Understanding the Influence of Cultural Norms and Beliefs on Black Canadian Women's Journey After Pregnancy Loss
Bibliographic record
Abstract
The experiences and meanings assigned to pregnancy loss are deeply influenced and shaped by the socio-cultural context of affected women. However, very limited studies have examined the influence of cultural norms and beliefs on how Black women make sense of pregnancy loss from a Canadian context. This study explored ways cultural norms and beliefs influenced Black Canadian women's journey after pregnancy loss. An exploratory qualitative design was used as part of a larger study exploring the experiences of Black Canadian women following a pregnancy loss. We used purposive and snowball sampling to recruit 32 Black Canadian women with lived experiences of pregnancy loss. Semi-structured interviews were conducted, and thematic analysis was used to organize the data into meaningful themes. Five themes shedding light on the experiences of Black Canadian women were identified: (i) living with the stigma, (ii) grappling with the silence, (iii) enduring the shame, (iv) dealing with the stereotype, and (v) calling for awareness. These experiences impeded emotional healing, access to community support, and reintegration into family and community. Participants also called for greater awareness to address the cultural myths and misconceptions surrounding pregnancy loss. The findings underscore the need to create a culturally sensitive awareness campaign to foster greater understanding about the causes of pregnancy loss, reduce the stigma associated with the experience, and facilitate open dialogue. Such actions will contribute to normalizing the experiences of pregnancy loss and increase access to community and social support.
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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 | 0.004 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.027 | 0.013 |
| Scholarly communication | 0.007 | 0.002 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.001 | 0.003 |
| 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".