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Record W3007279367

Better measurement, better outcomes: Housing first for youth in Canada

2018· article· en· W3007279367 on OpenAlexaboutno aff
Stephen Gaetz, Lauren Kimura, Ashley J. W. Ward

Bibliographic record

VenueParity · 2018
Typearticle
Languageen
FieldHealth Professions
TopicHomelessness and Social Issues
Canadian institutionsnot available
Fundersnot available
KeywordsPsychosocialWorkforceNormativeWorkforce developmentPsychologyPsychological resiliencePositive Youth DevelopmentGerontologyEconomic growthPolitical scienceMedicineDevelopmental psychologySocial psychologyPsychiatryEconomics
DOInot available

Abstract

fetched live from OpenAlex

In North America, youth homelessness has historically and predominantly been addressed through reliance on emergency services such as shelters and day programs. While these are essential services in a community's systemic response to homelessness, a crisis response alone does not adequately prevent homelessness, nor does it provide tools and resources needed to avoid future experiences of homelessness for young people. This can initiate a cycle of housing instability that negatively impacts young people's health and well‑being; cognitive and psychosocial development; personal safety; ability to have normative/age-appropriate experiences; and engagement with family, community, school, and the workforce. Importantly, for youth, prolonged or repetitive exposure to homelessness can interfere with their ability to transition to adulthood in a safe, healthy, and autonomous way.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.009
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.064
Threshold uncertainty score0.462

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.009
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.004
Science and technology studies0.0070.001
Scholarly communication0.0040.001
Open science0.0020.003
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0040.000

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 head0.156
GPT teacher head0.392
Teacher spread0.236 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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

Citations3
Published2018
Admission routes1
Has abstractyes

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