Self-Control, Social Consequences, and Criminal Behavior: Street Youth and the General Theory of Crime
Bibliographic record
Abstract
Using a sample of 400 homeless street youth, this article examines the role that self-control plays in the generation of crime and drug use as well as its link to negative social consequences. It also explores if these social consequences are themselves related to crime as predicted in strain and differential association theory, or if their impact is eliminated by the presence of low self-control. The results reveal that low self-control predicts a range of criminal behaviors as well as drug use. Consistent with the general theory, low self-control influences the association with deviant peers, the adoption of deviant values, length of unemployment, and length of homelessness. However, the results reveal that a number of social consequences; including deviant peers, deviant values, length of homelessness, relative deprivation, and monetary dis-satisfaction; have an effect on criminal behavior and drug use controlling for self-control lending support to other theoretical perspectives. Results are discussed in terms of developing the general theory by incorporating other perspectives.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".