Gangster Girlfriends in British Columbia: The Allure of Louboutin, Chanel, and Tiffany
Bibliographic record
Abstract
According to Peterson (2014) female members may account for as much as 40% of the gang membership in the United States, and yet we still know so little about the female role, membership, association to, and relationships with known gang members. Indeed, Decker (2017: xvii) has noted that “In too many studies of organized crime groups, women are either not dealt with or are treated as appendages.” Our research goes some way to correcting this, adding to the body of evidence by understanding the decision for involvement with gangs, as non-gang members. The main objective was to explore the romantic relationships between females and gang members. The research examines why young females, who do not identify as gang members, enter relationships with gang members and what the nature of these relationships are. In doing so, the research is able to offer a number of recommendations for intervention, which may be effective at deterring gang involvement, and supporting ‘exit strategies’ of young women involved with gang members. The data used to recommend intervention and prevention strategies was produced from qualitative interviews with three women from British Columbia who have previously been in a relationship with a gang member. The results contribute to the ongoing debate about whether females become involved with gangs because they are victims or through conscious decision. A rational choice. The present study argues that women need to be viewed as active decision makers in their own lives, while still acknowledging that dating a gang member is a dangerous and abusive experience. The research also finds support for the glamorization of gangs and suggests that this is an integral factor in entering a relationship with a gang member. This study argues that prevention and intervention methods that aim to de-glamourize gangs are needed to deter young women from entering these relationships.
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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 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.030 | 0.004 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.002 | 0.005 |
| Insufficient payload (model declined to judge) | 0.010 | 0.001 |
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".