How do views of working conditions vary across school staff?
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
There has been much recent interest in working conditions in schools. Yet most existing studies are based on samples of teachers, without capturing the views of other members of staff. This is despite individuals in non-teaching roles (teaching assistants, office staff, pastoral care) accounting for around half of England’s school employees and who make a considerable contribution to the work environment shared amongst office staff. The present paper therefore presents new evidence on how working conditions compare across different staff groups. It does so via a secondary analysis of data from almost 6,500 school employees within 91 schools collected by The Engagement Platform (TEP). Using a mix of descriptive statistics and OLS regression analysis we find that, while workload is the key issue facing teachers, pay is of relatively greater concern amongst teaching assistants, pastoral workers and office staff. The strong association between the views of those in teaching and non-teaching roles within the same school nevertheless means that samples comprising only teachers are likely to be a reasonable proxy for the school working environment as a whole. Senior leaders are also found to be consistently more positive about working conditions than the staff they employ.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.004 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| 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