How Did Peter Pan Grow Up Into A Children's Story?
Bibliographic record
Abstract
The tale of Peter Pan by J. M. Barrie (1860–1937) has found its way to a children's audience despite the tensions it elicits around the idea of childhood. After the novel "The Little White Bird" (1902), where Peter appears for the first time, and its stage adaptation "Peter Pan" (1904), both explicitly intended for adults, Barrie arrived at his final version for children published in 1911, the novel "Peter and Wendy", through a tormented history of reworkings. \nMy research aims at exploring the significance of Barrie’s constant reshaping of the Peter Pan materials in order to recast the story for a young audience. Moreover, I will investigate as to what extent the ambiguity and instability of the Peter Pan fictions have been tamed in its school and cinema adaptations. These adaptations have deployed strategies to counter Barrie’s rebellious attitude against the didacticism and pedagogic expectations which are conventionally associated with children’s literature. As will become clear in the following, Barrie challenged the traditional barriers between adults and children on many points. Nevertheless, Peter Pan has been singled out to become a cultural icon of children’s literature – hence, my central questions: How, exactly, did Peter Pan grow up into a children’s story? What conflicting discourses and ideologies concerning childhood may be seen to inform Barrie’s different versions of the Peter Pan story?
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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 | 0.003 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.008 | 0.013 |
| Scholarly communication | 0.009 | 0.012 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.002 | 0.006 |
| Insufficient payload (model declined to judge) | 0.004 | 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".