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Record W3009323001 · doi:10.3366/gothic.2020.0038

‘The worst loups-garous that one can meet’: Reading the Werewolf in the Canadian ‘Wilderness’

2020· article· en· W3009323001 on OpenAlexaboutno aff
Kaja Franck

Bibliographic record

VenueGothic Studies · 2020
Typearticle
Languageen
FieldArts and Humanities
TopicFolklore, Mythology, and Literature Studies
Canadian institutionsnot available
Fundersnot available
KeywordsWildernessTrilogyFolkloreNarrativeLiteratureDepictionHistoryArtReading (process)Art historyPhilosophy

Abstract

fetched live from OpenAlex

Ginger Snaps (2000) has been recognised as a significant example of feminist horror. This article analyses the final film in the trilogy, Ginger Snaps Back: The Beginning (2004). On first appearance, Ginger Snaps Back reacts to the ending of the first film, in which Brigitte kills her lupine sister Ginger. Set in the nineteenth century, the film draws on Canadian Gothic tropes with the two sisters trapped in an isolated fort, surrounded by frozen forest. In doing so, it echoes another Canadian werewolf narrative, Henry Beaugrand's ‘The Werwolves' (1898). Beaugrand's story opens with a group of settler-colonisers spending the Christmas period in Fort Richelieu, Quebec. This location evokes North American fears, and the representation of the wooded wilderness as full of wild beasts and wild men. Beaugrand collapses the ‘wild beasts’ and ‘wild men’ into one hybrid monster. By comparing the depiction of werewolves in Ginger Snaps Back and Beaugrand's story, this article uncovers the implications of ignoring and appropriating Native Canadian folklore.

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 imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.057
Threshold uncertainty score0.412

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0400.023
Scholarly communication0.0070.003
Open science0.0020.002
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.0070.000

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.

Opus teacher head0.101
GPT teacher head0.265
Teacher spread0.164 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2020
Admission routes1
Has abstractyes

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