When You're Out, You're Not Really Out: Exiting Strategies Among Gang-Affiliated Chicanas
Bibliographic record
Abstract
In recent years there has been an increased focus on gang desistence and exiting strategies, yet little is known at present regarding the experiences of women exiting the gang lifestyle. The current study, based on semi-structured interviews with twenty-four formerly gang-affiliated Chicana women involved with a prominent gang prevention/intervention organization, sought to understand how these women negotiated their disengagement from the gang. Consistent with previous literature, we found that disengagement from the gang lifestyle is neither linear nor immediate. Five primary themes that emerged from the interviews included: (1) the process of identity transition; (2) motherhood and its responsibilities; (3) generational shifts in gang culture; (4) burning bridges; (5) impacts of prison; and (6) support services. The women's narratives offer an alternative lens through which to understand women’s negotiation of their own identities through the process of disengagement from the gang.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.011 | 0.005 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| 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".