Too far to help: The effect of perceived distance on the expected impact and likelihood of charitable action.
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
Fact: Holding force constant, a snowball thrown from 10 feet away will hurt more than one thrown from 50 feet away; it will have more impact. We show that people expect charitable donations-much like snowballs-to have more impact on nearby (vs. faraway) targets. Therefore, because making an impact is a powerful motivator of prosocial behavior, people are more willing to take action to help nearby (vs. faraway) causes-independent of social distance. Six studies, including lab and field experiments, and secondary data from fundraising campaigns support this prediction. Specifically, Study 1 shows that people expect charitable donations to have a greater impact on nearby (vs. faraway) recipients, and that these judgments stem from metaphorical thinking. In the context of alumni giving to their alma mater, the next two studies show that donations increase as real (Study 2) or perceived (Study 3) distances decrease. Study 4 extends these findings using a more conservative manipulation of distance perception (Study 4). Finally, Study 5 demonstrates the mediating role of expected impact on the effect of perceived distance on charitable action, whereas Study 6 shows that a motivational focus on making an impact moderates this effect. (PsycINFO Database Record
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 | 0.001 | 0.000 |
| 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 | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 it