Effects of Fundraising Alliances on Charitable Donations
Bibliographic record
Abstract
Fundraising Alliances (FAs) are independent organizations that fundraise for two or more charities under a separate brand. High-profile examples of FAs include the Disasters Emergency Committee (DEC) in the United Kingdom and the Humanitarian Coalition (HCC) in Canada. FAs are designed to reduce promotional costs and increase the effectiveness of fundraising efforts. FAs are thought to be differentially effective for smaller charities that are less familiar and that do not have the managerial and financial resources to fundraise independently. However, are FAs actually effective? The present research examines the conditions under which individual charities are better off joining an FA rather than fundraising independently. We find evidence that FAs do not help (and may harm) charity fundraising, particularly for smaller charities that are perceived to be low on familiarity, trustworthiness, and effectiveness. The research has important implications for nonprofit marketing and contributes to the literature on branding and charity fundraising.
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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 | 0.005 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".