Comparing Youth Gang Involvement Near the U.S. Mexico-Border to Other Communities: Is Youth Gang Involvement a Major U.S. Border Issue?
Bibliographic record
Abstract
Background Little is known about the proximity to the U.S. – Mexico border on youths and the impact of transnational gang activity in these areas that might influence adolescents to gravitate toward gang involvement.Objectives To fill this gap in the literature by investigating youth gang involvement in Arizona’s border counties and non-border counties.Methods Youth of the 2022 Arizona Youth Survey data (n = 48469) were compared through Bivariate and regression analyses to examine the relationship between border versus non-border youth gang involvement.Results Bivariate analyses reveal a significant association when comparing gang involvement between those youth who reside in border counties compared to those that do not. Multivariate analysis results indicate that population density is a major predictor of youth gang involvement and not proximity to the Mexico border.Conclusion Youth residing in border counties are significantly less likely to report being gang-involved when compared to youth in other counties.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".