Bibliographic record
Abstract
In her foreword to the "V-Day Edition" of Eve Ensler's The Vagina Monologues, Gloria Steinem writes of her initial reaction to seeing Ensler's performance: "I already know this: it's the journey of truth telling we've been on for the past three decades". I shared that reaction as a spectator of the monologues, performed as part of the V-Day College Campaign on university campuses for the past three years, and when I sat in a US$55 seat to watch a professional production in Chicago in 2001. The four performances had only the text in common, but audience reactions were very much the same. The standing ovations, the whistles and yells, and the jubilant atmospheres left me wondering about this newly discovered need to jointly celebrate womanhood. What may initially appear as old-fashioned and redundant to those familiar with feminism's theatrical history in the U.S. strikes many in the general publicas outrageous and innovative, and they can't get enough. Why is such a need still present in these postfeminist days? and What does it signify that the need is being met through theatre (another old-fashioned notion for some)? If, indeed, The Vagina Monologues is merely echoing what early feminist consciousness- raising groups were teaching in the seventies, why has it now become a political sensation unparalleled in American feminist theatre?
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.015 | 0.015 |
| Scholarly communication | 0.014 | 0.009 |
| Open science | 0.001 | 0.009 |
| Research integrity | 0.002 | 0.007 |
| Insufficient payload (model declined to judge) | 0.019 | 0.005 |
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".