Leveraging Creativity in Charity Marketing: The Impact of Engaging in Creative Activities on Subsequent Donation Behavior
Bibliographic record
Abstract
Charities are constantly looking for new and more effective ways to engage potential donors in order to secure the resources needed to deliver services. The current work demonstrates that creative activities are one way for marketers to meet this challenge. Field and lab studies find that engaging potential donors in creative activities positively influences their donation behaviors (i.e., the likelihood of donation and the monetary amount donated). Importantly, the observed effects are shown to be context independent: they hold even when potential donors engage in creative activities unrelated to the focal cause of the charity (or the charitable organization itself). The findings suggest that engaging in a creative activity enhances the felt autonomy of the participant, thus inducing a positive affective state, which in turn leads to higher donation behaviors. Positive affect is demonstrated to enhance donation behaviors due to perceptions of donation impact and a desire for mood maintenance. However, the identified effects emerge only when one engages in a creative activity—not when the activity is noncreative, or when only the concept of creativity itself is made salient.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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; a candidate call from one source (direct Gemma or distilled Codex), 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".