Beyond Mortality: The Social and Health Impacts of COVID-19 among Older (55+) BIPOC and LGBT Respondents in a Canada-Wide Survey
Bibliographic record
Abstract
This study focused on the effects of the COVID-19 pandemic on the marginalized populations—specifically Black and Indigenous people as well as People of Color (BIPOC) compared to White older adults and LGBT individuals compared to heterosexual older adults. Data were derived from our national online survey of Canadians aged 55+, conducted from 10 August to 10 October 2020. The survey explored the influence of COVID-19 on lifestyle changes, well-being, and planning for the future. Our sample comprised 4292 respondents. We compared sets of dichotomous variables with White vs. BIPOC, LGBT vs. heterosexual, and LGBT White vs. LGBT BIPOC respondents. Significantly more BIPOC than White individuals reported changes in accessing food (44.3% vs. 33.2%) and in family income (53.9% vs. 38.9%) and fewer reported feeling accepted and happy, and more felt isolated and judged. Significantly more LGBT than heterosexual respondents reported changes in routines and in accessing social support, medical and mental health care and more feeling depressed, lonely, anxious, and sad. More LGBT–BIPOC than LGBT–White respondents reported changes in access to food (66.7 vs. 30.6, p < 0.001); in family income (66.7 vs. 41.5, p < 0.005); and in access to mental health care (38.5 vs. 24.0, p < 0.05). The only difference in emotional response to COVID-19 was that more BIPOC–LGBT than White–LGBT respondents reported feeling judged (25.9 vs. 14.5, p < 0.05). These findings reflect a complex mix of the effects of marginalization upon BIPOC and LGBT older adults, revealing both hardship and hardiness and warranting further research.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| 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) | 0.002 | 0.000 |
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.
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".