Control of resources in the nursing workplace: Power and patronage relations
Bibliographic record
Abstract
Immigrant nurses make up a large percentage of the Australian nursing workforce. Since the support in the workplace is expected to be inclusive for all nurses, the aim of this article is to explore how support and opportunities for professional growth, learning and development are distributed across different categories of nurses working in a neonatal intensive care unit (NICU). An ethnographic approach has opened an examination of the everyday workplace practices in the NICU to gain insight into how nurses made sense of the social and power relations occurring between themselves and their senior colleagues and how they experienced the support and opportunities they received in their workplace. As today's workplaces such as the NICU are diverse in races, culture and experiences, the concepts of intersectionality and cultural safety assisted in identifying inequality and injustice related to such diversity. The results showed how patronage relations rendered nurses with immigrant status with major disadvantage and left them clinically and culturally vulnerable. Such inequity defeats the reasons for encouraging skilled migration of nurses and poses questions on the cultural competency of recruiting organisations. Considering how cultural safety might guide staff development offers opportunities for authentic support to culturally diverse nurses.
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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 | 0.007 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.012 | 0.023 |
| Scholarly communication | 0.010 | 0.006 |
| Open science | 0.001 | 0.010 |
| Research integrity | 0.001 | 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".