Triggered: Qualitatively exploring structural and social drivers of firearm violence exposure among LGBTQ+ young adults of color in Detroit
Bibliographic record
Abstract
Firearm violence is a leading cause of injury and death among youth and young adults in the U.S. with notable inequities across race and ethnicity, geography, and gender. Lesbian, gay, bisexual, transgender, and queer (LGBTQ+) young adults are largely absent from firearms research. Guided by structural violence and Social Safety theory, we qualitatively explored structural and social influences on firearm violence exposure among LGBTQ+ young adults of color in Detroit, Michigan. Through analysis of in-depth interviews with 24 participants, we developed three themes aligned with this aim. First, participants' accounts reflected how contemporary and historical structural racism in Detroit is the root cause of the firearm violence. Second, participants characterized firearms as a source of protection in the absence of structural safety. Finally, participants described how firearm violence against LGBTQ+ people is often an attempt to regain social status lost to structural violence. These themes indicate that structural racism in Detroit has unique impacts on LGBTQ+ young adults of color's exposure to firearms and firearm violence. Future research with this community is needed to guide protective interventions and policy changes.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".