Thinking Big: Community Philanthropy and Management of Large-Scale Assets
Bibliographic record
Abstract
This article presents three case studies — from Ghana, the U.S., and Canada — to examine how community philanthropy might scale up to support community asset management and increase the power of communities to determine their own development with much greater and more complex financial investments. Community philanthropy institutions have become increasingly popular — especially in the Global South, where they serve to harness local assets, cultivate local capacities, and build trust among diverse stakeholders. Although bilateral donors and other international development funders are beginning to recognize the power of these local organizations, they are usually considered small-scale actors. As resource extraction continues to reach into remote areas and other large-scale industries (e.g. solar energy, agroforestry) grow, pressure on resources and the rights of communities will intensify. This article illustrates the agility, responsiveness, and effectiveness of the Newmont-Ahafo Development Foundation, the Cherokee Preservation Foundation, and the Clayoquot Biosphere Trust, and presents a case that, despite organizational challenges, community philanthropy has demonstrated the power to promote community self-determination, democratic decision-making, and more sustainable results from development projects.
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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 | 0.008 | 0.018 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.002 | 0.005 |
| Scholarly communication | 0.005 | 0.007 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.009 | 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".