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Record W4361768921 · doi:10.1525/collabra.73649

The Hazards of Daily Stressors: Comparing the Experiences of Sexual and Gender Minority Young Adults to Cisgender Heterosexual Young Adults During the COVID-19 Pandemic

2023· article· en· W4361768921 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueCollabra Psychology · 2023
Typearticle
Languageen
FieldPsychology
TopicLGBTQ Health, Identity, and Policy
Canadian institutionsUniversity of VictoriaOkanagan University CollegeUniversity of British Columbia, Okanagan CampusUniversity of British Columbia
Fundersnot available
KeywordsStressorPsychologyMultilevel modelCoronavirus disease 2019 (COVID-19)PandemicClinical psychologyDemographyProportional hazards modelMoodDevelopmental psychologyMedicineDisease

Abstract

fetched live from OpenAlex

Some individuals may be at greater risk for encountering stressors in daily life than others, especially those with minority identities. Initial evidence shows that the disparities between cisgender heterosexual (CH) individuals and sexual and gender minority (SGM) individuals on stress-related experiences may be exacerbated by the COVID-19 pandemic. We examined the daily stressors experienced by undergraduate students during the COVID-19 pandemic (stressor exposure), the association between the experience of daily stress and same-day negative mood (stressor reactivity), and whether these varied between undergraduate students with SGM identities and their CH counterparts using a 14-day daily diary design. We did not find significant differences between SGM and CH groups on stressor exposure or stressor reactivity. One common feature of daily diary data is right censoring, which is when some individuals do not experience specific events during the study duration. We used multilevel survival analysis, which accounts for right censored data, to examine group differences in the risks of stressor exposure. We discuss the statistical issues involved when right-censored cases are not taken into consideration in studies of stressor exposure and propose multilevel survival analysis as one solution to move the field towards more accurately understanding whether, when, and why SGM individuals are at greater risk for stressors.

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.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.130
Threshold uncertainty score0.840

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.001
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 head0.099
GPT teacher head0.415
Teacher spread0.316 · 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