British Girls’ and Women’s Magazines at the University ofWaterloo
Bibliographic record
Abstract
I am a European historian, specializing in British girls’ magazines, but I do my research in Canada. How can this be? Like many, my path in academia has not been a straight one. I completed the bulk of my BA with one daughter; my second daughter was born the summer before I began my fourth year. It was around the same time that I decided to change my original plan of becoming a high school social studies teacher, opting instead for graduate school. Entering my MA with two children – one six, the other one – I had to carefully balance studying, researching, working as a TA, and family. I was grateful to stumble upon a microfilm collection of the first two years of The Girls’ Best Friend, a British girls’ publication, at the University of BC, facilitating my first foray into girls’ magazines and permitting me to more easily balance the various parts of my life. Entering the PhD program at Simon Fraser University, however, I thought that I would need to travel to England to continue my work on girls’ magazines. I was concerned: how would I fund this travel? How would I secure sufficient time to do my research? What about my family? For personal reasons, packing everyone up and relocating to England to allow sufficient\ntime to go through my sources was simply not possible; going alone would mean frequent, short trips to minimize the impact of my time away. Each of these options, though, resulted in a significant amount of stress.
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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.006 | 0.001 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.235 | 0.031 |
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".