Choosing nursing as a career: a narrative analysis of millennial nurses' career choice of virtue
Bibliographic record
Abstract
The growth and sustainability of the nursing profession depends on the ability to recruit and retain the upcoming generation of professionals. Understanding the career choice experiences and professional expectations of Millennial nurses (born 1980 or after) is a critical component of recruitment and retention strategies. This study utilized Polkinghorne's interpretive, narrative approach to understand how Millennial nurses explain, account for and make sense of their choice of nursing as a career. The positioning of nursing as a virtuous choice was both temporally and contextually influenced. The decision to enter the profession was initially emplotted around a traditional understanding of nursing as a virtuous profession: altruistic, noble, caring and compassionate. The centricity of virtues depicts one-dimensional understanding of the nursing profession that alone could prove dissatisfying to a generation of professionals who have many career choices available to them. The narratives reveal how participants' perceptions and expectations remain influenced by a stereotypical understanding of nursing, an image that remains prevalent in society and which holds implications for the future recruitment, socialization and retention strategies for upcoming and future generations of 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 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.008 | 0.007 |
| Scholarly communication | 0.006 | 0.008 |
| 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".