"On our own, we can't manage": experiences with infant feeding recommendations among Malawian mothers living with HIV
Bibliographic record
Abstract
BACKGROUND: Infant feeding in communities with a high prevalence of HIV and AIDS is a potential challenge for mothers who must ultimately decide how to feed their infants within contexts that constrain their choices. METHODS: We investigated how infant feeding policy recommendations translate into maternal infant feeding decisions and practices using ethnographic research conducted between August 2004 and June 2005 among women participating in a prevention of mother-to-child transmission (PMTCT) program in Lilongwe, Malawi. RESULTS: Qualitative findings are that maternal ability to adhere to recommendations to breastfeed exclusively for the first six months of infant life was constrained by expectations and psycho-social support. The most salient were women's pre-existing views on breastfeeding, their understanding of the medico-scientific information, and the quality of counselling received. In contrast, maternal decisions to wean were largely influenced by household economic factors and food insecurity. CONCLUSIONS: We conclude that PMTCT programs delivered in ways which "download" the responsibility of adhering to recommendations to women in the absence of adequate psycho-social and livelihood supports contribute to substantial maternal psychosocial distress in this and, likely, similar settings.
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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 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.010 | 0.005 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.002 | 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".