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Record W2594620988 · doi:10.22329/wyaj.v33i2.4845

WHO IS MY NEIGHBOUR? THE DUTY OF CARE IN THE IMMIGRATION CONTEXT: A PERSPECTIVE FROM CANADIAN CASE LAW

2017· article· en· W2594620988 on OpenAlexaffvenueabout
Sasha Baglay

Bibliographic record

VenueWindsor Yearbook of Access to Justice · 2017
Typearticle
Languageen
FieldSocial Sciences
TopicEuropean Criminal Justice and Data Protection
Canadian institutionsOntario Tech University
Fundersnot available
KeywordsTortDuty of careImmigrationDutyLawContext (archaeology)Immigration lawPolitical scienceJurisprudencePerspective (graphical)NarrativeState (computer science)Power (physics)SociologyHistoryLiabilityPhilosophy

Abstract

fetched live from OpenAlex

This article reviews and analyzes recent Canadian jurisprudence on immigration-related torts, situating it in the context of the contrasting logic of immigration and tort law. Immigration law’s focus on the absolute power of the state to control admission directs courts away from the recognition of the duty of care. In contrast, tort law theory does not preclude the possibility of private law duties to non-citizens, especially in light of the absence of other effective remedies to address the power imbalance between the host state and the non-citizen. The article examines how these two narratives were negotiated in cases of alleged negligence in immigration processing. It problematizes certain aspects of the current construction of the duty of care towards non-citizens and offers some suggestions for a more nuanced understanding of the factors considered under the Anns/Cooper test.

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)0.008
metaresearch head score (Gemma)0.013
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 score0.215
Threshold uncertainty score0.910

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0080.013
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0040.007
Science and technology studies0.0590.060
Scholarly communication0.0170.007
Open science0.0050.008
Research integrity0.0110.010
Insufficient payload (model declined to judge)0.0040.000

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 head0.050
GPT teacher head0.357
Teacher spread0.307 · 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

Citations0
Published2017
Admission routes3
Has abstractyes

Explore more

Same venueWindsor Yearbook of Access to JusticeSame topicEuropean Criminal Justice and Data ProtectionFrench-language works237,207