The Business Leaders Behind the Foundations: Understanding India’s Emerging Philanthropists
Bibliographic record
Abstract
Abstract This research builds our understanding of emerging corporate and private Indian foundations through the lens of their founders—India’s new generation of high-net-worth business leaders. Based on over 45 interviews and drawing on existing literature, it explores the background of these individuals, their unique position as “hyperagents,” and the Indian context that shapes their foundations. Findings suggest that these philanthropists prefer operational foundation models, politically and socially “safe” sectors, carry over business tendencies, pursue social change through a driver or catalyst role, and hold preference for control at the cost of coordination between actors. These approaches are logical given the context but are not the ideal end-goal, rather a step toward advancing HNWI philanthropy in the country. This work will be of interest to those looking to engage with Indian philanthropists and foundations, and given the limited existing scholarship on Indian philanthropy, it contributes to the development of India-specific theories.
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How this classification was reachedexpand
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".