Health System Access for Precariously Housed Youth: A Participatory Youth Research Project
Bibliographic record
Abstract
This article builds from young people’s experiences navigating health system organizations to identify concrete institutional and policy processes that pose problems for youth experiencing or at risk of homelessness, as well as those that show promise in terms of health promotion. Our participatory youth research team explored homeless youth’s health-seeking practices, the specific barriers they face, and relations between their health-seeking efforts and their homelessness. Youth and adult co-researchers interviewed 38 individual youth (aged 16–29) who completed 64 qualitative institutional history interviews. Their accounts illuminate a systemic lack of capacity to address the mental health needs of homeless youth. Unable to secure access to timely, sufficient, and suitable programs and services, youth navigate patchwork of crisis and emergency supports that undermine their autonomy, their health, and their housing stability. Finally, youth without stable housing—particularly those who are Trans* and non-binary youth and/or who use drugs—report discrimination in health care settings. Our results suggest that access to timely, appropriate, de-stigmatizing, and consistent (mental) health services is one way to prevent youth homelessness.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.026 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.011 | 0.004 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.001 | 0.002 |
| 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".