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Record W4236243580 · doi:10.3138/utlj.60.2.315

FREEING MIGRATION FROM THE STATE: MICHAEL TREBILCOCK ON MIGRATION POLICY

2010· article· en· W4236243580 on OpenAlexaffvenueabout
Audrey Macklin

Bibliographic record

VenueUniversity of Toronto Law Journal · 2010
Typearticle
Languageen
FieldSocial Sciences
TopicCanadian Policy and Governance
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsImmigrationImmigration policyOpposition (politics)CitizenshipDemocracyImmigration lawPoliticsPolitical sciencePolitical economyState (computer science)EconomicsLaw

Abstract

fetched live from OpenAlex

Michael Trebilcock's The Law and Economics of Immigration Policy sets out a broad prescriptive model for migration policy. It is informed by a classically liberal endorsement of free movement of labour, a commitment to efficiency, and a preference for market over state regulation. Trebilcock claims that his policy proposal will significantly liberalize immigration in prosperous liberal democratic states and be politically palatable. The key lies in pre-empting the objection that increased levels of immigration will impose or exacerbate the negative fiscal impact of immigrants on receiving states. Trebilcock would privatize selection by delegating it entirely to the market (employers) or the family (relatives), and institute a mandatory private insurance scheme payable by sponsors to insure against the risk that an immigrant will impose fiscal burdens on the state in the period leading up to eligibility for citizenship. While applauding the objective animating this proposal, the author relies partly on Ninette Kelley and Michael Trebilcock's historical account in The Making of the Mosaic: A History of Canadian Immigration Policy to challenge its viability. First, the author suggests that Trebilcock's claim that his model is politically pragmatic is predicated on a contestable understanding of the nature of political opposition to immigration. Second, it is not obvious that Trebilcock's model, on its own terms, would actually liberalize immigration across the range of states where he would seek to implement it. The author concludes by reflecting on the capacity of broadly conceived, transnational policy prescriptions to grapple with the complexity of migration as a global phenomenon, the specificity of national contexts, and the limits on state actors' ability to socially engineer the character of present and future generations through immigrant selection. Where the vast majority of immigrants are admitted on the basis of ascriptive kinship criteria, family matters – and will continue to matter – in the future direction of immigration.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.772
Threshold uncertainty score0.811

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 studies0.0010.000
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 head0.008
GPT teacher head0.230
Teacher spread0.222 · 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

Citations13
Published2010
Admission routes3
Has abstractyes

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