Donor Advised Fund Policies and Intergenerational Justice
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
Abstract Questions about donor advised funds (DAFs) abound in the nonprofit sector. Every year more money is contributed, with donations to DAFs doubling in the past five years. A key set of questions about DAFs relates to how long that money stays in DAFs before being redistributed. Writing previously in Nonprofit Policy Forum, Murray (Murray, I. 2020. “Donor Advised Funds: What Can North America Learn from the Australian Approach?” Canadian Journal of Comparative and Contemporary Law 6: 260–304) proposed the use of normative theories of intergenerational justice to address such questions and discussed how the duties that apply to directors/trustees of the public charities that sponsor DAFs might be one mechanism for incorporating intergenerational justice principles. DAF sponsor policies are a key tool for directors/trustees to meet their duties and to set the scope for delegations of authority and to review and monitor those delegations. Heist and Stone (Heist, D., and K. Stone. 2023. Self-Regulating Donor Advised Funds: An Analysis of Inactive Account Policies and Endowed DAFs. DAF Research Collaborative Working Paper) published a white-paper reviewing timing-relevant policies from the largest 150 DAF sponsors in the US. The empirical findings in that paper and the organizational policies assembled by Heist and Stone provide an opportunity to explore whether Murray’s suggested approach is reflected in DAF sponsor policies on inactive accounts, endowed DAF accounts, and succession. In this article, we therefore seek to answer the question: to what extent do current DAF sponsor policies reflect principles of intergenerational justice? We provide evidence that current DAF policies do, to some extent, reflect norms of intergenerational justice, but that there is room for improvement.
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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 | 0.000 | 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 | 0.000 | 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