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Record W2468825987

Good Enough, Bad Enough, Animal, Monster: Mothers in Alice Munro’s The Love of a Good Woman

2015· article· en· W2468825987 on OpenAlexaffvenue
Chantel Lavoie

Bibliographic record

VenueStudies in Canadian Literature · 2015
Typearticle
Languageen
FieldArts and Humanities
TopicShort Stories in Global Literature
Canadian institutionsRoyal Military College of Canada
Fundersnot available
KeywordsAmbivalenceMonsterDepictionPsychoanalysisNew WomanArtGender studiesSociologyPsychologyArt historyLiterature
DOInot available

Abstract

fetched live from OpenAlex

This essay considers the dark ambivalence of the monstrous mother in Alice Munro’s work, in particular in her 1998 collection, The Love of a Good Woman .  In these eight stories — set from the 1940s through the 1970s — we encounter sickly mothers, stepmothers, mothers who abandon their children by leaving their husbands, and aunts who try to wrest a mother’s duties from her. Whereas we see such monsters everywhere in Munro’s many books, in this collection especially Munro suggests that mothers — in their particular intimate experience of the monstrosity of birth and how it introduces death into the world — cannot help embodying monstrosity, nor should they be condemned for trying to escape it.  Employing theories of the good-enough mother by psychoanalyst D.W. Winnicott, and Munro’s depiction of various functions of motherhood, including breastfeeding, this essay considers various monstrous maternal figures in The Love of a Good Woman and Munro’s emphasis therein on the inevitable space between being human and being animal that being a mother forces a woman to inhabit, along with the sometimes monstrous consequences of that role.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.945
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.033
GPT teacher head0.277
Teacher spread0.244 · 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.

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

Citations1
Published2015
Admission routes2
Has abstractyes

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