Is It Who You Know in Prison That Counts? Exposure to Prison Gang Members and Criminal Careers
Bibliographic record
Abstract
Incarceration exposes inmates to a range of offenders with a variety of skillsets. Whether connections made in prison have lasting consequences for criminal careers, or are simply relationships made “for the stay,” is at the heart of this study. We examine the potential consequences of prison ties of a specific kind: connections to prison gang members. We rely on unique social network data drawn from a subsample of male participants from the Incarcerated Serious and Violent Young Offender Study who formed a prison gang between 2000 and 2010. Using data on daily interactions of inmates as captured by correctional agents, we examine if being part of a youth prison gang has long-term consequences for criminal careers – not just for gang members, but also for a subsample of non-gang members embedded within the prison gang network. We find that non-gang youth who had a smaller social distance to gang members had longer criminal careers than non-gang youth who were further away from gang members. These non-gang youth even had longer criminal careers than youth prison gang members.
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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 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".