The Times of the Faculty: Variations in the Length of the Workweek of Faculty at Flemish Universities
Bibliographic record
Abstract
Over the past decade discontent in Flemish universities with the increased work load of faculty members has risen. This study is the first to examine how many hours a week senior researcher (postdocs and faculty) in Flemish universities actually work. The data used stems from the 2010 Survey of Senior Researcher conducted among senior researchers at the five Flemish universities. 1195 respondents provided information on their working hours. Senior researchers worked on the average 50.4 hours a week, with 12% reporting to work more than 60 hours a week. The number of hours worked varied significantly with rank, where respondents in more senior ranks reported to work more hours. Once one controls for rank any gender differences in number of hours work disappear. We did observe a significant trade-off between the time spent on various activities. Postdocs spent more time on research than the other ranks, and senior professors spent more time on service and administration. Respondents from the humanities, and to a lesser degree from the social sciences, spent more time on education than respondents from other disciplines. This study confirms that senior researchers at Flemish universities work long hours, and that the number of hours spent on various activities is largely a reaction to demands from their institutional environment.
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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 | 0.001 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".