The New Interdisciplinary Fields of Public Policy Engineering and Computational Public Policy

2014 ◽  
pp. 233-238 ◽  
Author(s):  
Ashu M. G. Solo
Keyword(s):  
Public Policy ◽  
Decision Making ◽  
Research And Development ◽  
Computer Science ◽  
Natural Science ◽  
Policy Formulation ◽  
Definition Of

This chapter describes two new interdisciplinary fields defined by Ashu M. G. Solo called “public policy engineering” and “computational public policy.” Public policy engineering is the application of engineering, computer science, mathematics, or natural science to solving problems in public policy. Computational public policy is the application of computer science or mathematics to solving problems in public policy. Public policy engineering and computational public policy include, but are not limited to, principles and methods for public policy formulation, decision making, analysis, modeling, optimization, forecasting, and simulation. The definition of these two new fields will greatly increase the pace of research and development in these important fields.

The New Interdisciplinary Fields of Public Policy Engineering and Computational Public Policy

2015 ◽  
pp. 2243-2249
Author(s):  
Ashu M. G. Solo
Keyword(s):  
Public Policy ◽  
Decision Making ◽  
Research And Development ◽  
Computer Science ◽  
Natural Science ◽  
Policy Formulation ◽  
Definition Of

This chapter describes two new interdisciplinary fields defined by Ashu M. G. Solo called “public policy engineering” and “computational public policy.” Public policy engineering is the application of engineering, computer science, mathematics, or natural science to solving problems in public policy. Computational public policy is the application of computer science or mathematics to solving problems in public policy. Public policy engineering and computational public policy include, but are not limited to, principles and methods for public policy formulation, decision making, analysis, modeling, optimization, forecasting, and simulation. The definition of these two new fields will greatly increase the pace of research and development in these important fields.

The Interdisciplinary Fields of Political Engineering, Public Policy Engineering, Computational Politics, and Computational Public Policy

2020 ◽  
pp. 1-16
Author(s):  
Ashu M. G. Solo
Keyword(s):  
Public Policy ◽  
Decision Making ◽  
Research And Development ◽  
Computer Science ◽  
Natural Science ◽  
Policy Formulation ◽  
Academic Programs ◽  
Political Decision ◽  
University Curricula ◽  
Political Decision Making

This chapter describes four interdisciplinary fields originated and defined by Ashu M. G. Solo in 2011 called political engineering, public policy engineering, computational politics, and computational public policy. Political engineering is the application of engineering, computer science, mathematics, or natural science to solving problems in politics. Computational politics is the application of computer science or mathematics to solving problems in politics. Political engineering and computational politics include, but are not limited to, principles and methods for political decision-making, analysis, modeling, optimization, forecasting, simulation, and expression. Public policy engineering is the application of engineering, computer science, mathematics, or natural science to solving problems in public policy. Computational public policy is the application of computer science or mathematics to solving problems in public policy. Public policy engineering and computational public policy include, but are not limited to, principles and methods for public policy formulation, decision-making, analysis, modeling, optimization, forecasting, and simulation. The chapter describes the scope of research and development in these fields, provides examples of research and development in these fields, and provides possible university curricula for academic programs in these fields.

The New Interdisciplinary Fields of Political Engineering and Computational Politics

2014 ◽  
pp. 226-232 ◽  
Author(s):  
Ashu M. G. Solo
Keyword(s):  
Decision Making ◽  
Research And Development ◽  
Computer Science ◽  
Natural Science ◽  
Political Decision ◽  
Definition Of ◽  
Political Decision Making

This chapter describes two new interdisciplinary fields defined by Ashu M. G. Solo called “political engineering” and “computational politics.” Political engineering is the application of engineering, computer science, mathematics, or natural science to solving problems in politics. Computational politics is the application of computer science or mathematics to solving problems in politics. Political engineering and computational politics include, but are not limited to, principles and methods for political decision making, analysis, modeling, optimization, forecasting, simulation, and expression. The definition of these two new fields will greatly increase the pace of research and development in these important fields.

