Aging at the intersection of race and gender: Investigating the health and wellbeing of aging Black women in Canada
Bibliographic record
Abstract
Inequities in health systematically put groups of people who are socially disadvantaged due to being poor, female, a particular age and/or a member of a disenfranchised racial group at further disadvantage. Black people comprise 3% of Canada’s population and are more likely to be exposed to risk but less likely to seek preventative care. Older Black women face further disadvantages because of multiple intersecting factors related to their race, gender, and age. This dissertation presents findings from a sequential mixed methods study conducted to understand the health, wellbeing, and aging experiences of older Black women aged 55 and older in Canada. The study design and data analysis were informed by two theoretical frameworks: intersectionality and the life course perspective. First, using data from the Canadian Community Health Survey (CCHS), several multilevel logistic regression models were used to establish and compare association between racial identity and inequalities in hypertension, diabetes, cancer, chronic obstructive pulmonary disease (COPD), asthma, self-rated health, and self-rated mental health between Black and White men and women aged 55 and older. Second, qualitative phenomenological interviews were conducted simultaneously to gain a deeper understanding of the health and wellbeing of older Black women and factors that have influenced their health and wellbeing across their life course. These were factors that could not be deeply explored through the CCHS. Twenty-seven semi-structured interviews were conducted with Black women aged 55 and older living in the Greater Toronto Area. Following the conclusion of the first two phases, a thematic content analysis was completed for eight policy documents to determine whether and how the need for adequate housing among older Black women was addressed. These needs were identified in the semi-structured interviews conducted in the previous qualitative phase of the study. Overall, this study demonstrated that there are opportunities for additional research to understand the diverse aging experiences of women across their life course. It also demonstrated the opportunities for the use of intersectionality in mixed methods studies. Doing so will bridge an evidence gap as well as contribute to addressing health and social programming needs among understudied populations.
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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 | 0.000 | 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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 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".