Under What Conditions Does Prosocial Spending Promote Happiness?
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Under what conditions does prosocial spending promote happiness? In a series of appropriately powered and pre-registered experiments, the present research revisited the role of impact, social connection, and perceived choice in maximizing the emotional benefits of spending money on others. In two exploratory studies, we found that happy (vs. less happy) prosocial spending experiences were marked by higher levels of impact, social connection and perceived choice (Study 1a and 1b). Consistent with these initial findings, three pre-registered studies confirmed that spending money on others was particularly rewarding when people were able to see the difference their generosity made (Study 2); when they felt a sense of social connection to the person or cause they were helping (Study 3); and when they felt that the decision to help was freely chosen (Study 4). Together, our findings corroborate previous research on impact, social connection and perceived choice, and highlight the importance of considering these key variables when evaluating old and new evidence on the emotional benefits of prosocial spending. In addition, our findings suggest that charitable organizations and policymakers should review their current solicitation strategies and pay more attention to people’s sense of impact, connection and choice when seeking charitable donations.
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.
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 | 0.001 |
| 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) | 0.008 | 0.003 |
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