COVID-19 and the Disproportionate Impact Seen on the BIPOC Community A literature Review
Bibliographic record
Abstract
Objectives: To highlight the ongoing health inequities experienced by the BIPOC community in Canada through the data collected from the COVID-19 pandemic. To demonstrate the disproportionate effect of COVID-19 on the BIPOC community, through the negative outcomes such as infection rates, hospitalization, ICU admission, and death. To correlate which non-medical factors contributed to the outcomes seen and what needs to be accomplished to mitigate future health crises. Methods: Literature review using the platform PubMed. Key terms used included “COVID-19 pandemic outcomes, COVID-19 and the BIPOC community, disproportionate outcomes of BIPOC community COVID-19, social determinants of health and COVID-19, healthy inequity and COVID-19.” Subsequently, 11 articles were deemed suitable for use in this review. Studies were focused on North American studies, particularly in Canada, but were not restricted to such. Results: The literature review identified that BIPOC individuals experienced disproportionate outcomes during the COVID-19 pandemic. They held greater infection rates, hospitalizations, and death compared to the white population of Canada. The non-medical factors which contributed to the poor outcomes seen during the pandemic included employment, neighbourhood, SES, and systemic racism in health care practices. Conclusions: The social determinants of health associated with the negative outcomes seen during the COVID-19 pandemic highlight changes that need to be taken to protect vulnerable communities. Negative outcomes can be prevented through collaborative measures to create safer employment strategies, safer neighbourhoods, and safer health care practices with the goal of eliminating systemic racism and creating health equity.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 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 teacher head, 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".