Bibliographic record
Abstract
Development aid work is dependent on funding, and the funding model is changing. Private philanthropic funding from the world's developed economies to countries of developing economies is USD $59 billion. This figure represents significant and rising investment by private citizens in development aid. The purpose of this dissertation is to provide contextual understanding of the perceived nature, reach, and influence of philanthropic private aid engagement as it is experienced by those who are most impacted - the recipients. Using the exploratory case study method this study examines the nature of privately funded aid and scrutinizes the role of private funding. Privately funded development aid players in Moshi and the Kilimanjaro Region of Tanzania are found to be characterized by a high concentration of diverse, mainly small to medium-sized organizations and projects. Tourism has an enormous impact on the presence and activities of privately funded aid projects. Findings suggest that a weakness of the privately funded sector is isolation of learning and a lack of mechanisms to transfer knowledge to others. The strengths of privately funded organizations and projects are close relationships with the target community, and flexibility and responsiveness to changes in the system. Drawing from on-site observation and interviews with donors, implementers and end-use recipients, these research findings provide insight into: how recipients are included in project decision-making; unintended consequences of private aid and notably the collective consequence of private actors adding to aid dependency; the use of standardized management tools such as logframes, theory of change, and guiding principles. Drawing from the experience and wisdom of the recipient these findings offer insight into the means by which initiatives meaningfully engage recipient communities and encourage critical reflection on the process of design and management of development projects in privately funded development aid. Keywords: global philanthropy, recipient voice, nonprofit management, grantmaking, development aid, unintended consequences, aid dependency, theory of change, guiding principles
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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 | 0.006 | 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 | 0.009 | 0.005 |
| Scholarly communication | 0.008 | 0.003 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.007 | 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".