Understanding children's literature : key essays from the second edition of the International companion encyclopedia of children's literature
Bibliographic record
Abstract
1. Introduction: The Expanding World of Children's Literature Studies Peter Hunt, Cardiff University 2. Theorising and Theories: How Does Children's Literature Exist? David Rudd, Bolton Institute 3. Critical Tradition and Ideological Positioning Charles Sarland, Liverpool John Moores University 4. The Setting of Children's Literature: History and Culture Tony Watkins, University of Reading 5. Analysing Texts: Linguistics and Stylistics John Stephens, Macquarie University 6. Readers, Texts, Contexts: Reader-Response Criticism Michael Benton, Professor Emeritus, University of Southampton 7. Reading the Unconscious: Psychoanalytical Criticism Hamida Bosmajian, Seattle University 8. Feminism Revisited Lissa Paul, University of New Brunswick 9. Decoding the Images: how Picture Books Work Perry Nodelman, University of Winnipeg 10. Bibliography: the Resources of Children's Literature Matthew Grenby, University of Newcastle upon Tyne 11. Understanding Reading and Literacy Sally Yates, Literacy Consultant UK 12. Intertextuality and the Child Reader Christine Wilkie-Stibbs, University of Warwick 13. Healing Texts: Bibliotherapy and Psychology Hugh Crago, Co-Editor Australia and New Zealand Journal of Family Therapy 13. Theory into Practice: the Views of the Authors Peter Hunt, Cardiff University General Bibliography Glossary Index
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 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.008 | 0.015 |
| Science and technology studies | 0.004 | 0.003 |
| Scholarly communication | 0.008 | 0.006 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.021 | 0.005 |
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".