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Record W2898856648 · doi:10.26556/jesp.v14i1.370

Immigrant Selection, Health Requirements, and Disability Discrimination

2018· article· en· W2898856648 on OpenAlexaboutno aff
Douglas MacKay

Bibliographic record

VenueJournal of Ethics and Social Philosophy · 2018
Typearticle
Languageen
FieldSocial Sciences
TopicPolitical Philosophy and Ethics
Canadian institutionsnot available
Fundersnot available
KeywordsImmigrationIdentity (music)Law and economicsPolitical sciencePsychologyLawBusinessActuarial scienceMedicineSociology

Abstract

fetched live from OpenAlex

Australia, Canada, and New Zealand currently apply health requirements to prospective immigrants, denying residency to those with health conditions that are likely to impose an “excessive demand” on their publicly funded health and social service programs. In this paper, I investigate the charge that such policies are wrongfully discriminatory against persons with disabilities. I first provide a freedom-based account of the wrongness of discrimination according to which discrimination is wrong when and because it involves disadvantaging people in the exercise of their freedom on the basis of morally arbitrary features of their identity. Discrimination is permissible, I suggest, when it is necessary to advance a valuable exercise of the discriminating agent’s freedom. I then apply this account to the case of social cost health requirements. Against critics of these requirements, I argue that it is sometimes permissible for states to discriminate against prospective immigrants with disabilities. States may do so, I suggest, when such discriminatory treatment is necessary to prevent an increase in rates of mortality and/or morbidity among citizens. Alongside critics of social cost health requirements however, I argue that existing policies are likely a form of wrongful discrimination insofar as they are too broad to satisfy this standard.

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)0.006
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.825
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0060.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0030.003
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.160
GPT teacher head0.429
Teacher spread0.270 · 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.

Study designTheoretical or conceptual
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

Citations7
Published2018
Admission routes1
Has abstractyes

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