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Record W2241252882 · doi:10.1353/trh.2012.0019

작가, 소설, 인생의 서사적 지리학 - 마거릿 로렌스의 『예언자들』 / The Epic Geography of Writer, Fiction and Life:Margaret Laurence’s The Diviners

2012· article· ko· W2241252882 on OpenAlexaboutno aff
Myungok Yoon

Bibliographic record

VenueTrans-Humanities · 2012
Typearticle
Languageko
FieldArts and Humanities
TopicShort Stories in Global Literature
Canadian institutionsnot available
Fundersnot available
KeywordsEPICPilgrimageCulminationNarrativeIdentity (music)LiteratureHistoryArtArt historyAesthetics

Abstract

The Diviners, written by Canadian novelist Margaret Laurence, is the last of her five Manawaka novels and represents the culmination of all the trends shown throughout the Manawaka cycle. It furthers Laurence’s emphasis on self-empowerment for women, especially the female artist, and intensifies her use of innovative narrative strategies. It is patterned as a pilgrimage along epic lines and features a protagonist and writer, Morag Gunn, and her quest for identity. Through a spiritual journey, Morag Gunn explores herself as a woman, a mother, and a writer in her memories of the past and her vision of the future.

Stored with the screening record, where it is evidence for the labels above.

How this classification was reachedexpand

The three-model screen

all 5,600 screened works →

All three models called this out of scope.

stratum: about_only · design weight: 3321.24 (the sample is stratified; any rate computed without the weight is wrong)
Claude Opus 4.8OUT
genre: conceptual
about Canada: no
confidence: high

Literary criticism of Margaret Laurence's The Diviners; the object is a novel.

GPT-5.6 (high)OUT
genre: conceptual
about Canada: no
confidence: high

This literary analysis interprets Margaret Laurence's fiction and does not study research practice.

Grok 4.5OUT
genre: conceptual
about Canada: no
confidence: high

Literary criticism of Margaret Laurence’s novel; humanities domain analysis.

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)0.003
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: Other · Consensus signal: Other
Teacher disagreement score0.192
Threshold uncertainty score0.000

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0200.014
Scholarly communication0.0070.003
Open science0.0010.003
Research integrity0.0020.003
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 head0.022
GPT teacher head0.221
Teacher spread0.199 · 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
GenreOther

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
Published2012
Admission routes1
Has abstractyes

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