Bibliographic record
Abstract
PART ONE: POLITICAL ECONOMY OF REFORM India Fiscal Federalism - Kenneth Kletzer and Nirvikar Singh Political Economy and Issues for Reform Fragmented Legislatures and Electoral Systems - Bhaskar Dutta The Indian Experience The Political Economy of Privatisation in India - Anand Gupta Centre-state Relations in India and Brazil - Leslie Elliot Armijo Privatisation of Electricity and Banking PART TWO: FISCAL REFORM Reforming Indian Income Tax Enforcement - Arindam Das-Gupta and Dilip Mookherjee Fiscal Adjustment and the Role of State Governments in India - M. Govinda Rao Tax Amnesties in India - Arindam Das-Gupta and Dilip Mookherjee An Empirical Evaluation PART THREE: REFORMING PUBLIC GOODS DELIVERY The Health and Medical Sector in India - Anil Deolalikar and Prem Vashishtha Potential Reforms and Problems Fertility, Literacy, and the Institution of Child Labour - Mukesh Eswaran PART FOUR: AGRICULTURAL PARASTATALS AND RURAL GOVERNANCE The Food Corporation in India - Ashok Gulati, Pradeep Sharma and Satu Kahkonen Successes and Failures in Indian Foodgrain Marketing Economic Reforms and Agricultural Parastatals - Ashok Gulati and Sangeeta Shroff The Case of the Cotton Corporation in India and Maharashtra Federation Panchayati Raj in India - Chandrika Gulati Problems and Prospects PART FIVE: REFORMING THE INDUSTRIAL AND FINANCIAL STRUCTURE Regulation and Reform of the Financial Sector in India - Pradeep Agrawal An Analysis of the Underlying Incentives Labour Markets as Social Institutions in India - Mrinal Datta-Chaudhuri Labour Policies, Employment and Worker Earnings - Pradeep Agrawal Indian and International Experiences
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.004 |
| Science and technology studies | 0.002 | 0.006 |
| Scholarly communication | 0.007 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.008 | 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".