Covid-19 in st. James town: The social determinants of health inequities reflected in canada’s most diverse neighbourhood
Bibliographic record
Abstract
It has been well documented that COVID-19 does not affect all populations equally;the pandemic disproportionately impacts racialized, ethnic minority, low-income, and underserved communities. To further this conversation, this paper examines three adjacent, yet very distinct, neighbourhoods in the downtown core of Toronto, Ontario: St. James Town, Cabbagetown, and Rosedale. The socioeconomic positions of each neighborhood vary from low to high, and their respective COVID-19 positive case counts are inversed. After laying out the COVID-19 case data for each region, we examine the stark demographic and socioeconomic inequalities of these neighborhoods. Finally, we frame this information through the lens of the social determinants of health to identify gaps as well as steps toward meaningful solutions. © 2021, University of Toronto. All rights reserved.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.010 | 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".