Bibliographic record
Abstract
Doris didn’t change my life, but she helped refine it. She made huge assumptions about women in those days: if they were intelligent, of course they were feminists. By the time I met her in the 1960s, I knew I was a feminist but Doris made it seemed normal to be one. Remember in those days everyone seemed to hate us. We were freaks. At parties husbands would hiss, and women would go ballistic at anyone who professed to believe in Women’s Liberation. I was doing a series for cbc called People’s Liberation but the show was really only about women and you could get a real going over socially. Then I went to work for Chatelaine in 1970. You didn’t necessarily have to be a feminist to be a member of the staff. It wasn’t required by any means, you just absorbed Doris’s ideas like an osmotic transfer. I remember once seeing her at the movies (she loved going to movies and went alone, in the afternoon, or in the early evening—any time she could shoehorn them in). It was m*a*s*h* with Donald Sutherland, a Canadian actor we both admired. I was sitting on the aisle with my husband, laughing my head off when I saw Doris stomp out of the theatre hissing: “This is unbearable, it’s so sexist.” I muttered: “But it’s reflecting the way things were.” It didn’t occur to me that it wasn’t acceptable to just go along with something like that, even a movie, without thinking about it. I stopped laughing and saw the movie for what it was: agonizingly sexist. Doris never said another word about it. And certainly not at work. So in normalizing feminism in my life, she also extended my feminism. I was going through consciousness-raising sessions with women friends, discussing orgasms and other highly personal things none of us had talked about before. We didn’t think to ask Doris to join us, though we did ask Rosie Abella (now a Justice of the Supreme An Osmotic Transfer
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.004 |
| Scholarly communication | 0.005 | 0.007 |
| Open science | 0.002 | 0.009 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.099 | 0.027 |
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".