Bibliographic record
Abstract
This article begins with the question of whether and how theatres use the word feminism in their advertising and on their websites. I address Calgary’s Urban Curvz theatre company and their assertive use of the word, drawing on conversations with Lindsey Zess-Funk, Artistic Associate, and Jacqueline Russell, the company’s Artistic Director. Is the language of feminism attractive as a marketing strategy for professional theatre? The marketing choices of Urban Curvz—the images used, the language employed, the events hosted—can provide an alternative message to the cacophony of other theatres’ advertising campaigns, and can create an alternative intention for theatregoers in Calgary, but need to be handled carefully. Urban Curvz has made an impact through the growing profile of its Girls Gone Wilde! festival and other special events it sponsors, such as Take Back Halloween, an event held in 2014 that attracted significant media attention but also some negative feedback, as the intention to offer an alternative to the hypersexualization of Halloween costumes was misconstrued by some as “slut shaming.” This incident points to the challenges of articulating a feminist message.
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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.006 | 0.007 |
| Scholarly communication | 0.007 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.007 | 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".