Identifying 2SLGBTQ+ individuals experiencing homelessness using Point-in-Time counts: Evidence from the 2021 Toronto Street Needs Assessment survey
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".