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Record W2662146564

Dwelling in Intimate and Grand Spaces: Natural, Bodily and Narrative Landscapes in Alice Munro’s “What Do You Want to Know For?”

2017· article· en· W2662146564 on OpenAlexaff
Margaret Steffler

Bibliographic record

VenueLiterary Geographies · 2017
Typearticle
Languageen
FieldArts and Humanities
TopicShort Stories in Global Literature
Canadian institutionsTrent University
Fundersnot available
KeywordsNarrativeMemoirNatural (archaeology)AestheticsSpace (punctuation)ArtLiteratureArt historyPhilosophyHistoryArchaeology
DOInot available

Abstract

fetched live from OpenAlex

This article addresses relationships between natural landscapes, narrative style and women’s bodyscapes in Alice Munro’s The View from Castle Rock (2006), concentrating on the final short story, “What Do You Want to Know For?” Focusing on theories of space and place-relations by Yi-Fu Tuan, E. Relph, Henri LeFebvre and Wesley A. Kort, the discussion examines the narrator’s return home in these memoir-like stories. The structures and shapes of these narratives of the landscape, the woman’s body and the short story stress dynamic processes and evolving presences rather than permanence or stability. The article, referring to Martin Heidegger’s concept of dwelling, argues that through sparing and preserving her home-place, the narrator is freed from the compulsion to dig into the earth, the past and memory for knowledge and answers. The mounded shapes of the kame moraine, crypt and narrator’s breast, which connect landforms, mortality and the woman’s body, allow for the opening of intimate space into grand space, freeing the narrator from curiosity and the need to know .

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: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.981
Threshold uncertainty score0.037

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0150.015
Scholarly communication0.0040.003
Open science0.0010.006
Research integrity0.0010.002
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 head0.008
GPT teacher head0.243
Teacher spread0.235 · 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 designQualitative
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
Published2017
Admission routes1
Has abstractyes

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