Making water policy and water laws democratic: lessons from South Indian states

The present attempt is to propose local people’s involvement in Water Policy and Water Law formulation in Indian sub continent on the growing realization that policies and laws the state governments have so far either visualized or implemented seems remain paper tigers. It examines the existing water laws and its implementation from 3 south Indian states viz., Kerala, Karnataka and Tamil Nadu for this purpose. Analysis shows that water laws mainly are centered on participatory irrigation management and water user associations. Groundwater laws are given lowest emphasis by the state governments where as majority of the Indian population depends upon it especially for domestic use. Indiscriminate sand mining is seen an emerging threat for river hydrological system that has accentuated by income tax rebates and gaps of housing policies. It indicates that the entire process of evolving water policy and laws is devoid of its stakeholders’ participation particularly from the grassroots level. Institutional framework to facilitate local people’s participation like Gram Sabha and Panchayati Raj Institutions are grossly underutilised for this purpose. On this background it examines the recent attempt of Kerala government in facilitating stakeholders’ participation in law formulation in water related Bill, called The Kerala Conservation of Paddy Fields and Wetlands Bill 2007.Length: pp.708-719Water policyWater lawLegislationStakeholders

Random Walks on Hypergraphs with Edge-Dependent Vertex Weights

Hypergraphs are used in machine learning to model higher-order relationships in data. While spectral methods for graphs are well-established, spectral theory for hypergraphs remains an active area of research. In this paper, we use random walks to develop a spectral theory for hypergraphs with edge-dependent vertex weights: hypergraphs where every vertex $v$ has a weight $\gamma_e(v)$ for each incident hyperedge $e$ that describes the contribution of $v$ to the hyperedge $e$. We derive a random walk-based hypergraph Laplacian, and bound the mixing time of random walks on such hypergraphs. Moreover, we give conditions under which random walks on such hypergraphs are equivalent to random walks on graphs. As a corollary, we show that current machine learning methods that rely on Laplacians derived from random walks on hypergraphs with edge-independent vertex weights do not utilize higher-order relationships in the data. Finally, we demonstrate the advantages of hypergraphs with edge-dependent vertex weights on ranking applications using real-world datasets.Comment: Accepted to ICML 201

Trade Theory and Trade Facts

This paper quantitatively tests the "new trade theory" based on product di.erentiation, increasing returns, and imperfect competition. We employ a standard model, which allows both changes in the distribution of income among industrialized countries, emphasized by Helpman and Krugman (1985), and nonhomothetic preferences, emphasized by Markusen (1986), to e.ect trade directions and volumes. In addition, we generalize the model to allow changes in relative prices to have large e.ects. We test the model by calibrating it to 1990 data and then "backcasting" to 1961 to see what changes in crucial variables between 1961 and 1990 are predicted by the theory. The results show that, although the model is capable of explaining much of the increased concentration of trade among industrialized countries, it is not capable of explaining the enormous increase in the ratio of trade to income. Our analysis suggests that it is policy changes, rather than the elements emphasized in the new trade theory, that have been the most significant determinants of the increase in trade volume.

Trade theory and trade facts

This paper quantitatively tests the “new trade theory” based on product differentiation, increasing returns, and imperfect competition. We employ a standard model, which allows both changes in the distribution of income among industrialized countries, emphasized by Helpman and Krugman (1985), and nonhomothetic preferences, emphasized by Markusen (1986), to effect trade directions and volumes. In addition, we generalize the model to allow changes in relative prices to have large effects. We test the model by calibrating it to 1990 data and then “backcasting” to 1961 to see what changes in crucial variables between 1961 and 1990 are predicted by the theory. The results show that, although the model is capable of explaining much of the increased concentration of trade among industrialized countries, it is not capable of explaining the enormous increase in the ratio of trade to income. Our analysis suggests that it is policy changes, rather than the elements emphasized in the new trade theory, that have been the most significant determinants of the increase in trade volume.Trade ; Product differentiation

NIPS - Not Even Wrong? A Systematic Review of Empirically Complete Demonstrations of Algorithmic Effectiveness in the Machine Learning and Artificial Intelligence Literature

Objective: To determine the completeness of argumentative steps necessary to conclude effectiveness of an algorithm in a sample of current ML/AI supervised learning literature. Data Sources: Papers published in the Neural Information Processing Systems (NeurIPS, n\'ee NIPS) journal where the official record showed a 2017 year of publication. Eligibility Criteria: Studies reporting a (semi-)supervised model, or pre-processing fused with (semi-)supervised models for tabular data. Study Appraisal: Three reviewers applied the assessment criteria to determine argumentative completeness. The criteria were split into three groups, including: experiments (e.g real and/or synthetic data), baselines (e.g uninformed and/or state-of-art) and quantitative comparison (e.g. performance quantifiers with confidence intervals and formal comparison of the algorithm against baselines). Results: Of the 121 eligible manuscripts (from the sample of 679 abstracts), 99\% used real-world data and 29\% used synthetic data. 91\% of manuscripts did not report an uninformed baseline and 55\% reported a state-of-art baseline. 32\% reported confidence intervals for performance but none provided references or exposition for how these were calculated. 3\% reported formal comparisons. Limitations: The use of one journal as the primary information source may not be representative of all ML/AI literature. However, the NeurIPS conference is recognised to be amongst the top tier concerning ML/AI studies, so it is reasonable to consider its corpus to be representative of high-quality research. Conclusion: Using the 2017 sample of the NeurIPS supervised learning corpus as an indicator for the quality and trustworthiness of current ML/AI research, it appears that complete argumentative chains in demonstrations of algorithmic effectiveness are rare

The global nuclear liability regime post Fukushima Daiichi

Nuclear liability regimes are important as they ensure that potential victims will be compensated promptly and efficiently after a nuclear accident. The accident at Fukushima Daiichi in Japan in 2011 prompted a review of the global nuclear liability regime that remains on-going. Progress has been slow, but over the next few years the European Union is set to announce its new proposals. Meanwhile, in 2015, another global nuclear liability regime, the Convention on Supplementary Compensation for Nuclear Damage, has entered into force. This paper aims to move the debate in the literature on nuclear liability and focuses on the four following major issues: (1) reviews third-party nuclear liability regimes currently in operation around the world; (2) analyses the international nuclear liability regime following the accident at Fukushima Daiichi; (3) comparatively assesses the liability regimes for nuclear energy and the non-nuclear energy sector; and (4) presents the future outlook for possible developments in the global nuclear liability regime