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Record W7014226253

The Pedagogy of the Sasquatch: Imagining the Aboriginal without Feathers in Eden Robinson’s Monkey Beach

2008· article· en· W7014226253 on OpenAlexaboutno aff

Bibliographic record

VenueRUC (Universidade Da Coruña) · 2008
Typearticle
Languageen
FieldArts and Humanities
TopicEcocriticism and Environmental Literature
Canadian institutionsnot available
Fundersnot available
KeywordsVisionColonialismCONTESTNegotiationMythologyReading (process)Space (punctuation)
DOInot available

Abstract

fetched live from OpenAlex

[Abstract] This paper analyzes Canada’s foundational myths of Nature and Natives vis-à-vis recent negotiations of that same relationship by Aboriginal writers, and will offer a reading of Eden Robinson’s novel Monkey Beach (2000) as paradigmatic of those changes. This novel, I will argue, exposes the contradictions of a colonial discourse that has produced visions of the natural/native space as void of meaning, as claustrophobic, and as filled with unknown threats (the famous “garrison mentality”). By focusing on the culture-specific figure of the Sasquatch, Robinson’s text incorporates and analyzes those colonial notions side by side Aboriginal beliefs of the mythic and the supernatural. In the process, new meanings of nature and aboriginality will come about that contest those previously thought of as traditional or representative of the national ethos. At the same, I will try to show how the novel manages to avoid the common practices of stereotyping and/or essentializing aboriginality.

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)0.002
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: none
Teacher disagreement score0.643
Threshold uncertainty score0.710

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0220.030
Scholarly communication0.0060.003
Open science0.0020.004
Research integrity0.0030.005
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 head0.015
GPT teacher head0.230
Teacher spread0.215 · 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
Published2008
Admission routes1
Has abstractyes

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