Flag-bearers of a new era? The evolution of new regulatory institutions in India (1991–2016)
Bibliographic record
Abstract
This chapter provides a critical, descriptive account of the emergence of a select few regulatory state institutions in India since the early 1990s, when the national government initiated a series of new economic policies. The creation and evolution of these institutions has arguably altered the landscape of Indian administrative law in fundamental ways, the significance and impact of which has yet to be carefully studied and understood. In describing the factors that influenced the formation and evolution of these new regulatory institutions, I analyze their original design and critically assess their functioning across the quarter century of their existence. While focusing on new regulatory institutions in India as a whole (which currently constitute 25 in number), the focus will be on three sectors in particular: telecom, electricity and the securities sector. I argue that as these regulatory institutions mature and move into the next phase of their evolution, far greater attention needs to be paid to the appointments’ process and the persons who are selected as regulators. There is a dire need for specialized knowledge and skills. The current system where mostly retired bureaucrats are appointed to these positions needs to be reviewed and changed.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.002 | 0.005 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 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".