A Scholarly Tribute to Bettina Bradbury, Feminist Historian of the Family
Bibliographic record
Abstract
I came to Canada from England in 1995 to pursue an ma and then a PhD in Women’s Studies. Bettina supervised both my master’s thesis and doctoral dissertation. The first compared discourses about women and aviation in Canada and the USA before 1920, and the second dealt with women in imperial airspace from 1922 to 1937, with a particular emphasis on the relationship between England and New Zealand. During my ma I wrote a paper on the pilot Katherine Stinson for Bettina for a graduate course in Women’s Studies that she was team teaching. Although aviation history is quite far from Bettina’s own areas of expertise, she was willing to take me on for the thesis. I think that she was up for the challenge in part because her own scholarship has been part of large shifts in the way history is done with its linguistic and spatial turns and because in her own research on family, widows, law, and empire she is constantly willing to ask new questions and to ask questions in different ways. In the process of writing the paper on Stinson, Bettina pushed me to undertake two tasks. First, she wanted me to find newspaper accounts about Stinson in 1917 and 1918, so I had to learn to use microfilm. I spent hours after classes in the Scott Library at York University making my head swim as I toiled through the Manitoba Free Press, the Calgary Daily Herald, and The Globe. The second task she set me was to find out what happened to Stinson in the end: obviously, the newspaper accounts could not tell me. The only major book on the Stinson family, by John Underwood, was in the great tradition of aviation history. It focused on the family’s glorious youthful years because part of the mythology of flying is to be young, as Bernhardt Rieger demonstrates so well in his work.1 So I had to learn how to trace a person once their early fame had evaporated. Bettina’s prodding, over the amount of detail that I needed to know in order to make any claims, completely changed my intellectual life. In the end, she showed me that my argument would begin to emerge from the welter of detail. Up until then my exposure to history had been reading textbooks for the history unit in my American Studies undergraduate degree. I therefore imagined that in order to write about women pilots (not something that any serious scholar was doing at that time) I would read histories of aviation (which were mostly histories of particular aircraft types or organizational or military histories) and try to add women in. I also thought I should note
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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 | 0.004 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.032 | 0.024 |
| Scholarly communication | 0.010 | 0.008 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.003 | 0.013 |
| Insufficient payload (model declined to judge) | 0.022 | 0.004 |
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".