Giving against the Odds: When Tempting Alternatives Increase Willingness to Donate
Bibliographic record
Abstract
The authors examine how a reference to an unrelated product in the choice context affects consumers’ likelihood of donating to charity. Building on research on self-signaling, the authors predict that consumers are more likely to give when the donation appeal references a hedonic product than when a utilitarian product is referenced or when no comparison is provided. They posit that this phenomenon occurs because referencing a hedonic product during a charitable appeal changes the self-attributions, or self-signaling utility, associated with the choice to donate. A series of hypothetical and actual choice experiments demonstrate the predicted effect and show that the increase in donation rates occurs because the self-attributions signaled by a choice not to donate are more negative in the context of a hedonic reference product. Finally, consistent with these experimental findings, a field experiment shows that referencing a hedonic product during a charitable appeal increases real donation rates in a nonlaboratory setting. The authors discuss the theoretical implications for both consumer decision making and the self-signaling motives behind prosocial choice.
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 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 | 0.096 | 0.040 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; both teacher heads agree on what is shown here.
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".