Finding the door: Critical incidents facilitating gang exit among indigenous men.
Bibliographic record
Abstract
OBJECTIVE: Our aim was to generate a categorical scheme to describe how participants exited from gang life. METHOD: We utilized the CIT (Butterfield, Borgen, Amundson, & Maglio, 2005; Flanagan, 1954; Woolsey, 1986) and explored gang exit processes among 10 Indigenous men living in Manitoba and Saskatchewan, Canada. Participants responded to the question: What facilitated gang exit for you? RESULTS: They provided 136 critical incidents that were organized into 13 categories of behaviors and experiences that facilitated their exit from gang life: (a) working in the legal workforce, (b) accepting support from family or girlfriend, (c) helping others stay out of gang life, (d) not wanting to go back to jail, (e) accepting responsibility for family, (f) accepting guidance and protection, (g) participating in ceremony, (h) avoiding alcohol, (i) publically expressing that you were out of the gang, (j) wanting legit relationships outside gangs, (k) experiencing a native brotherhood, (l) stopping self from reacting like a gangster, and (m) acknowledging the drawbacks of gang violence. CONCLUSION: The categorical scheme is presented, described with use of extensive quotes from this research, theoretical and clinical implications are discussed, and suggestions for future research are offered. (PsycINFO Database Record
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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 | 0.003 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.009 | 0.005 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.005 |
| 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".