Women in psychiatry: A view from the Indian subcontinent
Bibliographic record
Abstract
BACKGROUND: Psychiatry has not been a preferred medical specialty for women in the Indian subcontinent unlike in the Western countries like USA, Canada or UK. Recent years have seen an increase in the number of women doctors in India choosing psychiatry as career. MATERIALS AND METHODS: Information on women in psychiatry in the Indian subcontinent was collected using resources like PubMed, directories of the professional societies, websites of medical institues, souvenirs and scientific programme of various conferences and personal communication with psychiatrists, and the data about postgraduate trainees available with the authors' own institute. RESULTS: Women psychiatrists constitute about 15% of total psychiatrists in India, out of whom only 10% are at a relatively senior level, and the most are young. The women psychiatrists are also in faculty positions in a number of medical schools and have held important positions in the Indian Psychiatric Society at different times. CONCLUSIONS: Most of the women psychiatrists appear to be still at junior levels, having joined the profession relatively recently as compared to their male counterparts. The trend at increasing number of women psychiatrists in the Indian subcontinent is similar to the worldwide trends.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.010 | 0.007 |
| Scholarly communication | 0.007 | 0.004 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.002 | 0.005 |
| 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".