Women, Partners, and Mothers–Migratory Tendencies of Psychiatric Trainees Across Europe
Bibliographic record
Abstract
Introduction: Combining a successful career with family planning has become increasingly important in recent years. However, maintaining a relationship, deciding upon the optimal time for pregnancy and other family planning decisions can still be quite challenging, especially for junior doctors whose training is long and demanding. Currently, women form an important part of the medical workforce, and there is noticeable feminisation in migration. However, little is known about the personal characteristics of junior doctors in Europe and how these play a role in their decision to migrate. Methods: Survey of psychiatric trainees in 33 European countries, exploring how personal characteristics, such as gender, relationship status and parenthood, impact their attitudes towards migration. Results: 2281 psychiatric trainees in Europe took part in the study. In this sample, the majority of psychiatric trainees were in a relationship, but only one quarter had children, although there were variations across Europe. Both men and women indicated personal reasons as their top reason to stay. However, women ranked personal reasons as the top reason to leave, and men financial reasons. Single woman were the most likely of all subgroups to choose academic reasons as their top reason to leave. Interestingly, when women were in a relationship or had children, their attitudes towards migration changed. Conclusions: In this study, a low number of psychiatric trainees in Europe had children, with differences across Europe. This finding raises awareness as to the role of paternity conditions, which may be favouring or discouraging parenthood in junior doctors in different countries.
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 | 0.001 | 0.002 |
| 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 | 0.001 |
| 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 | 0.000 |
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 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".