Launching a career: inter-generational differences in the early career stage based on retrospective accounts
Bibliographic record
Abstract
Launching a career is one of the critical challenges of early adulthood. The early career stage, which generally occurs by age 30 (Shindul-Rothschild 1995) is a period of tremendous psychological changes, including organizational and occupational socialization, gaining professional competence and self-efficacy and earning the acceptance and respect of peers (Lynn et al. 1996). This foundational career stage is when career entrants form initial career expectations that may or may not be consistent with the reality of their subsequent experiences. Recent literature concerning generational differences (e.g. Twenge et al. 2010) and the changing nature of careers (e.g. Briscoe and Finkelstein 2009; Sullivan and Baruch 2009) suggests that the nature and experiences of today’s career entrants differ notably from previous generations. If so, traditional career counseling and life planning models may not be consistent with more contemporary career experiences (Burke and Ng 2006), requiring a new conception of the career cycle. In this qualitative study, we compare the early career experiences of members of three distinct generations (Baby Boomers, Generation Xers, and Millennials) of Canadian workers. In order to overcome the limitations of cross-sectional research as a method of studying inter-generational career patterns, we employed in-depth interviews to attain guided retrospective narratives of the early careers of people from various generations. This study illustrates a useful means of qualitatively assessing generational differences. It contributes to the literature concerning generations and careers by analyzing first-hand accounts of the early career experiences of people who launched their careers in various historical eras, providing contextual evidence about the changing nature of careers through the words of career actors.
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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 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".