given past practice, however, we can expect the Canadian government to continue to pursue avenues to persuade the US to take on additional responsibility for refugees – and moments of crisis will be important drivers for those efforts.

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)0.000
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: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.254
Threshold uncertainty score0.515

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.010
GPT teacher head0.251
Teacher spread0.242 · 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 designNot applicable
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

Citations3
Published2020
Admission routes3
Has abstractyes

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