From Neverland to Narnia - An Ecocritical Study of Child Character’s Interaction with Wild Nature in J.M Barrie’s ‘Peter Pan’ and C.S. Lewis’ ‘The Lion, the Witch and the Wardrobe’.
Bibliographic record
Abstract
This thesis explores how the interplay between nature and imagination in J.M. Barrie’s Peter Pan and C.S. Lewis’ The Lion, the Witch and the Wardrobe affects the young protagonists’ relationship with the natural environment of Neverland and Narnia. The primary focus of this thesis is to show how the characters’ interaction with the two landscapes, through means of imagination, may lead to a more environmentally conscious relationship with their surroundings. While most ecocritical studies of the novels today focus on the negative sides of Barrie’s and Lewis’ portrayal of nature, this thesis examines the positive outcomes of the children’s adventures in Neverland and Narnia. By engaging with examples from romantic poetry, this thesis suggests how it is possible to form connections between the Romantic imagination and the use of imagination amidst nature in the novels. To better illustrate this, I will also offer a study of selected movie adaptations of the novels.
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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.010 | 0.014 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.004 |
| Insufficient payload (model declined to judge) | 0.002 | 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".