The development of children's preferences for equality and equity across 13 individualistic and collectivist cultures
Bibliographic record
Abstract
A concern for fairness is a fundamental and universal element of morality. To examine the extent to which cultural norms are integrated into fairness cognitions and influence social preferences regarding equality and equity, a large sample of children (N 2,163) aged 4-11 were tested in 13 diverse countries. Children participated in three versions of a third-party, contextualized distributive justice game between two hypothetical recipients differing in terms of wealth, merit, and empathy. Social decision-making in these games revealed universal age-related shifts from equality-based to equity-based distribution motivations across cultures. However, differences in levels of individualism and collectivism between the 13 countries predicted the age and extent to which children favor equity in each condition. Children from the most individualistic cultures endorsed equitable distributions to a greater degree than children from more collectivist cultures when recipients differed in regards to wealth and merit. However, in an empathy context where recipients differed in injury, children from the most collectivist cultures exhibited greater preferences to distribute resource equitably compared to children from more individualistic cultures. Children from the more individualistic cultures also favored equitable distributions at an earlier age than children from more collectivist cultures overall. These results demonstrate aspects of both cross-cultural similarity and divergence in the development of fairness preferences.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".