Conflict pressure cooker: Nurse managers’ conflict management experiences in a diverse South African workplace
Bibliographic record
Abstract
BACKGROUND: Nurse managers are central to conflict management and a healthy work environment. South Africa is one of the most diverse countries globally and workplace diversity is a reality in healthcare organisations. There is a gap in academic literature on conflict management by nurse managers in diverse workplaces in South Africa. AIM: This research aims to understand nurse managers' experiences of conflict management within a diverse South African workplace (military hospital) in order to facilitate a healthy work environment. SETTING: The context was a diverse, medical military organisation servicing all nine South African provinces. This military hospital employed staff of varying nationalities, catering to military and private patients, and functioned within a strict hierarchical structure. METHODS: Purposive sampling was used. Thirteen unstructured, individual interviews were conducted based on a qualitative, phenomenological design. The interviews were followed by content analysis and five main themes emerged as a result. RESULTS: A hierarchical, diverse organisational culture complicates conflict management. The ranking structure, resource shortages, intergenerational dynamics, poor communication and distrust cause conflict. Nurse managers experience conflict daily and are central to conflict management. As such, they have certain personal characteristics and display specific conflict management skills. Conflict management skills can be taught, but this requires an intra- to interpersonal process. A major challenge for the nursing profession today is the younger nurses who seem less passionate and nurse managers who are under more pressure than before. CONCLUSION: A medical military organisation presents an organisational culture that combined with diversity is predisposed to conflict, which endangers the work environment. Yet, both conflict and workplace diversity can, when managed correctly, enrich a healthcare organisation. Nurses and nurse managers will benefit from reflective conflict management training as an intra- to interpersonal process.
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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 | 0.004 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.014 | 0.004 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 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".