How Do Hunter-Gatherer Children Learn Social and Gender Norms? A Meta-Ethnographic Review
Bibliographic record
Abstract
Forager societies tend to value egalitarianism, cooperative autonomy, and sharing. Furthermore, foragers exhibit a strong gendered division of labor. However, few studies have employed a cross-cultural approach to understand how forager children learn social and gender norms. To address this gap, we perform a meta-ethnography, which allows for the systematic extraction, synthesis, and comparison of quantitative and qualitative publications. In all, 77 publications met our inclusion criteria. These suggest that sharing is actively taught in infancy. In early childhood, children transition to the playgroup, signifying their increased autonomy. Cooperative behaviors are learned through play. At the end of middle childhood, children self-segregate into same-sex groups and begin to perform gender-specific tasks. We find evidence that foragers actively teach children social norms, and that, with sedentarization, teaching, through direct instruction and task assignment, replaces imitation in learning gendered behaviors. We also find evidence that child-to-child transmission is an important way children learn cultural norms, and that noninterference might be a way autonomy is taught. These findings can add to the debate on teaching and learning within forager populations.
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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 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.008 | 0.006 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".