Bibliographic record
Abstract
In 2009 a Globe and Mail pundit claimed that the current doctor shortage stems from increasing numbers of women in medicine. This opinion is widely held, despite articulate opposition from medical deans who characterized it as a new variant of the old "sexist blame game" (CMAJ 2008). In this ambivalent climate, we interviewed 10 women who entered the Canadian profession between 1945 and 1960, when strict limits on female students were established in most schools. Using semi-structured, in-person and telephone interviews, we found that they worked as much as their male colleagues. Several also raised three to five children; and negotiation of the domestic sphere usually fell to them. Most worked past age 65, and two are still working well into their eighties. Our findings will be set in the context of the existing literature on women in medicine. We will also examine the results of surveys on physicians' working hours, in which all specialties show a decline, including those that have not been feminized. We conclude that the women who entered the profession between 1945 and 1960 did not contribute to the current doctor shortage.
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 | 0.010 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.070 | 0.025 |
| Scholarly communication | 0.011 | 0.004 |
| Open science | 0.002 | 0.009 |
| Research integrity | 0.007 | 0.011 |
| Insufficient payload (model declined to judge) | 0.007 | 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".