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Record W4254804476 · doi:10.32920/ryerson.14664003.v1

Clinging to a knife’s edge: the Live-in Caregiver Program

2021· preprint· en· W4254804476 on OpenAlexaffabout
Leona Carmelita Pagunuran Canay

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldSocial Sciences
TopicMigration and Labor Dynamics
Canadian institutionsToronto Metropolitan UniversityCentre for Social Innovation
Fundersnot available
KeywordsDenialInterviewColonialismHuman rightsImmigrationNarrativeDominance (genetics)InequalityPoliticsPsychologySociologyPolitical scienceGender studiesLawPsychotherapist

Abstract

fetched live from OpenAlex

Since the 1900s, Canada has heavily relied on foreign domestic workers. This program has evolved over the years into what is currently known as the Live-in Caregiver Program (LCP). It is rooted in our colonial history and has reproduced power imbalances between employers and caregivers. Challenging dominance is a difficult task given that immigration policies perpetuate inequalities through the denial of social, economic and political rights to caregivers. I selected this topic based on my experiences as a live-in caregiver with this program. This study uses anti-colonialism and feminist thought to examine the experiences of three former LCP workers. Through narrative interviewing, the findings indicate that the live-in requirement of the LCP has contributed to the abuse, exploitation and marginalization of these caregivers. The study concludes with a discussion of the ways in which the structure of the program can be modified to prevent further exploitation and human rights violations.

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)0.003
metaresearch head score (Gemma)0.006
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 score0.922
Threshold uncertainty score0.156

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0230.008
Scholarly communication0.0030.003
Open science0.0010.005
Research integrity0.0010.004
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 head0.029
GPT teacher head0.362
Teacher spread0.333 · 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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