Gender differences in Coronavirus Disease 2019 (COVID-19) related beliefs and practices of Orthodox Jews in Montreal: An exploratory study
Bibliographic record
Abstract
Background: The COVID-19 pandemic highlighted the disproportionate impact of communicable diseases on minority groups, including the Orthodox Jewish community.Men and women experienced the pandemic differently as evidenced by the ratio of male to female cases and deaths being 0.88 and 1.30 respectively, based on data collected from the World Health Organization from 186 countries as of August 21, 2023 [1].Gender consists of socially constructed norms that determine roles, relationships, and positional power in society [2].In cultures where women take on the role of primary caregivers, men may be less aware of health information and less motivated to locate such information.No studies have been conducted thus far on the role of gender in understanding the differential experiences of COVID-19 within Orthodox Jewish communities.Gender roles are strictly defined in this community and align with biological sex.With its breadth of sub-groups and specific gender roles based on Jewish Law, the Orthodox Jewish community of Montreal presented an ideal opportunity to investigate the relationship between gender and communicable disease impact on minority groups.Objective: To investigate the role of gender in the differential reporting of COVID-19 experiences, including levels of trust, public and healthcare satisfaction, and compliance with public health measures within Orthodox Jewish communities in Montreal.Methods: This cross-sectional study is embedded within an interdisciplinary mixed methods project conducted in partnership with the Orthodox Jewish community of Montreal.Data were obtained from a modified version of the COVID-19 Immunity Taskforce Core Data Elements Survey.Our convenience sample includes adults who intended to receive the COVID-19 vaccine; data were collected at baseline between June 23, 2021 and May 25, 2022.The main
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.002 |
| Scholarly communication | 0.002 | 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".