Are People Generous When the Financial Stakes Are High?
Bibliographic record
Abstract
How generous are people when making consequential financial decisions in the real world? We took advantage of a rare opportunity to examine generosity among a diverse sample of adults who received a gift of U.S. $10,000 from a pair of wealthy donors, with nearly no strings attached. Two-hundred participants were drawn from three low-income countries (Indonesia, Brazil, and Kenya) and four high-income countries (Australia, Canada, the United Kingdom, and the United States) as part of a preregistered study. On average, participants spent over $6,400 on purchases that benefited others, including nearly $1,700 on donations to charity, suggesting that humans exhibit remarkable generosity even when the stakes are high. To address whether generosity was driven by reputational concerns, we asked half the participants to share their spending decisions publicly on Twitter, whereas the other half were asked to keep their spending private. Generous spending was similar between the groups, in contrast to our preregistered hypothesis that enhancing reputational concerns would increase generosity.
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How this classification was reachedexpand
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.001 |
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 teacher head, 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".