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Record W4394693901 · doi:10.1371/journal.pone.0298252

Identifying 2SLGBTQ+ individuals experiencing homelessness using Point-in-Time counts: Evidence from the 2021 Toronto Street Needs Assessment survey

2024· article· en· W4394693901 on OpenAlexaffabout
Alex Abramovich, Max Marshall, Christopher M. Webb, Nicole Elkington, Rowen K. Stark, Nelson Pang, Linda A. Wood

Bibliographic record

VenuePLoS ONE · 2024
Typearticle
Languageen
FieldHealth Professions
TopicHomelessness and Social Issues
Canadian institutionsPublic Health OntarioUniversity of TorontoCentre for Addiction and Mental Health
Fundersnot available
KeywordsOutreachTransgenderLesbianNeeds assessmentSexual orientationMedicinePsychologyGerontologySociologySocial psychologyGender studiesPolitical science

Abstract

fetched live from OpenAlex

INTRODUCTION: The objective of this study was to utilize the data generated by the City of Toronto, Street Needs Assessment conducted in 2021 to explore the prevalence, causes, experiences, and characteristics of 2-spirit, lesbian, gay, bisexual, transgender, queer, and questioning (2SLGBTQ+) individuals experiencing homelessness in Toronto, Ontario, Canada. METHODS: Data was collected by the City of Toronto during its Street Needs Assessment in April 2021. The Street Needs Assessment is a needs assessment survey and Point-in-Time count of people experiencing homelessness across the city of Toronto. Homelessness included any individual who was sleeping outdoors or staying in City-administered emergency/transitional shelters and shelter motels/hotels on the night of data collection. The Street Needs Assessment survey was administered to clients by trained shelter and outreach staff using a computer or mobile device. To ensure that survey questions were 2SLGBTQ+ inclusive, questions on sexual orientation, gender identity, and 2SLGBTQ+ identity were included in the survey. RESULTS: Two hundred and eighty-eight 2SLGBTQ+ individuals completed the survey. Compared to non-2SLGBTQ+ individuals experiencing homelessness, 2SLGBTQ+ respondents were younger at the time of survey completion and when they first experienced homelessness, were more likely to have been in foster care or a group home, reported higher rates of conflict with and/or abuse by a parent/guardian as their main pathway into homelessness, and were more likely to experience chronic homelessness. CONCLUSION: Our study results demonstrate that Street Needs Assessments and Point-in-Time counts can be used to examine homelessness in marginalized populations, including 2SLGBTQ+ individuals and that sexual orientation and gender identity questions need to be included on future government surveys. The consistency of findings from this study and previous research suggests that 2SLGBTQ+ individuals experience a significant need for population-based housing and social support services aimed at meeting the needs of 2SLGBTQ+ populations.

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)0.013
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 score0.183
Threshold uncertainty score0.368

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.013
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.003
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.002
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.197
GPT teacher head0.433
Teacher spread0.235 · 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

Citations7
Published2024
Admission routes2
Has abstractyes

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