Descriptive Evidence of COVID-19’s Impact on Black LGBTQ Adults Amidst Ongoing Health Inequities
Bibliographic record
Abstract
Abstract Black LGBTQ people significant challenges and discrimination as they face the barriers of living at the intersection of multiply marginalized identities, which have worsened during the coronavirus pandemic. At a baseline, LGBTQ people exhibit elevated risk of being negatively impacted by the pandemic across health, economic and other social outcomes (Cahill et al., 2020; Heslin & Hall, 2021; Human Rights Campaign, 2020). Black LGBTQ people have also suffered significant economic losses (Human Rights Campaign Foundation, 2020) . Methods: The Human Rights Campaign Foundation and AARP supported and partnered with Community Marketing & Insights to conduct a survey of 1,815 Black LGBTQ adults in the United States. The online survey was fielded between September 21 and October 30, 2020. Many Black LGBTQ adult participants report healthcare discrimination in the last three years, with 19% reporting racial discrimination and 11% reporting sexual orientation-based discrimination. Furthermore, 31% of Black transgender adults report healthcare discrimination in the last three years. Preventing or treating COVID-19 is an important health concern to 67% of Black LGBTQ adults aged fifty-five and older, 63% of Black LGBTQ adults aged thirty-five to fifty-four and 53% aged eighteen to thirty-four. Overall, Black LGBTQ adults report being significantly impacted by the pandemic, including negative impacts on their social health (60%), mental health (44%), the physical health of their close friends and family (33%), their finances (30%), and their employment status (22%). Overall, one-quarter (25%) of Black LGBTQ adults had at least one close friend or family member die from coronavirus illness.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".