Bibliographic record
Abstract
This book is a literary analysis of J.M. Barrie’s Peter Pan in all its different versions -- key rewritings, dramatisations, prequels, and sequels -- and includes a synthesis of the main critical interpretations of the text over its history. A comprehensive and intelligent study of the Peter Pan phenomenon, this study discusses the book’s complicated textual history, exploring its origins in the Harlequinade theatrical tradition and British pantomime in the nineteenth century. Stirling investigates potential textual and extra-textual sources for Peter Pan, the critical tendency to seek sources in Barrie’s own biography, and the proliferation of prequels and sequels aiming to explain, contextualize, or close off, Barrie’s exploration of the imagination. The sources considered include Dave Barry and Ridley Pearson’s Starcatchers trilogy, Régis Loisel’s six-part Peter Pan graphic novel in French (1990-2004), Andrew Birkin’s The Lost Boys series, the films Hook (1991), Peter Pan (2003) and Finding Neverland (2004), and Geraldine McCaughrean’s "official sequel" Peter Pan in Scarlet (2006), among others.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.021 |
| Scholarly communication | 0.008 | 0.008 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
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".