The New Interdisciplinary Fields of Political Engineering and Computational Politics

2015 ◽  
pp. 2250-2257 ◽  
Author(s):  
Ashu M. G. Solo
Keyword(s):  
Decision Making ◽  
Research And Development ◽  
Computer Science ◽  
Natural Science ◽  
Political Decision ◽  
Definition Of ◽  
Political Decision Making

This chapter describes two new interdisciplinary fields defined by Ashu M. G. Solo called “political engineering” and “computational politics.” Political engineering is the application of engineering, computer science, mathematics, or natural science to solving problems in politics. Computational politics is the application of computer science or mathematics to solving problems in politics. Political engineering and computational politics include, but are not limited to, principles and methods for political decision making, analysis, modeling, optimization, forecasting, simulation, and expression. The definition of these two new fields will greatly increase the pace of research and development in these important fields.

Professionalising Natural Science Education and Multipronged Open Distance Learning

2012 ◽  
pp. 306-320 ◽  
Author(s):  
B. PanduRanga Narasimharao
Keyword(s):  
Biological Sciences ◽  
Public Policy ◽  
Computer Science ◽  
Natural Science ◽  
The Other ◽  
Science Journalism ◽  
Physical Sciences ◽  
Master's Programs ◽  
Natural Science Education ◽  
And Training

Tobias et al. (1995) postulated in their book on “Rethinking Science as a Career” that Master’s programs could produce graduates who provide the same level of expertise and leadership as professionals do in other fields. They say that they would do so by having the ability to use the products of scholarship in their work and by being familiar with the practical aspects of emerging problem areas. If we consider natural science consisting of physical sciences, biological sciences, mathematics, geosciences, and computer science, degrees in computer science and geosciences served as credentials for practice, whereas physics, chemistry, and biological sciences served as classical graduate education. Robbins-Roth (2006) collected 22 career descriptions for science graduates ranging from public policy to investment banking, and from patent examining to broadcast science journalism. There are several sectors of the society where the principles and knowledge of these science disciplines are used. On the other hand, there are many of the graduates in these disciplines who either are working in areas completely unrelated to their education and training or are unemployable. The need for preparing the science graduates professionally is well recognized (Schuster, 2011; Vanderford, 2010; Narasimharao, Shashidhara Prasad and Nair, 2011; Chuck, 2011).

Professionalising Natural Science Education and Multipronged Open Distance Learning

2015 ◽  
pp. 138-152
Author(s):  
B. PanduRanga Narasimharao
Keyword(s):  
Biological Sciences ◽  
Public Policy ◽  
Computer Science ◽  
Natural Science ◽  
The Other ◽  
Science Journalism ◽  
Physical Sciences ◽  
Master's Programs ◽  
Natural Science Education ◽  
And Training

Tobias et al. (1995) postulated in their book on “Rethinking Science as a Career” that Master's programs could produce graduates who provide the same level of expertise and leadership as professionals do in other fields. They say that they would do so by having the ability to use the products of scholarship in their work and by being familiar with the practical aspects of emerging problem areas. If we consider natural science consisting of physical sciences, biological sciences, mathematics, geosciences, and computer science, degrees in computer science and geosciences served as credentials for practice, whereas physics, chemistry, and biological sciences served as classical graduate education. Robbins-Roth (2006) collected 22 career descriptions for science graduates ranging from public policy to investment banking, and from patent examining to broadcast science journalism. There are several sectors of the society where the principles and knowledge of these science disciplines are used. On the other hand, there are many of the graduates in these disciplines who either are working in areas completely unrelated to their education and training or are unemployable. The need for preparing the science graduates professionally is well recognized (Schuster, 2011; Vanderford, 2010; Narasimharao, Shashidhara Prasad and Nair, 2011; Chuck, 2011).

