Bibliographic record
Abstract
A ccording to a Toronto film critic, the Canadian film Ginger Snaps (2001) puts a “post-Buffy spin on an old familiar tale” (Harkness, 2001:99). The tale is of the werewolf, or, as it is referred to more properly, and consistently, throughout the film, lycanthrope; from the Greek lukanthropia , meaning lukos , wolf, and anthropos , man. It is an old tale indeed, dating back at least to Pliny. And while modern werewolf chronicles are not foreign to celluloid, director John Fawcett’s Ginger Snaps ups the ante with a parallel tale of the horrors of puberty and high school in suburban Toronto. This much (aside from the Toronto part) it does share with Buffy the Vampire Slayer . But in Fawcett’s film, the lycanthrope is not a “man” transformed into beast, but a teenaged girl, already with a lust for the morose, morphing into beastly form and sexual awakening after being attacked on the day she first begins menstruation—by a creature who’s been doing in the neighborhood dogs. These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.011 | 0.005 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.041 | 0.005 |
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".