In poor families, mothers' milk is richer for daughters than sons: A test of Trivers–Willard hypothesis in agropastoral settlements in Northern Kenya
Bibliographic record
Abstract
The Trivers-Willard hypothesis predicts the unequal parental investment between daughters and sons, depending on maternal condition and offspring reproductive potential. Specifically, in polygynous populations where males have higher reproductive variance than females, it predicts that mothers in good condition will invest more in sons, whereas mothers in poor condition will invest more in daughters. Previous studies testing this hypothesis focused on behavioral investment, whereas few examined biological investment. This study investigates the Trivers-Willard hypothesis on both behavioral and biological parental investment by examining breastfeeding frequencies and breast milk fat concentrations. Data from exclusively breastfeeding mothers in Northern Kenya were used to test hypotheses: Economically sufficient mothers will breastfeed sons more frequently than daughters, whereas poor mothers will breastfeed daughters more frequently than sons, and economically sufficient mothers will produce breast milk with higher fat concentration for sons than daughters, whereas poor mothers will produce breast milk with higher fat concentration for daughters than sons. Linear regression models were applied, using breastfeeding frequency or log-transformed milk fat as the dependent variable, and offspring's sex (son = 1/daughter = 0), socioeconomic status (higher = 1/lower = 0), and the sex-wealth interaction as the predictors, controlling for covariates. Our results only supported the milk fat hypothesis: infant's sex and socioeconomic status interacted (P = 0.014, n = 72) in their relation with milk fat concentration. The model estimated that economically sufficient mothers produced richer milk for sons than daughters (2.8 vs. 1.74 gm/dl) [corrected] while poor mothers produced richer milk for daughters than sons (2.6 vs. 2.3 gm/dl). Further research on milk constituents in relation to offspring's sex is warranted.
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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 | 0.003 |
| 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 | 0.001 |
| 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".