Stakes and Risks in the Prediction of Violent Criminal Behavior

1988 ◽  
Vol 3 (4) ◽  
pp. 247-262 ◽  
Author(s):  
Don M. Gottfredson ◽  
Stephen D. Gottfredson
Keyword(s):  
Public Policy ◽  
Decision Making ◽  
Criminal Justice ◽  
Criminal Behavior ◽  
Policy Formulation ◽  
Individual Decision ◽  
Individual Decision Making ◽  
Violent Criminal ◽  
Prediction Of Violence

Retributive and utilitarian goals for criminal justice decisions are in conflict. In part, this is because the retributive aim rejects prediction, while all utilitarian aims require it. In the context of this debate, we review research concerning the prediction of violence, and conclude that because such predictions are of low accuracy, they are only modestly useful for public policy formulation or for individual decision-making. Because we believe prediction, and utilitarian goals, to be important, this paper focuses on two issues that have potential for increasing the accuracy with which predictions may be made. One is the measurement of the seriousness of crime and ways to improve it. Second, we introduce the concept of societal stakes and suggest that this must be assessed as well. Finally, we propose a model that may be useful for lessening the conflict between retributive and utilitarian perspectives.

scholarly journals Sustainability Indicators: Relevance, Public Policy Support and Challenges

2019 ◽  
Vol 9 (2) ◽  
pp. 173
Author(s):  
Andre C. S. Batalhao ◽  
Denilson Teixeira ◽  
Maria de Fatima Martins ◽  
Hans Michael van Bellen ◽  
Adriana Cristina Ferreira Caldana
Keyword(s):  
Public Policy ◽  
Decision Making ◽  
Public Policies ◽  
Sustainability Indicators ◽  
Policy Support ◽  
Mixed Methods Approach ◽  
The Public ◽  
Development Goals ◽  
The Subject ◽  
Definition Of

Sustainability is a topic that has gained importance in several fields of knowledge, including the public, private and society spheres, based on the discussions that involve the definition of several public policies. Sustainability Indicators (SI) are metrics that seek to measure the level of sustainability and compile information for better decision-making concerning policies, programs, projects and actions related to sustainability. Demonstrated their relevance to public policies the SI appears as an essential tool for evaluating development goals as a sustainable proposal. In this way, this research aimed to discuss the main challenges and methodological limitations found in the use of SI, emphasizing the main fragilities identified in the literature. In methodological terms, the research has exploratory characteristics, supported by the mixed methods approach using a theoretical-empirical analysis, from the available literature on the subject and the methodologies used and the experience of researchers about the topic addressed. The main results demonstrated that Sustainability Indicators are tools that should be used to define, implement, evaluate and monitor public policies at all levels, considering the potentialities/weaknesses and priorities of each context.

Next Generation of Intelligent Cities

2021 ◽  
pp. 87-111
Author(s):  
Vijayaraghavan Varadharajan ◽  
Rian Leevinson J.
Keyword(s):  
Public Policy ◽  
Decision Making ◽  
Autonomous Vehicles ◽  
Policy Making ◽  
Next Generation ◽  
Government Organizations ◽  
Intelligent City ◽  
Intelligent Cities ◽  
Definition Of ◽  
Rapid Transformation

Over the past decade, intelligent cities have undergone rapid transformation. The definition of an intelligent city may vary based on the context and the purpose served. However, the next generation of intelligent cities will have unique characteristics that will set them apart from the existing intelligent cities. They will be more people-centered, and they will be formed through the fusion of technology, government, organizations, and people. This chapter explores four intelligent cities in Europe that are setting examples for innovation, ingenuity, technology, public policy making, and sustainable development: London, Amsterdam, Vienna, and Stockholm. With growing emphasis on people involvement in decision making, the intelligent city ecosystem is continuously evolving. However, technology continues to play a prominent role in shaping the intelligent city paradigm. In this contribution, the authors also examine different emerging technologies such as quantum computing, autonomous vehicles, AI, ML, etc. that could potentially impact the next generation of such cities.

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