The Nation in children's literature: nations of childhood
Bibliographic record
Abstract
This book explores the meaning of nation or nationalism in children’s literature and how it constructs and represents different national experiences. The contributors discuss diverse aspects of children’s literature and film from interdisciplinary and multicultural approaches, ranging from the short story and novel to science fiction and fantasy from a range of locations including Canada, Australia, Taiwan, Norway, America, Italy, Great Britain, Iceland, Africa, Japan, South Korea, India, Sweden and Greece. The emergence of modern nation-states can be seen as coinciding with the historical rise of children’s literature, while stateless or diasporic nations have frequently formulated their national consciousness and experience through children’s literature, both instructing children as future citizens and highlighting how ideas of childhood inform the discourses of nation and citizenship. Because nation and childhood are so intimately connected, it is crucial for critics and scholars to shed light on how children’s literatures have constructed and represented historically different national experiences. At the same time, given the massive political and demographic changes in the world since the nineteenth century and the formation of nation states, it is also crucial to evaluate how the national has been challenged by changing national languages through globalization, international commerce, and the rise of English. This book discusses how the idea of childhood pervades the rhetoric of nation and citizenship, and how children and childhood are represented across the globe through literature and film.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.004 | 0.006 |
| Science and technology studies | 0.007 | 0.012 |
| Scholarly communication | 0.012 | 0.008 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".