Serving up revolution: feminist restaurants, cafés, and coffeehouses in the United States and Canada from 1972-1989
Bibliographic record
Abstract
“Serving Up Revolution: Feminist Restaurants, Cafés, and Coffeehouses from 1972-1989 in the United States and Canada,” is the first history of more than 250 feminist and lesbian restaurants, cafés, and coffeehouses that existed in Canada and the United States during the 1970s and 1980s. Utilizing business records, advertisements, feminist and lesbian periodicals, and a dozen original interviews, I examine the ways feminist restaurants, cafés, and coffeehouses promoted women-owned and women-centered businesses and fostered non-capitalist and non-hierarchal business practices and models. The existence of these restaurants challenged the assumption of a fraught relationship between feminism and cooking and showed that the kitchen could be a space of empowerment for women rather than an oppressive sphere. I argue that feminist restaurant history reveals the importance of physical space for socializing, activism, economics, and community building. I also make a methodological contribution by utilizing a large database of lesbian and women’s travel guides, from which I created maps using GIS mapping technology. By including a study of feminist coffeehouses, this dissertation is able to spotlight feminist activism and community building additionally in smaller towns as these commonly temporary women’s spaces could happen anywhere from a church basement in Iowa to the corner of a bookstore in Washington state. I ultimately argue that feminist restaurants produced fertile environments for political organizing and activism. The history of feminist restaurants, cafés, and coffeehouses in the United States and Canada is a history of business practices, political activism, and food politics
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.028 | 0.007 |
| Scholarly communication | 0.006 | 0.002 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.000 |
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".