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Record W4392911017 · doi:10.1080/19361653.2024.2329879

COVID-19 pandemic experiences of LGBTQIA + Asian youth in Canada

2024· article· en· W4392911017 on OpenAlexaffabout
Kenny Chee, Todd Coleman

Bibliographic record

VenueInternational journal of LGBTQ+ youth studies. · 2024
Typearticle
Languageen
FieldPsychology
TopicLGBTQ Health, Identity, and Policy
Canadian institutionsWilfrid Laurier University
Fundersnot available
KeywordsCoronavirus disease 2019 (COVID-19)Pandemic2019-20 coronavirus outbreakSevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2)VirologyPolitical scienceMedicineOutbreakInfectious disease (medical specialty)

Abstract

fetched live from OpenAlex

LGBTQIA + Asian youth face unique challenges due to their intersecting identities (i.e. racial discrimination from LGBTQIA + communities, and LGBTQIA+ -related stigmatization from their Asian culture). The COVID-19 pandemic exacerbated existing intersectional challenges due to the closure of community spaces for LGBTQIA + Asian youth, spaces which served as a safe haven from home and anti-Asians sentiments. Thus far, there have been no studies examining how the COVID-19 pandemic was experienced by LGBTQIA + Asian Canadian youth. To address this, we completed eight online focus group discussions with 30 LGBTQIA + Asian youth from across Canada, alongside a brief quantitative questionnaire to explore specific components of participants’ mental health and well-being. Quantitative findings suggested many participants were experiencing negative mental health outcomes (i.e. stress, anxiety, and depression). Thematic qualitative analysis showed that, despite various negative impacts of COVID-19 restrictions and increased anti-Asian sentiments, restrictions allowed youth to further explore their own sexual orientations and gender identities. Participants also shared that the #stopAsianhate movement was empowering, however it largely excluded LGBTQIA+ Asian voices. With the unique intersectional challenges experienced during the COVID-19 pandemic, this study highlights the importance of maintaining inclusive supports that consider the unique intracategorical complexities experienced by LGBTQIA +Asian youth.

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)0.001
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 score0.360
Threshold uncertainty score0.661

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.139
GPT teacher head0.453
Teacher spread0.314 · 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
Published2024
Admission routes2
Has abstractyes

Explore more

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