Bibliographic record
Abstract
In this article, my specific focus is on the American women mathematics PhDs of the 1940s.I begin by laying out some historical context for understanding this cohort of American women in mathematics.Next, I provide a list (current as of January 2021) of the 86 women I've been able to identify who earned mathematics PhDs in the US and Canada during the 1940s, and go on to describe some of their personal and professional characteristics.Finally, I discuss ongoing work on the Women Becoming Mathematicians website ([17]), which serves as a reference repository for basic background information on this generation of American women mathematics PhDs.A brief comment on notation: when I introduce a particular woman mathematics PhD in the text, I enclose the name of the PhD-granting institution and the year the PhD was awarded in parentheses immediately following the woman's name. Historical ContextAcross eras, civilizations, and cultures, it is clear that both women and men have carried out mathematical work.But in the recorded history of mathematics, there are very few accounts of women's mathematical activity before the 19th century.The 19th century also marks the emergence of the research doctoral degree, beginning in Europe and then spreading to America and across the globe.In most of the emerging mathematical communities of the late 19th and early 20th centuries, the PhD in mathematics came to be viewed as a certification of accomplishment in research and as prerequisite for admission to the professional caste in research mathematics ([18], [15, pp.1-3]).So far as we know, Sonya Kovalevskaya was the first woman to earn a PhD in mathematics, awarded to her in absentia by the University of Berlin in 1874 ([13, p. 123]).In 1862, Yale University awarded the first US PhD in mathematics-to a man, J. H. Worrall ([18, p. 202]).Twenty years later, in 1882, Christine Ladd-Franklin became the American Women Mathematics PhDs of the 1940s
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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 | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.008 | 0.003 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.000 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.018 | 0.003 |
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".