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Record W4402520314 · doi:10.7870/cjcmh-2024-011

Surviving the Added Pressures of the Pandemic: Sexual and Gender Diverse Communities Prioritize Social Connection to Decrease Mental Health Burden During the Covid-19 Pandemic

2024· article· en· W4402520314 on OpenAlexaffvenueabout
Nicole E. Pal, Kayla Huggard, Kiffer G. Card, Carolien Aantjes, Ben Klassen, Nathan J. Lachowsky

Bibliographic record

VenueCanadian Journal of Community Mental Health · 2024
Typearticle
Languageen
FieldHealth Professions
TopicHomelessness and Social Issues
Canadian institutionsCommunity Based Research CentreSimon Fraser UniversityUniversity of Victoria
Fundersnot available
KeywordsMental healthSocioeconomic statusPandemicContext (archaeology)Focus groupSocial supportPsychologyCoronavirus disease 2019 (COVID-19)SociologyPolitical scienceMedicineSocial psychologyPsychiatryGeographyDemography

Abstract

fetched live from OpenAlex

This study explored the mental health experiences of sexual and gender diverse (SGD) communities in Canada within the context of the Covid-19 pandemic. Three online focus groups with 14 SGD community members were conducted to discuss experiences with social determinants of mental health. Themes included social connection and support, healthcare access and utilization, discrimination and socioeconomic status (employment, income, housing, education). Social connection and support were prominent themes throughout all groups. Policy and practice should focus primarily on scaling community-led services and programs that build social connection and support informed by local context and perspectives.

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)0.002
metaresearch head score (Gemma)0.003
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.261
Threshold uncertainty score0.524

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0180.007
Scholarly communication0.0040.002
Open science0.0010.008
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0040.000

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 head0.195
GPT teacher head0.448
Teacher spread0.252 · 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

Citations0
Published2024
Admission routes3
Has abstractyes

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