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Record W2593376131 · doi:10.1111/cag.12361

Disabled people, medical inadmissibility, and the differential politics of immigration

2017· article· en· W2593376131 on OpenAlexaffvenueabout
Robert Wilton, Stine Thestrup Hansen, Edward Hall

Bibliographic record

VenueCanadian Geographies / Géographies canadiennes · 2017
Typearticle
Languageen
FieldSocial Sciences
TopicMigration, Identity, and Health
Canadian institutionsMcMaster University
Fundersnot available
KeywordsImmigrationPoliticsStatutory lawConstruct (python library)Reading (process)Differential (mechanical device)Disabled peopleKey (lock)Political scienceLawPublic relationsPublic administrationMedicineComputer scienceComputer securityEnvironmental healthEngineering

Abstract

fetched live from OpenAlex

Key Messages Medical inadmissibility provisions in Canada's immigration law exclude some disabled applicants on the basis that they would place “excessive demand” on health and social services. These statutory provisions construct disabled persons as burdensome, with little acknowledgment of the potential contributions such applicants might make to Canada. Recent legal cases have contested this narrow reading of disability, but have yet to challenge the underlying assumptions of the provision.

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)0.004
metaresearch head score (Gemma)0.008
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 score0.079
Threshold uncertainty score0.447

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.008
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0280.042
Scholarly communication0.0110.002
Open science0.0010.006
Research integrity0.0060.007
Insufficient payload (model declined to judge)0.0090.000

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 head0.011
GPT teacher head0.263
Teacher spread0.251 · 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

Citations10
Published2017
Admission routes3
Has abstractyes

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