Men Student Nurses: The Nursing Education Experience
Bibliographic record
Abstract
PURPOSE: This study explored the phenomenon of being a male in a predominately female-concentrated undergraduate baccalaureate nursing program. BACKGROUND: Men remain a minority within the nursing profession. Nursing scholars have recommended that the profile of nursing needs to change to meet the diversity of the changing population, and the shortfall of the worldwide nursing shortage. However, efforts by nursing schools and other stakeholders have been conservative toward recruitment of men. METHODS: Using Giorgi's method, 27 students from a collaborative nursing program took part in this qualitative, phenomenological study. Focus groups were undertaken to gather data and to develop descriptions of the experience. FINDINGS: Five themes highlighted men students' experience of being in a university nursing program: choosing nursing, becoming a nurse, caring within the nursing role, gender-based stereotypes, and visible/invisible. IMPLICATIONS: The experiences of the students revealed issues related to gender bias in nursing education, practice areas, and societal perceptions that nursing is not a suitable career choice for men. Implications for nurse educators and strategies for the recruitment and retention of men nursing students are discussed.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.008 | 0.004 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.001 | 0.009 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".