Exploring Canadian perceptions and experiences of stigma during the COVID-19 pandemic
Bibliographic record
Abstract
Background: The COVID-19 pandemic has led to stigmatization of individuals based on race/ethnicity, age, gender, and occupation, among other factors. We canvassed Canadian residents to explore perceptions of and experiences with stigma during the COVID-19 pandemic. Methods: stigma. Residents of Ontario, Canada were eligible to participate and we aimed to recruit a sample that was diverse by race/ethnicity and age. Results: A total of 1,823 individuals participated in the survey (54% women, 39% men; 54% 18-40 years old, 28% 41-60 years old, 12% 61+ years old; 33% White, 26% East/SouthEast Asian, 14% Black, 12% South Asian). Fifty-one percent of participants agreed/strongly agreed that racist views had increased toward certain racial/ethnic groups in Canada during the pandemic. Participants perceived that people in Canada were stigmatized during the pandemic because of race/ethnicity (37%), political beliefs (26%), older age (24%), being a healthcare worker (23%), younger age (22%), being an essential worker (21%), and gender (11%). Thirty-nine percent of respondents feared experiencing and 37% experienced stigmatization during the pandemic. Men, individuals aged 18-40, and racialized participants were more likely to fear or experience stigma. With respect to health behaviors, 74, 68, and 59% of respondents were comfortable masking in public, seeking medical care if they became ill, and getting tested for COVID-19, respectively. Men were less likely to indicate comfort with mask wearing or seeking medical care. Participants aged 18-40 and Black participants were less likely to indicate comfort with all three behaviors compared to those over age 41 and White participants, respectively. South Asian participants were less likely to be comfortable seeking medical care compared to White Participants. Discussion: Participants feared or experienced stigmatization towards various demographic characteristics during the COVID-19 pandemic. It is critical that the factors driving stigma during health emergencies in Canada be better understood in order to develop effective public health messaging and interventions.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.021 | 0.005 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".