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Record W1925733712

Anéatah et Déranah, les jumelles d'Hochelaga : un cas de réécriture chez Eugène Achard

2007· article· fr· W1925733712 on OpenAlexaboutno aff
Marilène Gill

Bibliographic record

VenueCanadian Children's Literature / Littérature canadienne pour la jeunesse · 2007
Typearticle
Languagefr
FieldSocial Sciences
TopicCanadian Identity and History
Canadian institutionsnot available
Fundersnot available
KeywordsHumanitiesArtAppropriationLegendMythologyFolkloreEthnologyPhilosophyArt historyLiteratureHistoryLinguistics
DOInot available

Abstract

fetched live from OpenAlex

Summary: Marilene Gill analyzes a First-Nations folktale published by Eugene Achard in 1943: Aneatah et Deranah, les jumelles d'Hochelaga . It is, in fact, a case of cultural appropriation based on a rewriting of a lesser-known folktale from the Grimm brothers. The article examines how a German narrative, thanks to the use of clever literary devices, can become a seemingly authentic Amerindian legend that explains the mythical origins of the Huron and Iroquois nations, and concurs with the traditional French-Canadian historical discourse. Resume: Marilene Gill analyse un conte amerindien d'Eugene Achard, Aneatah et Deranah, les jumelles d'Hochelaga , publie au cours de la Seconde Guerre mondiale. Dans cette historie adaptee d'un recit des freres Grimm, Blanchette et Rosette, l'auteur s'est livre a un travail d'appropriation culturelle complexe et retors. L'article analyse comment un recit folklore europeen peut devenir, grâce aux ruses de l'ecriture, une legende amerindienne, voire un mythe fondateur, dont l'authenticite paraissait pour le moins convaincante pour les lecteurs canadiens-francais de l'epoque.

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)0.001
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 score0.945
Threshold uncertainty score0.108

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0090.007
Scholarly communication0.0040.002
Open science0.0000.002
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0040.000

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 head0.005
GPT teacher head0.208
Teacher spread0.203 · 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
Published2007
Admission routes1
Has abstractyes

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