The impact of high-performance work practices on employee burnout experience in UK higher education: a professional services perspective
Bibliographic record
Abstract
Evidence demonstrates work intensity is on the rise and can lead to higher rates of burnout. The UK Higher Education professional services sector has been under-researched in terms of work intensity levels and experience of burnout. This research measured these levels and sought evidence of whether high-performance work practices (HPWPs) moderate the user’s level of burnout. Quantitative data were collected using a cross-sector survey and tested for correlation. The results evidenced a moderate, positive relationship between work intensity and burnout, and a strong, negative relationship between HPWPs and burnout. Drawing on the Job Demands – Resources model (Demerouti et. al. 2001), this research contributes to the understanding of the factors contributing to burnout in the UK Higher Education context. Practical implications include addressing the widespread culture of overwork and employing HPWP suites to moderate burnout. Suggestions for further research provide additional clarity.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".