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Record W1967190663 · doi:10.1177/1524838002238944

Street Youth Violence And Victimization

2003· article· en· W1967190663 on OpenAlexaff
Stephen W. Baron

Bibliographic record

VenueTrauma Violence & Abuse · 2003
Typearticle
Languageen
FieldHealth Professions
TopicHomelessness and Social Issues
Canadian institutionsQueen's University
Fundersnot available
KeywordsPovertyPoison controlPsychologySuicide preventionHuman factors and ergonomicsCriminologySexual violenceInjury preventionSocial psychologyEnvironmental healthPolitical scienceMedicineLaw

Abstract

fetched live from OpenAlex

The article reviews the literature surrounding street youth violence and victimization. It examines the role backgrounds of physical and sexual victimization play in street youth[#x2019]s taking to the street and their link to violent behaviors once there. It reveals that violent home experiences educate street youth to use force to settle disputes and provide cultural rules that support violence. On the street, these rules are broadened and reinforced by poverty, the threat of victimization, violent peers, and immersion in an environment where violence is the favored method of dispute resolution. These home and street experiences also serve to increase the risk of violent victimization on the street. These youth[#x2019]s risky lifestyles, deviant subsistence strategies, deviant peers, and involvement in violence all serve to increase the likelihood of sexual and physical victimization. Policy implications of the findings 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

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.008
Threshold uncertainty score0.025

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0020.002
Scholarly communication0.0020.002
Open science0.0000.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0080.001

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 head0.044
GPT teacher head0.358
Teacher spread0.313 · 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 designObservational
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

Citations99
Published2003
Admission routes1
Has abstractyes

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