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Record W2946639102 · doi:10.1177/0093854819848803

The Prevalence of Sexual and Gender Minority Youth in the Justice System: A Systematic Review and Meta-Analysis

2019· review· en· W2946639102 on OpenAlexaff
Melissa R. Jonnson, Brian M. Bird, Shanna M. Y. Li, Jodi L. Viljoen

Bibliographic record

VenueCriminal Justice and Behavior · 2019
Typereview
Languageen
FieldPsychology
TopicLGBTQ Health, Identity, and Policy
Canadian institutionsSimon Fraser University
Fundersnot available
KeywordsSexual minorityEconomic JusticeMeta-analysisEthnic groupPoison controlInjury preventionSuicide preventionPsychologyHuman factors and ergonomicsCriminal justiceDemographyCriminologyMedicineSocial psychologySexual orientationPolitical scienceEnvironmental healthSociology

Abstract

fetched live from OpenAlex

Theoretical models, such as the minority stress model, suggest that sexual and gender minority (SGM) youth may be overrepresented in the justice system. However, few studies have examined rates of SGM youth in the system, and even fewer have compared them with rates of these youth in the broader community. To obtain a more accurate estimate, we conducted a systematic review and meta-analysis of 31,258 youths and compared rates of SGM youth in the justice system with those in the community. Contrary to claims that SGM youth are overrepresented generally, this review suggests that sexual minority girls, specifically, are disproportionally involved in the justice system. Rates of involvement appeared to differ across ethnic subgroups of sexual minority youth, and evidence is inconclusive regarding the prevalence of gender minority youth in the system. Implications of these findings for researchers and justice system professionals are discussed.

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

Direct model labels (unvalidated)

Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.

Model armCategoriesStudy designConfidence
gemmano category
Domain: not available · Genre: Review
About the Canadian research system: no · About a Canadian topic: no
Meta-analysislow
gptno category
Domain: not available · Genre: Review
About the Canadian research system: no · About a Canadian topic: no
Systematic reviewhigh
models splitAgreement compares identical category sets and study designs across arms.

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)0.003
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.988
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0040.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
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 head0.396
GPT teacher head0.480
Teacher spread0.084 · 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

Labeled directly by 2 models reading the full record.

The models applied no category: nothing in the taxonomy fit this work.

The models disagree on parts of this classification; every voice is preserved in the section at the end of the page.

Study designMeta-analysis · Systematic review
Domainnot available
GenreReview

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

Citations27
Published2019
Admission routes1
Has abstractyes

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