Exploring the complex context of Canadian Indigenous maternal child-health through maternity experiences: the role of social determinants of health.
Bibliographic record
Abstract
BACKGROUND: The marginalization of Indigenous women in Canada has resulted in adverse pregnancy and infant health outcomes. While the epidemiological research focuses on statistical evidence, it fails to address the context and underlying causes, including social determinants of health. Despite clear evidence on how social determinants influence health, there is limited research on Indigenous women’s perspectives and experiences. Indigenous women’s narratives during pregnancy, birth and the early months of parenthood are critical to understand the underlying causes and proposed solutions. This research demonstrates how Indigenous women’s maternity experiences are embedded within their historical, social and cultural experiences, thus explaining the importance of addressing contexts related to social determinants of health. METHODS: Through an Indigenous and decolonized lens, maternity narratives from ten in-depth interviews were conducted with Indigenous birth mothers in British Columbia, Canada. Thematic content analysis findings contextualize Indigenous maternity experiences within proximal, intermediate and distal determinants of health. RESULTS: The proximal determinates include barriers to education, employment, income, food (in)security and a lack of safe and affordable housing and homelessness due to urban migration and violent relationships. Intermediate experiences included barriers to accessing maternity healthcare, including geographic barriers and experiences of racism. Distal determinants including traumatic narratives related to immediate and intergenerational impacts of colonialism, including the Indian residential school system and foster care, which has impacted mental health and addictions. CONCLUSION: This research contributes to expanding research on culturally safe and improved maternal-child health, healthcare and maternity research, as well as highlighting the need to address and alleviate adverse social determinants.
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.020 | 0.009 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.008 |
| Research integrity | 0.001 | 0.002 |
| 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".