Bibliographic record
Abstract
Fairy Tales Framed: Early Forewords, Afterwords, and Critical Words. Edited by Ruth B. Bottigheimer. Reviewed by Armando Maggi, University of Chicago. Afghan Folktales from Herat: Persian Texts in Transcription and Translation by Youli Ioannesyan. Reviewed by Margaret Mills, Ohio State University. World on a Maple Leaf: A Treasury of Canadian Multicultural Folktales. Edited by Asma Sayed and Nayanika Kumar. Reviewed by Martin Lovelace, Memorial University. La donna serpente by Carlo Gozzi. Edited by Giulietta Bazoli. Reviewed by Tatiana Korneeva, Freie Universität, Berlin. Wit als Sneeuw, Zwart als Inkt: De Sprookjes van Grimm in de Nederlandstalige Literatuur by Vanessa Joosen. Reviewed by Theo Meder, Meertens Instituut, Amsterdam. Voices of the People in Nineteenth-Century France by David Hopkin. Reviewed by Jack Zipes, University of Minnesota. The Russian Folktale by Vladimir Yakovlevich Propp. Edited and translated by Sibelan Forrester. Reviewed by Lee Haring, Brooklyn College. Textualité et intertextualité des contes: Perrault, Apulée, La Fontaine, Lhéritier... by Ute Heidmann and Jean-Michel Adam. Reviewed by Lewis C. Seifert, Brown University. Meseterápia: Mesék a gyógyításban és a mindennapokban by Ildikó Boldizsár and Mesepszichológia: Az érzelmi intelligencia fejlesztése gyermekkorban by Annamária Kádár. Reviewed by Anna Kérchy, University of Szeged. Stranger Magic: Charmed States and the Arabian Nights by Marina Warner. Reviewed by Dominique Jullien, University of California, Santa Barbara. A Card from Angela Carter by Susannah Clapp. Reviewed by Mayako Murai, Kanagawa University. Snotty Saves the Day and Lily the Silent by Tod Davies. Reviewed by Carmen Nolte, University of Hawai’i, Mānoa. Brave. Directed by Mark Andrews, Brenda Chapman, and Steve Purcell. Performed by Kelly Macdonald, Billy Connolly, and Emma Thompson. Reviewed by Christy Williams, Hawai‘i Pacific University.
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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 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.007 | 0.004 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.408 | 0.375 |
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".