The growing number of female physicians: meanings, values, and outcomes
Bibliographic record
Abstract
Throughout the developed world the proportion of women in professions such as medicine is increasing. This commentary uses Haklai et al's nuanced report on the feminization of medicine in Israel as a starting point. I discuss whether gender shifts are an outcome of more egalitarian attitudes towards women overall, or instead arise from men choosing other professions, the extent of the shift, and its meaning for the quantity and quality of medical care. The discussion is embedded in more fundamental concepts such as the aims of medical practice and the best indicators of effective care. I reflect on concerns about lower female physician productivity at a time when the proportion of female physicians still remains below parity in almost all countries. Medicine is embedded in the principles and expectations of the community being served. The profession's values and practices both shape and are shaped by those of that larger community. As cultures move toward equality, proportional representation of women and men in medicine will follow, while remaining limitations to gender equality will be mirrored in opportunities and restrictions for women in medicine. This is a commentary on http://www.ijhpr.org/content/2/1/37/.
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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 | 0.010 | 0.046 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.008 | 0.009 |
| Scholarly communication | 0.008 | 0.006 |
| Open science | 0.005 | 0.002 |
| Research integrity | 0.033 | 0.034 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".