Extraordinary Navigators: An Examination of Three Heroines in Neil Gaiman and Dave McKean's Coraline, The Wolves in the Walls, and MirrorMask
Bibliographic record
Abstract
Few author/illustrator teams have rendered a child's journey through the dark world with such psychological and emotional complexity as the duet of Neil Gaiman and Dave McKean. Their stories are as eerie, scary, and thrilling for the child reader as they are for the adult. But more impressive than their rendering of ghastly fantasy worlds is their creation of the intrepid heroines who navigate them. With their novella Coraline, their picturebook The Wolves in the Walls, and their illustrated film script MirrorMask, Gaiman and McKean present their readers with three wildly courageous, loyal, resourceful, and emotionally strong female protagonists, who are resolved to rescue their families and homes from chaos and evil. Thrown into realms of distortion and illusion, Coraline, Lucy, and Helena glean information from their intuition and dreaming, and skillfully manipulate art, language, and narrative, in order to discern, define, and reclaim borders. Ultimately, these powerful heroine...
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.029 | 0.019 |
| Scholarly communication | 0.009 | 0.006 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.003 | 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".