Motivations for food prohibitions during pregnancy and their enforcement mechanisms in a rural Ghanaian district
Bibliographic record
Abstract
BACKGROUND: Food taboos are known from virtually all human societies and pregnant women have often been targeted. We qualitatively assessed food taboos during pregnancy, its motivating factors, and enforcement mechanisms in the Upper Manya Krobo district of Ghana. METHODS: This was an exploratory cross sectional study using qualitative focus group discussions (FGDs). Sixteen FGDs were conducted. Participants were purposively selected using the maximum variation sampling technique. Tape recorded FGDs were transcribed verbatim and analyzed using Malterudian systematic text condensation technique. RESULTS: All the participants were aware of the existence of food prohibitions and beliefs targeting pregnant women in Upper Manya Krobo. The study identified snails, rats, hot foods, and animal lungs as tabooed during pregnancy. Adherence motivators included expectation of safe and timely delivery, avoidance of "monkey babies" (deformed babies); respect for ancestors, parents, and community elders. Enforcement mechanisms identified included constant reminders by parents, family members and significant others. Stigmatization and community sanctions are deployed sparingly. CONCLUSIONS: Food taboos and traditional beliefs targeting pregnant women exist in Upper Manya Krobo. Pregnant women are forbidden from eating snails, rats, snakes, hot foods and animal lungs. To a large extent, socio-cultural, and to a lesser, health concerns motivate the practice.
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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 | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".