Social Determinants of Breastfeeding Preferences among Black Mothers Living with HIV in Two North American Cities
Bibliographic record
Abstract
The study is motivated by the need to understand the social determinants of breastfeeding attitudes among HIV-positive African, Caribbean, and Black (ACB) mothers. To address the central issue identified in this study, analysis was conducted with datasets from two North American cities, where unique country-specific guidelines complicate infant feeding discourse, decisions, and practices for HIV-positive mothers. These national infant feeding guidelines in Canada and the US present a source of conflict and tension for ACB mothers as they try to navigate the spaces between contradictory cultural expectations and national guidelines. Analyses in this paper were drawn from a broader mixed methods study guided by a community-based participatory research (CBPR) approach to examine infant feeding practices among HIV-positive Black mothers in three countries. The survey were distributed through Qualtrics and SPSS was used for data cleaning and analysis. Results revealed a direct correlation between social determinants and breastfeeding attitude. Country of residence, relatives' opinion, healthcare providers' advice and HIV-related stigma had statistically significant association with breastfeeding attitude. While the two countries' guidelines, which recommend exclusive formula feeding, are cardinal in preventing vertical transmission, they can also be a source of stress. We recommend due consideration of the cultural contexts of women's lives in infant feeding guidelines, to ensure inclusion of diverse women.
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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 | 0.004 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".