Bad Girls of Fashion: Style Rebels from Cleopatra to Lady Gaga by J. Croll
Bibliographic record
Abstract
Jennifer Croll. Bad Girls of Fashion: Style Rebels from Cleopatra to Lady Gaga. Illustrated by Ada Buchholc. Annick Press, 2016.Vancouver journalist and fashion historian Jennifer Croll, author of Fashion that Changed the World (2014), has here shifted gears to acquaint younger readers with the role of fashion in the history of women’s empowerment and liberation. Through the lens of biography, Croll traces the gradual rise of Girl Power reflected in, and partly driven by, the fashion choices of forty women, all of them “Style Rebels.” She divides them into ten categories that include Leaders, Modernizers, Instigators, Gender-Benders, Radicals, Decadents, and Freaks.Egypt’s Queen Cleopatra VII and England’s Queen Elizabeth I crafted their regal images partly through their fashion choices; Cixi, the Dowager Empress of China, also outlawed the binding and deforming of girls’ feet; the excesses of Frances’s Queen Marie Antoinette helped to seal her doom; Amelia Bloomer and George Sand (aka Aurore Dupin) scandalized nineteenth-century society by shunning traditional women’s clothing; Coco Chanel replaced traditional corsetry and petticoats with comfortable fashions (and gave the world an eponymous perfume); fashion magazine editors Diana Vreeland and Anna Wintour reigned as arbiters (many said “dictators”) of late-twentieth-century fashion; artists as geographically and culturally diverse as Japan’s Yoko Ono and Rei Kawakubo and Mexico’s Frida Kahlo influenced fashion with their idiosyncratic styles; movie stars such as Louise Brooks, Marlene Dietrich, Marilyn Monroe, Diane Keaton, and Cher Bono became trend-setters in fashion by expanding acceptable boundaries of femininity and gender; while pop-star singers Madonna, Lady Gaga, Björk, Rihana, Nicki Minaj, Beth Ditto, and the ladies of Pussy Riot pushed still further the limits of attention-grabbing self-expression in their attire (or lack of it).Croll’s cast of characters is a large one—this is only a partial list—but one that she stage-manages adroitly. It’s also one that could have been considerably expanded; one notes, for example, the absence of such iconic, fashion trend-setters as Katherine Hepburn and pioneer aviator Amelia Earhart. Book designer Natalie Olsen has provided a stunning layout, one awash in bold colours, and illustrated with both photographs and original, caricature portraits by Polish illustrator Ada Buchholc. In this serious contribution to social history, the author neither shuns, nor sensationalizes, but treats lightly some of her subjects’ love affairs, marital infidelities, sexual preferences, and the role and influence of Lesbian fashions. These nonetheless mark this excellent book as one best suited to older, the publishers suggest ages 12+, and adult readers. Recommended for all public, high-school, and academic curriculum libraries, as well as specialized women’s studies collections.Highly Recommended: 4 out of 4 starsReviewer: Merrill Distad Historian and author Merrill Distad enjoyed a four-decade career building libraries and library collections.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.007 | 0.003 |
| Scholarly communication | 0.006 | 0.005 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.005 |
| Insufficient payload (model declined to judge) | 0.049 | 0.016 |
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".