Unpacking the Discourse on Youth Pathways into and out of Homelessness: Implications for Research Scholarship and Policy Interventions
Bibliographic record
Abstract
Youth homelessness presents a complex and persistent challenge worldwide, particularly affecting young adults between 16 and 24 years of age in the US and Canada. This population faces elevated risks of exploitation, victimization, and various health issues upon detachment from familial support structures. Understanding the multi-faceted nature of youth homelessness requires the consideration of individual, structural, and systemic factors within the socio-ecological model. Historically, when examining youth homelessness, traditional methods have concentrated either on individual factors contributing to homelessness or on broader structural issues within society. The emergence of the new orthodoxy attempted to bridge the apparent gap between individual- and structural-level factors by considering both to be equally significant, but it faced skepticism for its theoretical framework. In response, the “pathways” approach gained traction, emphasizing the subjective experiences and agency of youth experiencing homelessness. Departing from conventional epidemiological models, the pathways approach views homelessness as a dynamic process intertwined with individual life contexts. This paper navigates the scholarly discourse on youth homelessness and examines the distinct characteristics of the pathways approach. By exploring its implications for research and policy, this study contributes to a nuanced understanding of youth homelessness and informs future prevention-focused interventions.
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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 | 0.042 | 0.038 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.015 | 0.041 |
| Scholarly communication | 0.020 | 0.025 |
| Open science | 0.003 | 0.013 |
| Research integrity | 0.005 | 0.009 |
| Insufficient payload (model declined to judge) | 0.005 | 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".