The extended late career phase – examining senior nursing professionals
Bibliographic record
Abstract
Purpose By relying on a sustainable career perspective and recent studies on senior employees’ late career phase, this study aims to examine senior (50+) nurses’ late career narratives in the context of extending retirement age. Given the current global nursing shortage, there is a pressing need to find ways on how to promote longer and sustainable careers in the health-care field. Yet, there is limited knowledge about the extended late career phase of senior nurses. Design/methodology/approach Empirical data were derived from 22 interviews collected among senior (50+) nursing professionals working in a Finnish university hospital. The qualitative interview data were analysed using a narrative analysis method. As a result of the narrative analysis, four career narratives were constructed. Findings The findings demonstrated that senior nurses’ late career narratives differed in terms of late career aspirations, constraints, mobility and active agency of one’s own career. The identified career narratives indicate that the building blocks of sustainable late careers in the context of extending retirement age are diverse. Research limitations/implications The qualitative interview data were restricted to senior nurses working in one university hospital. Interviews were conducted on site and some nurses were called away leaving some of the interviews shorter than expected. Practical implications To support sustainable late careers requires that attention be based on the whole career ecosystem covering individual, organizational and societal aspects and how they are intertwined together. Originality/value So far, few studies have investigated the extended late career phase of senior employees in the context of a changing career landscape.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.007 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".