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Record W6967787000 · doi:10.5281/zenodo.13366746

Detetives transculturais: rompendo fronteiras na ficção criminal

2024· article· en· W6967787000 on OpenAlexaboutno aff

Bibliographic record

VenueZenodo (CERN European Organization for Nuclear Research) · 2024
Typearticle
Languageen
FieldArts and Humanities
TopicCrime and Detective Fiction Studies
Canadian institutionsnot available
Fundersnot available
KeywordsEulogyIdentity (music)MulticulturalismOfficerWhite (mutation)Race (biology)WifeRelation (database)Ethnic group

Abstract

fetched live from OpenAlex

Abstract: This article analyzes Lucha Corpi’s Eulogy for a Brown Angel (1992) and T. E. Wilson’s Mezcalero (2015). We seek to understand how their detectives, Gloria Damasco and Ernesto Sánchez, respectively, raise questions of identity, especially in relation to gender and ethnicity, and also bring multiculturalism and subalternity into their contexts. Corpi was born in Mexico and lives in the United States, while Wilson was born in Canada and lives in Mexico, and both write their detective fiction in English. The writing of these authors is a space of cultural resistance, expression of differences and alternative identity representations of members of groups marginalized by dominant society. While Damasco, a Chicana woman, begins her journey in criminal investigation as an amateur, reconciling her roles as wife and mother, Sánchez, a Trans man, begins his career as a police officer in Canada and later becomes a private investigator in Mexico. With the help of Schindler (2023) and Portilho (2009, 2016), among others, we analyze how the intersections between these two characters are approached, especially with regard to gender issues, highlighting how they subvert detective literature, which in its most widespread facet is still predominantly a straight cis white male narrative. Keywords: Detective fiction. Crime narrative. Identity. Transculturality.

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)0.004
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: Empirical · Consensus signal: Empirical
Teacher disagreement score0.011
Threshold uncertainty score0.026

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0110.013
Scholarly communication0.0060.002
Open science0.0010.004
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 head0.085
GPT teacher head0.266
Teacher spread0.181 · 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
Published2024
Admission routes1
Has abstractyes

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