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Record W4402055809 · doi:10.4324/9781003006770

The Routledge Companion to Gender and Borderlands

2024· book· en· W4402055809 on OpenAlexaboutno aff
Zalfa Feghali, Deborah Toner

Bibliographic record

Venuenot available
Typebook
Languageen
FieldSocial Sciences
TopicHistorical Gender and Feminism Studies
Canadian institutionsnot available
Fundersnot available
KeywordsHistorySociologyGender studiesMedia studies

Abstract

fetched live from OpenAlex

The chapter examines the memoir Mean (2017) by Chicana author Myriam Gurba and the novel The Break (2016) by Métis writer Katherena Vermette. Through textual analysis, the chapter shows how these two writers resist dominant ideas concerning “psychopathy” that perpetuate gendered, raced, and classed stereotypes. The chapter argues that these authors unsettle psychopathy as something situated in the individual to depict the United States and Canada as psychopathic structures that create the conditions for certain forms of violence to flourish. Vermette and Gurba’s work contributes to the body of Indigenous and Chicana writing that rejects, rewrites, and resists misleading images of violence.

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)0.002
metaresearch head score (Gemma)0.004
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 score0.063
Threshold uncertainty score0.212

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.005
Science and technology studies0.0080.014
Scholarly communication0.0110.009
Open science0.0010.004
Research integrity0.0040.006
Insufficient payload (model declined to judge)0.0630.015

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 head0.047
GPT teacher head0.323
Teacher spread0.276 · 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

Citations3
Published2024
Admission routes1
Has abstractyes

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