Growing Girls: The Natural Origins of Girls' Organizations in America. By Susan A. Miller. (New Brunswick: Rutgers University Press, 2007. xii, 270 pp. Cloth, $68.00, ISBN 978-0-8135-4063-4. Paper, $23.95, ISBN 978-0-8135-4064-1.)
Bibliographic record
Abstract
In recent years, a burgeoning literature on the history of childhood has expanded in many directions. Paralleling the contemporary interest in girls, evidenced by best sellers such as Mary Pipher's Reviving Ophelia (1994) and Rachel Simmons's Odd Girl Out (2002), scholars have approached from a number of angles what was known at the turn of the last century as “the girl problem.” Some have focused on discourse about youth and gender, while others have used a variety of methodologies and sources to explore girls' lived experiences. Susan A. Miller's book falls into the former category, as girls themselves make only rare appearances in the book. Instead, Miller analyzes the rhetoric surrounding girls' organizations, particularly the summer camps run by the Camp Fire Girls, Girl Scouts, and Girl Pioneers. She argues that the “constellation of ‘natural’ activities offered by girls' organizations” during the first decades of the twentieth century reveal a great deal about the fears and hopes attached to modernizing American girlhood (p. 3).
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.003 | 0.004 |
| Scholarly communication | 0.004 | 0.007 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.032 | 0.010 |
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".