[Female professors in medicine in 2003: appointment, duties and family life].
Bibliographic record
Abstract
OBJECTIVE: To inventory (a) how and when female professors of medicine were appointed, (b) how they combined their work with family life, (c) which changes in health care female and male professors expected as a consequence of the increasing number of women physicians, and (d) which changes they wished to see for their successors. DESIGN: Descriptive. METHOD: A questionnaire was used to collect data from the female professors of medicine who worked in the Netherlands as of 1 January 2003 (n = 43), and from the same number of male professors of medicine, who were matched for age and speciality. RESULTS: 39 women and 39 men responded (91%). The women were more often appointed after a closed application procedure (69 versus 51%). Two fifths of the women had a part-time appointment as professor, but they worked at least 45 hours per week. Women were more often present in educational committees than in selection committees. At the time of their appointment most women had no children (n = 16) or children who did not live at home (n = 7); the other 16 (41%) had children at home, as did 33 (85%) of the male professors. Over half of the 23 women with children were at home for at least 2 half-days per week when the children were young and in some cases the partners cared for the children full-time; the opposite was found among the 35 men with children. A quarter of both mothers and fathers was present for activities of their children, like soccer training and final swimming tests, during office hours. The most important recommendations regarding the appointment and the functioning of professors concerned the structure and flexibility of medical education, the carefulness when considering appointments, and the possibilities to work part-time and to have a family life.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".