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Record W3210462642 · doi:10.32920/ryerson.14654718.v1

Assessing the barriers regarding Canada's labour market policies and their impact on Caribbean immigrants in the skill-trade sector

2021· preprint· en· W3210462642 on OpenAlexaffabout
Shelleanne Hardial

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldSocial Sciences
TopicMigration and Labor Dynamics
Canadian institutionsToronto Metropolitan University
Fundersnot available
KeywordsImmigrationImmigration policyFace (sociological concept)Political scienceLabour economicsBusinessEconomic growthEconomicsSociology

Abstract

fetched live from OpenAlex

Many racialized immigrants, particularly Caribbean immigrants, leave their countries in hope of attaining a better life in Canada. In addition, skilled immigrants are lured to Canada by an aggressive immigration policy which promotes the notion that there is potential for immigrants to improve their lives and succeed as well rounded citizens who contribute to the Canadian society (Teelucksingh and Galabuzi, 2005). However, when many racialized immigrants try to enter the Canadian labour market, they face various challenges which sometimes continue after finding employment. This study will address the concerns relating to the barriers that Canadian labour market policies can present in the labour market, and the ways in which some Caribbean immigrants understand the policies, and experience its impact through systemic barriers. With the use of interviews by key informants from the Caribbean community, this paper seeks to explore the ways in which some racialized immigrants are acutely affected by Canada’s labour market policies.

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)0.002
metaresearch head score (Gemma)0.007
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: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.062
Threshold uncertainty score0.448

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0190.004
Scholarly communication0.0050.001
Open science0.0010.004
Research integrity0.0010.002
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 head0.014
GPT teacher head0.306
Teacher spread0.292 · 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
Published2021
Admission routes2
Has abstractyes

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