Hypertension Experiences of Black Men: A Critical Narrative Study
Bibliographic record
Abstract
Abstract Although Black individuals are disproportionately affected by hypertension as evidenced by higher prevalence and lower control rates, few studies have investigated this disparity from the lens of those most affected by this condition. This chapter explores how Black men make sense of their hypertension and how they negotiate this condition within their everyday lives, illuminating how racism and power dynamics embedded within their environments affect their experiences living with hypertension. Critical Race Theory tenets were utilized alongside a narrative design to elicit stories of hypertension experiences of four Black men living in Ontario, Canada. Eight semistructured in-depth interviews were conducted, transcribed, and thematically analyzed to illuminate how participants create meaning in regard to their hypertension. Participants’ experiences with discrimination, isolation, and migration raise awareness of how power relations embedded within social, political, and historical contexts can affect hypertension experiences. The findings of this study are bounded by its narrative context, and the characteristics of the individuals who shared their experiences. This study highlights the importance of how discussions concerning hypertensive minority men should be broadened to include the voices of such men, as well as the structures that discriminate against and oppress minority individuals.
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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 | 0.006 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.023 | 0.011 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.002 | 0.005 |
| 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".