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Record W2997459384 · doi:10.1093/bjc/azz079

‘I Did What I Had to Do’: Loyalty and Sacrifice in Girls’ Narratives of Homicide in Southern Brazil

2019· article· en· W2997459384 on OpenAlexaff
Natália Otto

Bibliographic record

VenueThe British Journal of Criminology · 2019
Typearticle
Languageen
FieldSocial Sciences
TopicCriminal Justice and Corrections Analysis
Canadian institutionsUniversity of Toronto
FundersCoordenação de Aperfeiçoamento de Pessoal de Nível Superior
KeywordsNarrativeHabitusGender studiesFemininitySociologyMasculinityDilemmaNarrative inquirySacrificeHomicideCriminologyPoison controlSuicide preventionHistorySocial science

Abstract

fetched live from OpenAlex

Abstract This paper examines how criminalized teenage girls who have committed homicide reconcile violent practices with self-conceptions of femininity in their personal narratives. Data come from 13 biographical interviews with adolescent girls incarcerated in Porto Alegre, Brazil. Drawing from Bourdieusian theory and narrative criminology, I examine how gendered social structures shape how girls produce intelligible and morally coherent accounts of their crimes. I found that girls share a narrative habitus that allows for three different frames to make sense of violence: violence as a gendered resource, as a gendered failure and as a gendered dilemma. This paper contributes to a growing feminist narrative criminology that investigates how personal narratives of violence are embedded in gendered social structures.

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)0.004
metaresearch head score (Gemma)0.010
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.032
Threshold uncertainty score0.064

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.010
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0100.013
Scholarly communication0.0050.004
Open science0.0010.006
Research integrity0.0020.003
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 head0.024
GPT teacher head0.305
Teacher spread0.281 · 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 designQualitative
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

Citations9
Published2019
Admission routes1
Has abstractyes

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