A Systematic Review of Factors Impacting Older Workers’ Experiences with Technology in the Workplace
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
The impact of technology on the work experiences of older workers is a topic of growing interest. As the global population ages, leading to an increased representation of older employees in the workforce, understanding the dynamics of their careers in the evolving technological landscape becomes crucial. Despite this demographic shift, there is a noticeable gap in research addressing the factors influencing older workers' experiences within the changing technological work environment. To bridge this gap, we conducted a comprehensive systematic literature review, encompassing 121 papers from peer-reviewed journal articles to grey literature. This review not only synthesizes and evaluates existing research but also provides significant implications for both scholars and practitioners. It provides valuable insights into individual career development, career management strategies, and the relationship between technology and careers, offering directions for future research and strategies to ensure a technologically adaptive work environment for older workers.
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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 | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.001 | 0.004 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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