Indonesia Infant and Young Child Feeding Practice: The Role of Women’s Empowerment in Household Domain
Bibliographic record
Abstract
Previous studies showed the significant association between women’s empowerment and infant and young child feeding (IYCF) practice. Only around 40% of Indonesian children met adequate IYCF practice. Hence, each dimension of women’s empowerment in the household domain must be explored. We carried out a dataset of the 2017 Indonesia Demographic and Health Survey, with samples of 4,880 mothers of reproductive age in a marriage relationship with their last-born child aged 6-23 months. Logistic regression was applied. Mother with legal asset ownerships had lower odds of her child meeting (aOR: 0.83; 95% CI: 0.72, 0.95) minimum dietary diversity (MDD), (aOR: 0.75; 95% CI: 0.65, 0.87) minimum meal frequency (MMF) and (aOR: 0.74; 95% CI: 0.61, 0.90) minimum acceptable diet (MAD). Mother who could control her own earnings had higher odds of her child meeting MDD (aOR: 1.52; 95% CI: 1.32, 1.74) and MAD (aOR: 1.62; 95% CI: 1.34, 1.94). Employed mother had higher odds of meeting MMF (aOR: 1.58; 95% CI: 1.38, 1.82). Mother who did not approve of intimate partner violence was more likely to feed her child with MDD (1.39 times), MMF (1.41 times) and MAD (2.04 times). Mother with three or more parity had lower odds of her child meeting MDD (aOR: 0.81; 95% CI: 0.79, 0.93), MMF (aOR: 0.84; 95% CI: 0.72, 0.99) and MDD (aOR: 0.80; 95% CI: 0.65, 1.00). Mother who did not approve towards domestic violence, was working, controlled her assets and had a maximum of two parity was associated with official IYCF recommendation.
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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".