The Work of Youth Homelessness Prevention in Ontario: Points of Frustration, Points of Potential
Bibliographic record
Abstract
Despite a rhetorical turn towards prevention in homelessness policy and research, the work of youth homelessness prevention continues to be frustrated by persistent structural barriers. In this article, we examine how youth homelessness prevention is being implemented in the province of Ontario, with a focus on targeted provincial support programs and local shelter diversion practices. Drawing on interviews with workers in the homeless-serving sector, we describe the implementation of these initiatives and identify points of frustration and potential that workers encounter as they try to prevent experiences of homelessness for youth. We contend that these points of frustration illuminate persistent structural barriers that continue to forestall the work of youth homelessness prevention. Meanwhile, points of potential demonstrate the importance of empowering workers to creatively adapt and offer responsive services. Taken together, these signal the critical importance of two aspects of contemporary homelessness prevention typologies—primordial prevention and empowerment. We end by offering aspirations for action, a political reframing of the policy recommendations sections more typical of social science research articles. We do so to affirm our commitment to advancing the work of structural transformation that is required to achieve the right to housing for all, including youth.
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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 | 0.007 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.034 | 0.025 |
| Scholarly communication | 0.006 | 0.002 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.002 | 0.003 |
| 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".