Governing a new generation of philanthropy: key leadership tools for success.
Bibliographic record
Abstract
Philanthropy has taken center stage again after the rapid growth of hospitals in the 1990s. It is an essential resource, not only because today's hospitals need the money more than ever, but also because great philanthropy helps forge rewarding relationships with the community. In meetings with more than 1,000 hospital board members and leaders at The Governance Institute's 2007 conferences, it became clear that maximizing philanthropy in the future will require boards to enhance three initiatives: a bolder service mission, more effective stakeholder engagement tools and enhanced planned giving programs. Health care philanthropy boards and the boards of their related organizations would be wise to devote time for robust conversations about their strategies for feeding the voracious capital appetites of contemporary health care systems and for examining their ability to govern a new generation of philanthropy.
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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 | 0.033 | 0.052 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.010 | 0.018 |
| Scholarly communication | 0.013 | 0.017 |
| Open science | 0.001 | 0.015 |
| Research integrity | 0.004 | 0.010 |
| Insufficient payload (model declined to judge) | 0.018 | 0.004 |
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".