The Impact of Maternal Education on Children's Allocation Preferences across 13 Countries
Why this work is in the frame
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Bibliographic record
Abstract
The aim of this paper was to investigate if maternal education had a predictive effect for children's allocation preferences across a variety of collectivistic and individualistic countries. It was predicted that maternal education would serve as a significant predictor such that as maternal education increases so will sharing to reflect an endorsement of merit, equity, and empathy. It was also predicted that certain patterns would emerge across 13 countries as they related to the varying levels of individualistic and collectivistic values in those countries. Of the thirteen countries studied, only three yielded significant results. It was found that in China and the United States, as maternal education increased, so did children's preferences for giving more candies to an injured recipient based on empathetic concern. The opposite was observed in Canada. Limitations and implications are discussed.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it