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<b>Abjection and violence in <i>Monoceros</i>, by Suzette Mayr

2015· article· en· W1913952839 on OpenAlexaboutno aff
Liane Schneider

Bibliographic record

VenueActa Scientiarum Language and Culture · 2015
Typearticle
Languageen
FieldArts and Humanities
TopicLiterature, Culture, and Criticism
Canadian institutionsnot available
FundersCoordenação de Aperfeiçoamento de Pessoal de Nível Superior
KeywordsNarrativeFeelingPsychologyNorm (philosophy)Identity (music)Gender studiesSocial psychologyPsychoanalysisSociologyAestheticsArtPolitical scienceLiteratureLaw

Abstract

fetched live from OpenAlex

Through the analysis of Monoceros (2011), a novel by Canadian contemporary writer Suzette Mayr, we examine the entanglement between concepts of violence and abjection in literature. Mayr presents several characters that come into contact as a result of a suicide committed by a previously bullied student of a Catholic school. With the narrative as a reference, we propose to discuss the growing violence inside the school system in contemporary times, in this case as a result of sexual intolerance. Works by Nan Stein and Melinda York, who address the imposition of too strict gender roles on female and male students as one of the causes for violent outcomes among youngsters, will be our main theoretical references. We also discuss the topic of desire and abjection, mainly developed by Kristeva and Kulzbach, as illuminating perspectives for the analysis of the selected novel. We suggest that in Monoceros bullying is performed to guarantee fixed and binary models of gender identity, which ends up by promoting low self-esteem and feelings of awkwardness on individuals defined as different from the norm.

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: Other · Consensus signal: none
Teacher disagreement score0.156
Threshold uncertainty score0.309

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 studies0.0150.022
Scholarly communication0.0050.002
Open science0.0010.003
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0020.000

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 head0.009
GPT teacher head0.217
Teacher spread0.208 · 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
Published2015
Admission routes1
Has abstractyes

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