Experiencing a Natural Disaster Alters Children’s Altruistic Giving
Bibliographic record
Abstract
Altruism is thought to be a major contributor to the development of large-scale human societies. However, much of the evidence supporting this belief comes from individuals living in pacific and often affluent environments. It is entirely unknown whether humans act altruistically when facing adversity. Adversity is arguably a common human experience (as manifested in, e.g., personal tragedies, political upheavals, and natural disasters). In the research reported here, we found that experiencing a natural disaster affected children's altruistic giving. Immediately after witnessing devastations caused by a major earthquake, 9-year-olds became more altruistic. In addition, the more empathic they were, the more they gave. In contrast, experiencing a major earthquake caused 6-year-olds to be more selfish. Three years after the earthquake, children's altruistic tendencies returned to pre-earthquake levels, which suggests that changes in children's altruistic giving are an acute response to the immediate aftermath of a major natural disaster. These findings suggest that environmental insults and empathy play crucial roles in human altruism.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".