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Record W4254971424 · doi:10.32920/ryerson.14660490

Fair access to regulated professions: decoding the transition of migrant caregivers to nursing in Ontario

2021· preprint· en· W4254971424 on OpenAlexaffabout
Gowsiga Thirunavukkarasu

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldHealth Professions
TopicGlobal Health Workforce Issues
Canadian institutionsToronto Metropolitan UniversityYork University
Fundersnot available
KeywordsOppressionNursingInequalityWork (physics)MedicinePolitical scienceLaw

Abstract

fetched live from OpenAlex

The Live-in Caregiver program provides a gendered pathway to permanent residency in Canada for women who are internationally trained nurses. Upon attaining permanent residency and open work permits, internationally trained nurses can become registered members with the College of Nurses of Ontario, which will allow them to re-enter the nursing profession. However, in light of recent amendments to the registration regulation by the College of Nurses of Ontario issues of unequal treatment for international applicants arise. This paper examines the regulation of the Live-in Caregiver Program, and the recent amendments to the registration regulation by the College of Nurses of Ontario, to present the systemic oppression and discrimination which creates barriers for internationally trained nurses to their transition from caregiving to nursing in Ontario. Conclusions state that amendments to the regulatory policies must occur to eliminate the inequalities against internationally trained nurses.

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)0.009
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 score0.908
Threshold uncertainty score0.671

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.009
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.003
Science and technology studies0.0130.013
Scholarly communication0.0040.002
Open science0.0010.005
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0020.000

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 head0.105
GPT teacher head0.460
Teacher spread0.355 · 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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