Engaging Youth Experiencing Homelessness in Research: A Framework Derived from Three Programs of Work in North America
Bibliographic record
Abstract
The need for representative samples in research is well-accepted and widely acknowledged. However, marginalized populations experiencing poverty, including unstably housed youth and youth experiencing homelessness, are consistently underrepresented. This underrepresentation has implications for fully understanding and addressing the needs of youth lacking adequate shelter and reduces the quality of the information available to inform intervention design and systems change. In particular, rigorous and representative youth engagement in research is essential in the design of robust prevention strategies at intervention and policy levels. The current paper summarizes lessons learned from three leading research teams in the field of youth homelessness, located in Canada and the United States, in the form of a framework for successful research engagement of youth with experiences of homelessness. Collaborative discussion with researchers and youth with lived experience generated an expert consensus of strategies crucial for successful research engagement. This consensus was summarized with five pillars of successful engagement that were relevant across settings: attunement, accessibility, communication, collaboration, and flexibility. The authors also highlight notable challenges and future directions. The objective of this paper is to introduce guiding principles that will both motivate and inform researchers undertaking research efforts with unstably housed youth, and to initiate further discussions on adapting engagement methods to meet the needs of marginalized youth populations.
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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 | 0.084 | 0.031 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.006 | 0.005 |
| Science and technology studies | 0.036 | 0.037 |
| Scholarly communication | 0.019 | 0.008 |
| Open science | 0.007 | 0.028 |
| Research integrity | 0.006 | 0.009 |
| Insufficient payload (model declined to judge) | 0.001 | 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".