Feasibility for the implementation of the MENtorship Program
Bibliographic record
Abstract
Objective: Men comprise only 9% of the U.S. nursing workforce and 15% of baccalaureate nursing students. The odds of male nursing students completing nursing school are significantly lower than that of female nursing students. Mentoring programs designed to improve male nursing student retention are needed. This study was conducted to evaluate the feasibility of a novel “MENtorship” Program for men in nursing school.Methods: This study used a sequential QUAN-qual explanatory mixed methods design in two phases: (1) quantitative web-based surveys were sent to all participants (n = 19) to assess mentor/mentee relationships; and (2) qualitative interviews were conducted to explain the survey results. Data were analyzed thematically, and data source triangulation was done by comparing the qualitative findings to the quantitative findings.Results: Findings included high perceived commitment from mentors and mentees. Participants described multiple program benefits and recommended program improvements. One key recommendation is to provide a thematic focus to each mentor/mentee meeting (i.e. professionalism, ethics, nursing specialties).Conclusions: The MENtorship Program pilot was deemed feasible for future implementation.
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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 | 0.035 | 0.041 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.012 | 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".