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Record W4412585499 · doi:10.1080/00918369.2025.2537842

Queering Shelter: Homelessness Service Provider Perspectives on Programming for 2SLGBTQ+ Adults in Montreal, Canada

2025· article· en· W4412585499 on OpenAlexaffabout
Hannah Brais, Jayne Malenfant

Bibliographic record

VenueJournal of Homosexuality · 2025
Typearticle
Languageen
FieldHealth Professions
TopicHomelessness and Social Issues
Canadian institutionsMcGill University
Fundersnot available
KeywordsSociologyGender studiesService providerQueerSocial workGerontologyPsychologyService (business)CriminologyMedia studiesPolitical scienceMedicineBusiness

Abstract

fetched live from OpenAlex

2SLGBTQ+ adults face unique experiences of homelessness often marked by heightened victimization. Notably, homelessness resources represent challenging environments where, in addition to risks of discrimination, 2SLGBTQ+ adults often do not have support that reflects their unique needs to exit homelessness. The case of Montreal, Canada, is particularly concerning as no resource specifically supports this group. This research set out with the following questions: 1. How are homelessness organizations in Montreal currently responding to the needs of 2SLGBTQ+ community members? 2. How do workers in housing and homelessness organizations imagine shifts to better support the 2SLGBTQ+ community? 3. What policies, practices, and training would support these shifts? Correspondingly, we facilitated three focus groups with a total of 15 individuals currently working in one Montreal homelessness resource. Findings revealed the following themes and recommendations: unique experiences and corresponding needs of 2SLGBTQ+ adults; homelessness resources and supports for 2SLGBTQ+ people in Montreal; staff hold competing views on the effectiveness of segregated or integrated supports for 2SLGBTQ+ people; and that information and training for staff requires greater attention. Overarchingly, findings suggest the need to develop stronger programming and more robust training supported by clear and actionable policies in homelessness services.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.363
Threshold uncertainty score0.688

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.029
GPT teacher head0.390
Teacher spread0.361 · 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 teacher head, not a consensus.

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

Citations1
Published2025
Admission routes2
Has abstractyes

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