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Record W1973728471 · doi:10.1177/0044118x10365354

Resilient Educational Outcomes: Participation in School by Youth With Histories of Homelessness

2010· article· en· W1973728471 on OpenAlexaff
Sophie Isabelle Hyman, Tim Aubry, Fran Klodawsky

Bibliographic record

VenueYouth & Society · 2010
Typearticle
Languageen
FieldHealth Professions
TopicHomelessness and Social Issues
Canadian institutionsCarleton UniversityUniversity of Ottawa
Fundersnot available
KeywordsPsychological resilienceSchool dropoutPsychologyPositive Youth DevelopmentDevelopmental psychologyLongitudinal studySociologySocial psychologySocioeconomicsMedicine

Abstract

fetched live from OpenAlex

Disrupted high school experiences, including dropout, are educational consequences for many youth with histories of homelessness. Using an ecological resilience prediction model (ERPM) based on the literature on resilience in at-risk youth, the study followed 82 youth who were initially homeless for a 2-year period, to identify predictors of participating in school. Female sex and increased duration of rehousing at Time 2 significantly predicted being in school at follow-up. Youth who were not in school reported a greater increase in satisfaction with social support compared to youth who were participating in school at follow-up. The study adds to what is understood regarding the longitudinal consequences of housing instability and discontinuity in school participation in youth by examining ecological predictors of resilience. Implications of findings for policy and program development targeting education and housing for youth are discussed.

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)0.001
metaresearch head score (Gemma)0.003
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 score0.013
Threshold uncertainty score0.026

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.034
GPT teacher head0.383
Teacher spread0.349 · 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

Citations35
Published2010
Admission routes1
Has abstractyes

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