Prolonging the careers of older information technology workers: continuity, exit or retirement transitions?
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
ABSTRACT The article explores the ways in which older workers' career trajectories influenced their exit from or continuity of employment in the Australian information technology (IT) industry. The data were collected through qualitative interviews with 71 employees of 10 small and medium-sized IT firms as part of the cross-country Workforce Ageing in the New Economy project (WANE), which was conducted in Canada, the United States, Australia and several European Union countries (the United Kingdom, Germany and The Netherlands). The analysis revealed that older IT workers' capacity to envisage careers beyond their fifties was constrained by age-based ‘normative’ capability assumptions that resulted in truncated careers, dissuaded the ambition to continue in work, and induced early retirement. The workers' constricted, age-bound perspectives on their careers were reinforced by the rapid pace of technological and company transformations. A structural incompatibility was found between the exceptional dynamism and competitiveness of the IT industry and the conventional age-staged and extended career. The analysis showed that several drivers of occupational career trajectories besides the well-researched health and financial factors predisposed ‘default transitions’ to exit and retirement. The paper concludes with policy and practice recommendations for the prolongation of IT workers' careers and their improved alignment with the contemporary lifecourse.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| 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 it