Costly Helping Across Three Societies
Bibliographic record
Abstract
Over the second and third years of life, toddlers begin to engage in helping even when it comes at a personal cost. During this same period, toddlers gain experience of ownership, which may influ- ence their tendency to help at a cost. Whereas costly helping has been studied in Western children, who have ample access to resources, the emergence of costly helping has not been examined in societies where children’s experience with ownership is varied and access to resources is scarce. The current study compared the development of toddlers’ costly and non-costly helping in three societies within Canada, India, and Peru that differ in these aspects of children’s early social experience. In two conditions, 16- to 36- month-olds (N = 100) helped an experimenter by giving either their own items (Costly condition) or the experimenter’s items (Non-costly condition). Children’s tendency to help increased with age in the Non-costly condition across all three societies. In the Costly condition, in Canada children’s tendency to help increased with age, in Peru children’s helping remained stable across age, and in India children’s level of helping decreased with age. Thus, whereas we replicate the findings that non-costly helping appears to develop synchronously across diverse societies, costly helping may depend on children’s early society-specific experiences. We discuss these findings in relation to children’s early ownership experience and access to resources, factors that may account for the divergent patterns in the development of costly helping across these societies.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.004 |
| 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".