Responding to Youth Homelessness during COVID-19 and Beyond: Perspectives from the Youth-Serving Sector in Canada
Bibliographic record
Abstract
The gaps and weaknesses in our social safety net have been laid bare when we see the impacts of the pandemic on young people at-risk of or experiencing homelessness and the youth-serving sector itself. Understanding the youth-serving sector’s need for early-stage, applied research and evidence on the impacts of COVID-19, A Way Home Canada and the Canadian Observatory on Homelessness conducted an initial survey in March, 2020 to identify the emergent trends, opportunities and challenges across Canada, as well as the ways we could support the sector throughout the pandemic. The resulting report, Summary Report: Youth Homelessness & COVID-19 - How the Youth-Serving Sector is Coping with the Crisis, was published in April, 2020. Respondents to this survey indicated a desire to stay connected to the broader network of service providers across Canada in order to share and receive information and discuss emerging challenges. As a result, A Way Home Canada has hosted weekly national COVID-19 Community of Practice calls for youth-serving agencies, which are still ongoing. The second survey was launched, seeking to dig deeper into the questions and insights from the first survey and the COVID-19 Community of Practice calls. The first of three sections of this report explores what service providers in organizations across Canada had to say about some of the impacts COVID-19 has had on the young people they serve. The second section highlights ways that the youth-serving sector has been impacted by and coped with the crisis. In the final section, we identify essential action areas for better responding to crises like COVID-19 and chart a way forward into recovery and rebuilding.
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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 | 0.006 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.055 | 0.013 |
| Scholarly communication | 0.014 | 0.004 |
| Open science | 0.004 | 0.011 |
| Research integrity | 0.003 | 0.011 |
| Insufficient payload (model declined to judge) | 0.004 | 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".