Federalism In India and the Challenges of Cooperative Federalism: Constitutional Vision, Contemporary Practices, and Emerging Trends
Bibliographic record
Abstract
Federalism in India represents a distinctive constitutional arrangement, often described as "quasifederal," where a strong Centre coexists with constitutionally guaranteed powers of the States.Rooted in the vision of the Constituent Assembly, Indian federalism balances unity with diversity through an elaborate distribution of legislative, administrative, and fiscal powers.Over the decades, this balance has evolved into the principle of cooperative federalism, emphasizing collaboration between the Union and the States in policy formulation, fiscal management, and governance.Institutional mechanisms such as the Inter-State Council, Finance Commissions, Zonal Councils, and more recently, NITI Aayog and the GST Council, exemplify this cooperative framework.However, the practice of cooperative federalism faces significant challenges.Political friction between ruling parties at the Centre and in the States, fiscal imbalances aggravated by GST compensation disputes, and the limited role of institutional forums often hinder effective cooperation.Judicial interventions, while upholding federal principles, have not eliminated ambiguities in Centre-State relations.Comparative insights from other federations such as the United States, Canada, and Germany highlight potential reforms for strengthening India's cooperative model.The present research argues that revitalizing cooperative federalism is indispensable for sustaining India's democratic pluralism, ensuring inclusive development, and addressing emerging governance challenges.
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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 | 0.004 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.006 |
| Science and technology studies | 0.004 | 0.016 |
| Scholarly communication | 0.007 | 0.004 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.001 | 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".