“The only girl in such a big class”: Women Students at the University of Toronto’s Faculty of Applied Science and Engineering during the 1920s and the 1930s
Bibliographic record
Abstract
This article draws the collective profile and examines the experiences of the handful of women who formed the first generation of female students enrolled at the University of Toronto's Faculty of Applied Science and Engineering (FASE) during the 1920s and 1930s. The student records shed light on their socio-economic background, which they shared to a large extent with their male counterparts and the other women attending university at the time. The available sources also provide information on the school's curriculum and pedagogical practices, and on the main features of student life at FASE. The institution cultivated and transmitted a deeply masculine culture: to train an engineer was to train a man and to construct a specific type of masculinity, symbolized by the "Schoolmen" and the "School Spirit." How did the pioneers adapt to this environment? How did FASE respond to their arrival? The article accounts for the diversity of views and experiences of the female students, and for the different reactions to their presence. Nevertheless, the entry of this pioneering group at FASE openly raised the question: can a woman be a woman and an engineer? Other studies are needed to better understand how female students answered this question in their own way, in different schools of engineering and in different historical settings. This work will help bring answers to this other question, which is still widely debated: why so few women engineers?
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.040 | 0.017 |
| Scholarly communication | 0.010 | 0.004 |
| Open science | 0.002 | 0.009 |
| Research integrity | 0.004 | 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".