Sociocultural Factors Affecting Breastfeeding Practices of Mothers During Natural Disasters: A Critical Ethnography in Rural Pakistan
Bibliographic record
Abstract
Natural disasters affect the health and well-being of mothers with young children. During natural disasters, this population is at risk of discontinuation of their breastfeeding practices. Pakistan is a middle-income country that is susceptible to natural disasters. This study intended to examine sociocultural factors that shape the breastfeeding experiences and practices of internally displaced mothers in Pakistan. This critical ethnographic study was undertaken in disaster-affected villages of Chitral, Pakistan. Data were collected utilizing multiple methods, including in-depth interviews with 18 internally displaced mothers and field observations. Multiple sociocultural factors were identified as either barriers or facilitators to these mothers' capacities to breastfeed their children. Informal support, formal support, breastfeeding culture, and spiritual practices facilitated displaced mothers to sustain their breastfeeding practices. On the other hand, lack of privacy, cultural beliefs, practices and expectations, covert oppression, and lack of healthcare support served as barriers to the breastfeeding practices of displaced mothers.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.005 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.002 |
| 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".