Bibliographic record
Abstract
Leadership is generally identified with men. Only a quarter of the secondary school heads in England and Wales are women. Despite changes in society, there are still issues for women who aspire to leadership in schools. Some of those tackled here are: Will I be up against institutionalized views that make my career progress difficult? Will I have to be seen to lead like a man if I am going to be considered a good headteacher? Will I have credibility as a leader and manager if I combine motherhood and a career? How will men react to being managed by a woman? There are also issues for schools and their senior managers, related to encouraging women to go to the top, such as: What career support and advice are we offering? Are we offering appropriate role models? How do we view maternity leave? Are we family friendly? The author's survey of women headteachers in England and Wales plus in-depth interviews present the views of the women who have become leaders in schools. Complementary data from the same number of male headteachers allows comparisons to be drawn between the careers and the perceptions of work and family of men and women heads, shedding light on the many issues explored.
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.
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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.007 | 0.006 |
| Scholarly communication | 0.007 | 0.004 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.014 | 0.004 |
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".