Forms of Capital as Facilitators of Internationally Educated Nurses’ Integration into the Registered Nursing Workforce in Canada
Bibliographic record
Abstract
Dans cet article, nous utilisons des données obtenues grâce à des interviews pour examiner comment des infirmières et des infirmiers ayant obtenu leur diplôme à l’étranger perçoivent les facteurs qui ont facilité leur intégration dans cette profession au Canada. Selon les participants, plusieurs facteurs entrent en jeu, et ces facteurs semblent refléter des formes de capital. Le capital économique (ressources financières disponibles) et le capital culturel (compétences linguistiques et connaissance du vocabulaire de la profession) leur ont permis de mettre à profit d’autres formes de capital afin de pouvoir faire officiellement partie de la profession et trouver ainsi du travail. Par conséquent, offrir aux infirmières et aux infirmiers ayant obtenu leur diplôme à l’étranger des ressources financières et des moyens de développer leurs compétences linguistiques pourrait les aider à avoir plus rapidement accès à la profession et à trouver un emploi au Canada.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.006 | 0.015 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.011 | 0.006 |
| Scholarly communication | 0.007 | 0.002 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".