Bibliographic record
Abstract
At the heart of Stripping, Sex, and Popular Culture lies a very personal story, of author Catherine Roach's response to the decision of her life-long best friend to become an exotic dancer. Catherine and Marie grew up together in Canada and moved to the USA to enroll in PhD programs at prestigious universities. For various reasons, Marie left her program and instead chose to work as a stripper. The author, at first troubled and yet fascinated by her friend's decision, follows Marie's journey into the world of stripping as an observer and analyst. She finds that this world raises complex questions about gender, sexuality, fantasy, feminism, and even spirituality. Moving from first hand interviews with dancers and others, the book broadens into a provocative and accessible examination of the current popularity of "striptease culture," with sex-saturated media imagery, thongs gone mainstream, and stripper aerobics at your local gym. Stripping, Sex, and Popular Culture scrutinizes the naked truth of a lucrative industry whose norms are increasingly at the center of contemporary society.Moving from first hand interviews with dancers and others, this book broadens into an accessible examination of the popularity of "striptease culture," with sex-saturated media imagery, and stripper aerobics at your local gym. It aims to scrutinize the truth of a industry whose norms are increasingly at the center of contemporary society.Catherine M. Roach is Associate Professor of New College, and Affiliated Faculty in Religious Studies and Women's Studies, at The University of Alabama, USA. She received her PhD from Harvard University in 1998 and is also the author of Mother / Nature: Popular Culture and Environmental Ethics (Indiana University Press, 2003).
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.007 | 0.019 |
| Scholarly communication | 0.010 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".