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GENERAL STRAIN, STREET YOUTH AND CRIME: A TEST OF AGNEW'S REVISED THEORY*

2004· article· en· W1989438702 on OpenAlexaff
Stephen W. Baron

Bibliographic record

VenueCriminology · 2004
Typearticle
Languageen
FieldSocial Sciences
TopicCrime Patterns and Interventions
Canadian institutionsQueen's University
Fundersnot available
KeywordsGeneral strain theoryAttributionPsychologyCriminal behaviorTest (biology)UnemploymentSocial psychologyCriminologyYouth unemploymentRelative deprivationStrain (injury)Juvenile delinquencyMedicine

Abstract

fetched live from OpenAlex

Using a sample of homeless street youth, this research examines how specific forms of strain–emotional abuse, physical abuse, sexual abuse, homelessness and being a victim of robbery, violence or theft, relative deprivation, monetary dissatisfaction and unemployment–lead to crime and drug use. It also explores how strain is conditioned by deviant peers, deviant attitudes, external attributions, self‐esteem and self‐efficacy. The results reveal that all ten types of strain examined can lead to criminal behavior either as main effects or when interacting with conditioning variables. The results are discussed in light of general strain theory and suggestions are offered for future research on this topic.

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)0.012
metaresearch head score (Gemma)0.038
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.012
Threshold uncertainty score0.066

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0120.038
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0020.002
Science and technology studies0.0010.004
Scholarly communication0.0020.003
Open science0.0020.004
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0070.001

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 head0.130
GPT teacher head0.361
Teacher spread0.231 · 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

Citations328
Published2004
Admission routes1
Has abstractyes

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