Reluctance to Retire: A Qualitative Study on Work Identity, Intergenerational Conflict, and Retirement in Academic Medicine
Bibliographic record
Abstract
Purpose of the Study: Some professions foster expectations that individuals cultivate their work identity above all other aspects of life. This can be problematic when individuals are confronted with the expectation that they will readily terminate this identity in later-career stages as institutions seek to cycle in new generations. This study examines the relationship between work identity and retirement by examining multiple generations of academic physicians. Design and Methods: This study used a multimethod qualitative design that included document analysis, participant observation, focus groups, and in-depth interviews with academic physicians from one of the oldest departments of medicine in North America. Results: This study illustrates how participants were predisposed and then groomed through institutional efforts to embrace a career trajectory that emphasized work above all else and fostered negative sensibilities about retirement. Participants across multiple generations described a lack of work-life balance and a prioritization of their careers above nonwork commitments. Assertions that less experienced physicians were not as dedicated to medicine and implicit assumptions that later-career physicians should retire emerged as key concerns. Implications: Strong work identity and tensions between different generations may confound concerns about retirement in ways that complicate institutional succession planning and that demonstrate how traditional understandings of retirement are out of date. Findings support the need to creatively reconsider the ways we examine relations between work identity, age, and retirement in ways that account for the recent extensions in the working lives of professionals.
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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 | 0.024 | 0.027 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.019 | 0.013 |
| Scholarly communication | 0.005 | 0.006 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.002 | 0.004 |
| 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".