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Record W4317830315 · doi:10.1177/00111287231151593

Unraveling the Sexual Victimization of Sex Workers: A Latent Class Analysis Through the Lens of Environmental Criminology

2023· article· en· W4317830315 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueCrime & Delinquency · 2023
Typearticle
Languageen
FieldSocial Sciences
TopicSex work and related issues
Canadian institutionsUniversité LavalInternational Centre for Comparative CriminologySimon Fraser University
Fundersnot available
KeywordsLegal guardianLatent class modelSituational ethicsCriminologyPsychologySexual violenceCrime preventionHarassmentSocial psychologyPolitical scienceLawComputer science

Abstract

fetched live from OpenAlex

Past research on violence against sex workers has contributed to our understanding of this phenomenon yet, often do not offer concrete preventative measures. The current study aims to investigate this issue through an environmental criminology perspective, and to identify measures that can be implemented to decrease violence through a situational crime prevention framework. Our sample consist of 402 French sex workers who experienced violent victimization (1990–2018). Latent class analysis revealed a four-class solution: (1) indoor/low-moderate guardianship, (2) outdoor/low guardianship, (3) mobile/low guardianship, and (4) mobile/moderate guardianship. Actionable crime prevention methods to mitigate the risk of violence suggested for each of the classes included pre-screening clients, installing panic buttons/closed-circuit television, offering self-defense and conflict management courses, and working in tandem.

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.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.064
Threshold uncertainty score0.377

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.070
GPT teacher head0.321
Teacher spread0.252 · 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