Infirmières issues de minorités visibles et mobilité verticale en milieu hospitalier
Bibliographic record
Abstract
Canada has experienced a significant change in its ethnic and cultural composition in recent decades. The sustained immigration from non-European countries has given rise to new generation of visible minorities. This new trend is clearly reflected in healthcare institutions. However, the number of visible minority nurses (VMN) is particularly low in management positions. This research adopting critical ethnography and postcolonial approach focuses on the career paths of VMN in Canadian healthcare institutions. Nurses (n = eight, MVN) and managers (n = four caucasian) participated in a series of semi-structured interviews to gather relevant information about the representativeness of the VMN in management positions. Theoretical framework « Othering » was used to guide this research as it makes the link with “la lutte de classement” of Bourdieu. Four main themes closely associated with barriers emerged from the analysis namely ; Hiring and Promotion ; instrumentalization of IMV ; interpersonal and suffering and defensive strategies. Results showed that the VMN faced obstacles, often invisible, that contribute to keeping them at a lower level of the institutional hierarchy, including the hiring and promotion process that they describe as unfair and discriminatory.
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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 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.011 | 0.009 |
| Scholarly communication | 0.006 | 0.002 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".