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Record W4213086005 · doi:10.33596/coll.84

Aging in the Community: Utilizing Community Based Participatory Research to Identify and Address the Housing Needs of LGBTQ2S+ Seniors

2022· article· en· W4213086005 on OpenAlexaffabout
Brent Oliver, Floyd Visser, Natasha Hoehn, Rocky Wallbaum, Donna Thorsten, Kate Berezowski

Bibliographic record

VenueCollaborations A Journal of Community-Based Research and Practice · 2022
Typearticle
Languageen
FieldPsychology
TopicLGBTQ Health, Identity, and Policy
Canadian institutionsThe Sharp FoundationMount Royal University
Fundersnot available
KeywordsTransgenderParticipatory action researchCommunity-based participatory researchQueerCitizen journalismLesbianSociologyPublic relationsQualitative researchPsychologyGerontologyGender studiesPolitical scienceMedicineSocial science

Abstract

fetched live from OpenAlex

This paper reports on the findings from a participatory research project exploring the housing needs and experiences of Lesbian, Gay, Bisexual, Transgender, Queer, Two-Spirit, and Non-Binary (LGBTQ2S+) individuals. The aim of this project was to better understand the perspectives of LGBTQ2S+ Seniors in Calgary and to present recommendations for housing and service providers. This community based participatory research project engaged peer researchers to conduct a community survey with LGBTQ2S+ seniors and interview various stakeholders working in or representing the intersection of housing, seniors, and LGBTQ2S+ people. Study findings from both the qualitative and quantitative phases of the research have been organized conceptually around three main themes identified by survey respondents and key stakeholders: 1). housing experiences of LGBTQ2S+ seniors; 2). experiences of discrimination and marginalization; and 3). inclusive housing for LGBTQ2S+ seniors. Housing policy and strategies for LGBTQ2S+ populations are identified and 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 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)0.141
metaresearch head score (Gemma)0.011
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Science and technology studies, Research integrity
Consensus categoriesMetaresearch
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.130
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.1410.011
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.007
Science and technology studies0.0160.001
Scholarly communication0.0010.001
Open science0.0020.001
Research integrity0.0000.015
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 head0.615
GPT teacher head0.588
Teacher spread0.027 · 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; both teacher heads agree on what is shown here.

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

Citations0
Published2022
Admission routes2
Has abstractyes

Explore more

Same venueCollaborations A Journal of Community-Based Research and PracticeSame topicLGBTQ Health, Identity, and PolicyFrench-language works237,207