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Record W3125579414

Precarious Pathways: Evaluating the Provincial Nominee Programs in Canada

2010· article· en· W3125579414 on OpenAlexaboutno aff
Jamie Baxter

Bibliographic record

VenueeYLS (Yale Law School) · 2010
Typearticle
Languageen
FieldHealth Professions
TopicEmployment and Welfare Studies
Canadian institutionsnot available
Fundersnot available
KeywordsGovernment (linguistics)Career PathwaysBusinessEconomic growthPolitical sciencePublic administrationEconomicsOperations management
DOInot available

Abstract

fetched live from OpenAlex

Temporary foreign workers in Canada experience substandard employment relationships, are explicitly denied many formal rights and are practically excluded from most employment protections. Led by a growing emphasis on workers’ temporary status as a root cause of their employment-related vulnerabilities, some advocates, as well as elected officials, are now calling on governments to improve opportunities for workers to attain permanent residency in Canada, primarily for those in lower-skilled occupations. The central aim of this paper is to evaluate whether Provincial Nominee Programs are likely to address the real insecurities faced by vulnerable lower-skilled temporary foreign workers. Given that there are multiple potential pathways that could be designed for temporary workers to make the transition to permanent residency, a basic assumption of this study is that different paths are likely to lead to substantially different outcomes for workers, as well as for employers and communities. In all cases, these diverging outcomes should be assessed in terms of their overall efficacy at confronting individual workers’ current insecurities and in terms of their long-term effects on governments’ abilities to coordinate pathways between provincial jurisdictions and with the federal government.

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)0.019
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.130
Threshold uncertainty score0.940

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0080.019
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.004
Science and technology studies0.0100.003
Scholarly communication0.0030.002
Open science0.0030.003
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0030.000

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 head0.067
GPT teacher head0.346
Teacher spread0.280 · 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 designObservational
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

Citations2
Published2010
Admission routes1
Has abstractyes

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