A Comparison of Street Gangs and Fraternities in the United States of America: Demographics, Conduct, and Criminal Justice Perception and Responses
Bibliographic record
Abstract
Street gangs and university fraternities are both prevalent social institutions in the United States of America. Despite differences in classification and treatment, they share many of the same characteristics, particularly initiation rituals, the pervasiveness of drugs and alcohol, the emphasis placed on brotherhood and male bonding, and the ways in which misogynistic attitudes and violence are used to reinforce masculinity and dominance. Despite these similarities, offences ranging from misbehaviour to criminal activity by fraternity members are protected under the guise of “academic brotherhood”, and thus go largely unpunished. On the contrary, gang members, who often come from lower-class backgrounds and are over-represented in Black and Hispanic populations, are not afforded these same benefits. I will be further exploring these double standards by examining the experiences of Black Greek Letter Organizations (BGLOs) and how they are likened to ‘educated gangs’. In this paper, I will be exploring the similarities between street gangs and fraternities in the United States in terms of demographics, conduct, and the types and prevalence of criminal offending. I will also be discussing the differences in classification and response of these two institutions by both the general public and the criminal justice system. While I am not advocating for the expansion of federal gang definitions to include fraternities, there needs to be a serious conversation regarding the types of violence that we take seriously, and the ways in which race and class factor into these decisions. Keywords: gang, fraternity, sexual violence, alcohol, initiation, masculinity, Black Greek Letter Organizations
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| 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".