Cultivating the Next Generation of Giving: Concluding Report on the Impact of Honeycombs Foundation Board Incubator Initiative
Bibliographic record
Abstract
Honeycomb launched the Foundation Board Incubator to support community-based teen foundations that empower teens to serve as local philanthropic leaders. As part of the Incubator, host organizations of Jewish teen philanthropy programs engaged in a three- or five-year partnership with local funders and Honeycomb.Honeycomb's Foundation Board Incubator supported organizations to develop their own, local Jewish youth philanthropy programs between 2014 and 2022 in ten communities: San Diego, Detroit, Boston, Toronto, Philadelphia, Melbourne, Israel, Seattle, Indianapolis, and Houston. More than 3,500 participants granted out over $1 million in the programs. Customizable curriculum guided participants through the full grantmaking process, from identifying Jewish values to awarding grants. Honeycomb staff provided coaching and cohort-based learning for program leaders.The Incubator provided host organizations with seed funding to begin their program, a curriculum to guide the participants' experience, and coaching and access to the community of fellow Incubator site staff to support implementation along the way. The programs are now independently operating Jewish Youth Philanthropy programs.
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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 | 0.009 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.005 | 0.002 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.011 | 0.001 |
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".