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Record W4247139472 · doi:10.32920/ryerson.14647947.v1

The monster in the dark: the monstrous maternal and abject black mother in Toni Morrison's Beloved

2021· preprint· en· W4247139472 on OpenAlexaff
Nikta Sadati

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldHealth Professions
TopicHomelessness and Social Issues
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsOppressionMonsterNarrativeGender studiesSociologyRacismPsychoanalysisHistoryLawArtPolitical scienceArt historyLiteraturePsychology

Abstract

fetched live from OpenAlex

[Introduction]: "Toni Morrison’s Beloved (1987) is centred on Sethe, a mother and an escaped slave.Through a non-linear narrative, the novel follows Sethe through her traumatizing memories of Sweet Home–the plantation in which she was a slave–as well as I24, her new home after her escape. Set in 1856 pre-abolition America, Beloved follows the aftermath of Sethe’s murder of her baby, Beloved, and the haunting of I24 by Beloved’s ghost. Sethe’s infanticide is revealed to the reader through a series of memories and stories from different neighbours of I24 and acquaintances of Sethe. Sethe is presented as a monstrous mother as she appears to her family and neighbours as detached from her maternal love and kinship. Throughout this essay, the research questions I will answer are the following: Who defines motherhood? How is grief exercised by a subject who is made abject? How is the concept of the monstrous maternal rooted in racial oppression Sethe’s murder of her child is seen as a cold and irrational act of violence; however, Beloved’s representation of black motherhood and slavery serves to complicate the narrative of the monstrous maternal."

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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.051
Threshold uncertainty score0.101

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0190.014
Scholarly communication0.0050.003
Open science0.0010.005
Research integrity0.0020.006
Insufficient payload (model declined to judge)0.0040.001

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 head0.040
GPT teacher head0.389
Teacher spread0.350 · 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
Published2021
Admission routes1
Has abstractyes

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