New evidence on teachers' working hours in England. An empirical analysis of four datasets
Bibliographic record
Abstract
Surveys have revealed that teachers in England work far longer hours than their international counterparts, causing serious concern amongst both policymakers and the profession. Despite this, surprisingly little is known about the structure of and changes to teachers’ working hours. We address this gap in the evidence base by analysing four different datasets. Working hours remain high: a quarter of teachers work more than 60 hours per week during term time, 40% report that they usually work in the evening and around 10% during the weekend. However, contrary to current narratives, we do not find evidence that average working hours have increased. Indeed, we find no notable change in total hours worked over the last twenty years, no notable change in the incidence of work during evenings and weekends over a fifteen year period and no notable change in time spent on specific tasks over the last five years. The results suggests that policy initiatives have so far failed to reduce teachers’ working hours and that more radical action may need to be taken in order to fix this problem.
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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 | 0.003 | 0.022 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 0.002 |
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".