Bibliographic record
Abstract
Prosocial behavior research has historically considered altruistic or self-interested motives as the primary drivers for charitable giving. Recently, however, there have been many high-profile cases wherein consumers use their donations to harm others. The authors define this behavior, characterized by a desire for retribution resulting from witnessing or experiencing volitional wrongdoing, as "retributive philanthropy" and examine this phenomenon using a multimethod approach. Qualitative interviews with perpetrators and targets of retributive philanthropy reveal key themes of blameworthiness judgments, strong negative affect, and a desire to harm as a terminal goal of donation-none which are typically associated with prosocial behaviors. Analysis of real-world antivaccine protestor donation data finds similar themes of perceived wrongdoing and outrage related to retributive donations in a large-scale context. Five lab studies and five supplementary studies then demonstrate the effects of perceived volitional wrongdoing, harm, efficacy, and authoritarianism on willingness to make retributive donations. Together, these findings offer critical insight into an emerging mode of donation that is emotionally, motivationally, and behaviorally distinct from traditional prosocial behavior and has important implications for consumers and charitable marketers.
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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 | 0.048 | 0.022 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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".