Feminist Collections, v.28, no.4 (summer-fall 2007)
Bibliographic record
Abstract
CONTENTS: From the Editors; Book Reviews: Girls’ Studies: Gendered Subjectivity and the Female Body: Discovering Agency and Power, by Brenda Boudreau; Mass Marketing and our Daughters, by Lise Mae Schlosser; Educating the Girl: Learning and Schooling in America ...and Elsewhere, by Rebekah Buchanan; Girls, Grrrls, Gurls, and the Tools They Use, by Lanette Cadle; ‘Othered’ Girls: Growing Up Between Two Worlds, by Sarah Hentges; Disruptive Girlhoods: Books on Aggression in Girls, by Jillian Hernandez; Reimagining Girlhood: Girls’ Writings and Self-Portrayals, by Sarah Myers; Great Reads for Young Girls, by Marge Loch-Wouters; What Adolescent Girls Read, by Elaine O’Quinn; Round-Up 2: Blogs and Other E-Tools for Women’s Studies; E-Sources on Women & Gender; New Reference Works in Women’s Studies; Periodical Notes; Items of Note; Books and Videos Recently Received; Index to Volume 28; Subscription Form
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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 | 0.003 | 0.004 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.260 | 0.115 |
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".