Bibliographic record
Abstract
The research was undertaken within the Workforce Ageing in the New Economy project funded by the Canadian Social Sciences and Humanities Research Council, involving Canada, Australia, United States and three EU countries. The paper is concerned with the issue of whether working in rapidly changing IT employment is leading to de-standardization of the life course and prolonging of working lives beyond 65. The main aims of the paper were to examine whether new versions of extended careers are emerging in IT employment, how age relations between younger and older workers affect IT careers and whether and how the life course of IT workers is being refashioned through their careers in IT. The findings are based on analyses of focused interviews with around seventy information technology workers in eight small to medium companies. The research examined whether working in IT employment is changing the expectations of standard life course of retiring at 65. Exploration of relations between the ages indicated that age relations tended to support existing retirement expectations rather than retention. Despite the potentiality for change and for reconstructing careers, perspectives of truncated careers persisted rather than of careers as lengthening. Nevertheless new sequences of careers were found which varied according to type of IT work and positions. Factors in retention included opportunities for training and some innovative human resources options. The analysis indicates that ageist expectations of working lives persist and that new human resources policies have yet to be tailored to prolonging working lives within new economy IT employment.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".