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Record W2935784162 · doi:10.51357/cs.v14i1.123

Newcomer Women's Experience of Immigration and Precarious Work in Toronto

2018· article· en· W2935784162 on OpenAlexaffabout
Leslie Nichols

Bibliographic record

VenueCritical Studies An International and Interdisciplinary Journal · 2018
Typearticle
Languageen
FieldHealth Professions
TopicEmployment and Welfare Studies
Canadian institutionsWilfrid Laurier University
Fundersnot available
KeywordsImmigrationUnit (ring theory)Immigration policyWork (physics)Unpaid workDemographic economicsPolitical scienceEconomic growthSociologyGender studiesPsychologyEconomicsLaw

Abstract

fetched live from OpenAlex

Canada's immigration policy encourages immigrants with education and job skills. They are awarded points for specific skills and admitted in the economic class. This system is held up as a model of a modern immigration policy, but it incorporates misogynistic norms that give male applicants a strong economic advantage over women. The policy divides applicants into primary applicants and dependents. Only the skills of the primary applicant, usually the husband in a family unit, are assessed. Thus women's potential economic contribution is not considered. This study of 30 newcomer women in Toronto found that they remained in low-paid precarious work, were vulnerable to workplace exploitation, sacrificed their careers to support their husbands, suffered economic and health repercussions, and had difficulty getting better work due to unpaid household labor and lack of social supports. This paper shows the connection between the marginalization of these women and Canadian immigration policy

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)0.001
metaresearch head score (Gemma)0.002
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 score0.043
Threshold uncertainty score0.309

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.002
Science and technology studies0.0180.006
Scholarly communication0.0030.001
Open science0.0010.005
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0050.000

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 head0.069
GPT teacher head0.494
Teacher spread0.426 · 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

Citations1
Published2018
Admission routes2
Has abstractyes

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