Proxy Power Play: Comparing the rise of Proxy Advisory Firms in India and the United States
Bibliographic record
Abstract
This paper aims to analyze and compare the strengths of Indian and US proxy advisory firms, focusing on their role in corporate governance and influence on institutional investor proxy voting. India has emerged as the fastest-growing large economy and a preferred choice for foreign direct investment, making its existing regulatory regime on proxy advisory firms crucial. The study examines the evolution of the proxy advisory industry, its growth, and the role of the market regulator, the Securities and Exchange Board of India (SEBI). It evaluates the working experience of proxy advisory firms in India and the US, identifying areas where they have made an impact. The article discusses factors that limit the role of proxy advisory firms in corporate governance in India compared to the US which include concentrated shareholding structures, lack of accountability, resistance to best practices, limited awareness about proxy advisory firms, limited resources, and absence of effective stewardship duties exercised by investment advisors. It is argued that the need for a stronger corporate governance regime in India requires legislative action and stricter regulation by SEBI. To enhance the influence of proxy advisory firms in India, the paper outlines three ways: strengthening the legal infrastructure to ensure stricter internal control tests and disclosures; introducing a mandatory public shareholding regime of 35% to improve price discovery of traded shares and deter highhandedness; and creating greater awareness of the important role played by proxy firms in securing high standards of corporate governance through education campaigns aimed at retail and institutional investors.
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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 | 0.001 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".