‘I didn’t want to be noticed’: discrimination and violence among LGBTQ + youth experiencing homelessness
Bibliographic record
Abstract
This qualitative study documents incidents of discrimination and violence among LGBTQ + youth experiencing homelessness along with their adaptation strategies. Using intersectionality theory, this analysis is based on individual interviews conducted with 17 LGBTQ + youth experiencing homelessness aged 17 to 25. According to their stories, LGBTQ + youth experienced various types of discrimination and violence in the context of homelessness. Youth report anticipating and experiencing physical and psychological violence from passersby in public spaces, causing them to hide from the gaze of others. They also report that police profiling of racialized youth and young women sex workers leads these youth to avoid confrontational interactions with the police. Some youth mention that landlords and employers discriminate against them based on their ethnicity and gender expression, requiring them to have contingency plans for housing and employment. Lastly, many LGBTQ + youths report hiding information about being bisexual, being trans or doing sex work to avoid prejudice and rejection from their intimate partners. The results show that heterosexist, cisgenderism, sexist and racist discrimination and violence amplify the social exclusion of LGBTQ + youth who are already marginalized due to their homelessness.
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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 | 0.004 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.008 | 0.007 |
| 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".