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Record W7042984106

Responding to Youth Homelessness during COVID-19 and Beyond: Perspectives from the Youth-Serving Sector in Canada

2020· report· en· W7042984106 on OpenAlexaboutno aff

Bibliographic record

VenueYork University Digital Library (York University) · 2020
Typereport
Languageen
Field
Topic
Canadian institutionsnot available
Fundersnot available
KeywordsService providerCoping (psychology)Survey data collectionPandemicSocial workAction (physics)Best practiceService (business)
DOInot available

Abstract

fetched live from OpenAlex

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.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.773
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0040.011
Science and technology studies0.0010.000
Scholarly communication0.0010.004
Open science0.0030.004
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.026
GPT teacher head0.188
Teacher spread0.163 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designQualitative
Domainnot available
GenreEmpirical

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".

Quick stats

Citations2
Published2020
Admission routes1
Has abstractyes

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