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Record W7103894611 · doi:10.1921/swssr20252442

Aging, Sexual Orientation, and Neighbourhood Deprivation: CLSA and CANUE data

2025· article· W7103894611 on OpenAlexaffabout

Bibliographic record

VenueSocial Work and Social Sciences Review · 2025
Typearticle
Language
FieldPsychology
TopicLGBTQ Health, Identity, and Policy
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsNeighbourhood (mathematics)PopulationHuman sexualityPsychological interventionPublic healthReproductive healthLongitudinal studyHealth equity

Abstract

fetched live from OpenAlex

Although there are increasing discussions regarding the sexual minority population’s aging through social work and public health perspectives, the information about this vulnerable population beyond the interpersonal level analysis still needs more growth. Hence, the current study utilized the Canadian Longitudinal Study on Aging and Canadian Urban Environmental Health Research Consortium data to explore a neighbourhood deprivation levels of aging sexual minority people’s living environments. Neighbourhood social and material deprivation levels were observed to determine whether there is a difference when compared to their heterosexual counterparts. Analysis of covariance was used and each analysis included age as a covariate. Gender stratification was considered in this study. The study’s results found that aging homosexual and bisexual men resided in more socially deprived neighbourhoods compared to their heterosexual peers. Similarly, aging homosexual and bisexual women reported that they reside in more socially deprived neighbourhood compared to their heterosexual counterparts. The study provides a critical information regarding the aging sexual minority population in Canada. Such knowledge can help design and disseminate behavioural and policy interventions in deprived neighbourhoods.

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)0.003
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.482
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.002
Science and technology studies0.0070.002
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0000.000
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 head0.101
GPT teacher head0.463
Teacher spread0.362 · 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.

Study designObservational
Domainnot available
GenreReview

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
Published2025
Admission routes2
Has abstractyes

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