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Record W2068388059 · doi:10.1080/01488376.2011.633814

An Ecological Systems Comparison Between Homeless Sexual Minority Youths and Homeless Heterosexual Youths

2011· article· en· W2068388059 on OpenAlexaboutno aff
Maurice N. Gattis

Bibliographic record

VenueJournal of Social Service Research · 2011
Typearticle
Languageen
FieldHealth Professions
TopicHomelessness and Social Issues
Canadian institutionsnot available
FundersNational Center for Advancing Translational SciencesNational Center for Research ResourcesCenters for Disease Control and Prevention
KeywordsSexual minorityPsychologyMental healthClinical psychologyStigma (botany)Context (archaeology)Substance useIntervention (counseling)LesbianPsychiatrySexual orientationSocial psychology

Abstract

fetched live from OpenAlex

This study examined risk and protective outcomes by comparing homeless sexual minority youths to heterosexual homeless youths regarding family, peer behaviors, school, mental health (suicide risk and depression), stigma, discrimination, substance use, and sexual risk behaviors. Structured interviews (N = 147) were conducted with individuals ages 16-24 at three drop-in programs serving homeless youths in Toronto. Bivariate analyses indicated statistically significant differences between homeless sexual minorities (n=66) and their heterosexual counterparts (n=81) regarding all variables: family, peer behaviors, stigma, discrimination, mental health, substance use and sexual risk behaviors with the exception of school belonging. Specifically, homeless sexual minority youths fared more poorly (e.g. lower satisfaction with family communication, experienced more stigma, used more drugs and alcohol) than their heterosexual counterparts. Improving family communication may be a worthwhile intervention if the youths are still in contact with their families. Future research should focus on victimization in the context of multiple systems.

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)0.002
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 score0.068
Threshold uncertainty score0.136

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.000
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 head0.390
GPT teacher head0.528
Teacher spread0.138 · 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

Citations93
Published2011
Admission routes1
Has abstractyes

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