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Record W4382365238 · doi:10.1386/fict_00070_1

Reading the ‘wordless unease’ in Margaret Atwood’s ‘Death by Landscape’

2023· article· en· W4382365238 on OpenAlexaboutno aff
Eleonora Togyer

Bibliographic record

VenueShort Fiction in Theory and Practice · 2023
Typearticle
Languageen
FieldArts and Humanities
TopicUtopian, Dystopian, and Speculative Fiction
Canadian institutionsnot available
Fundersnot available
KeywordsWildernessNarrativeAdventureReading (process)AestheticsPerformative utteranceThe ImaginaryLiteratureSociologyRepresentation (politics)ArtHistoryVisual artsArt historyPoliticsPsychoanalysisPsychologyLawPolitical science

Abstract

fetched live from OpenAlex

This article examines the way Margaret Atwood’s short story ‘Death by Landscape’ (1991) engages with the representational strategies of Canada’s celebrated Group of Seven artists. I situate my reading of Atwood’s work first within aesthetics, focusing on her subtle problematization of the masculine ideology and wilderness aesthetic of the Group of Seven. I argue that Atwood unsettles the dominant, virulently male tradition of representation of the wilderness by uncovering an alternative female narrative through an ekphrastic engagement with the paintings. By doing so she not only dismantles the concept of wilderness both as a physical space that women have limited access to and as an imaginary construct; but at the same time she also reconfigures the structure and the content of wilderness stories, and in fact the concept of wilderness itself. Atwood offers a counter-discursive revision of the male adventure and maturation story by deconstructing and restructuring traditional narrative practices to render the female experience visible. This article hopes to show that Atwood expands the possibilities of the adventure story and wilderness writing and creates room for a female version of the maturation story with a fundamentally different aesthetic.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.969
Threshold uncertainty score0.622

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.032
GPT teacher head0.295
Teacher spread0.262 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
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

Citations1
Published2023
Admission routes1
Has abstractyes

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