Info in global economy

In chapter1, the focus was on targeting five communities that make up the core field for ICT-enabled policy-making.  Name those five communities involved, and briefly explain to support your answer?

Q1 – Who are these five communities? 

• identify and name the five communities

• provide a short narrative for each

====================================================

=====

After reading through the Chapters, its reasonable to state that, Koliba and Zia (2015) observed that advancements in high-speed computing, digitization of data and improved collaboration across informatics project platforms create the need for quality simulation modeling education for two types of public servants.

Q2 – Who are these public servants? 

• identify and name these two types of public servants

• provide a short narrative of why it’s important for these servants to receive this education

====================================================

According to Chalmers et al. (1995, p. 173), validation of a simulation against empirical data is not about comparing “the real world” and the simulation output; but it is a comparison of what is observed as the real world with what is observed as the output.  In this scenario, both are constructions of observers and their views concerning relevant agents and their attributes (Chalmers et al., 1995). Constructing reality and simulation are just two-way of an observer seeing the world. The issue of objective, formation is not normally considered by computer scientists relying on the standard view: data is “organized” by a human programmer who appropriately fits them into the chosen representational structure. In most cases, researchers apply their prior knowledge of the nature of the problem to hand-code a representation of the data into a near-optimal form.

Q3 – In consideration of the constructionist’s views regarding the quality of social simulation as an example of a research-based and policy modeling approach, what happens when the possibility of validating a simulation by comparing it with empirical data from the “real world” is questioned? 

• provide a short and clear narrative with an explanation of what happens.

Chapter1- intro to policy making in the digital Age

Chapter2-Educating Public managers and policy analysts in the era of informatics

Chapter3-The Quality of social simulation: An example from research policy modeling

Chapter Goals and Objectives
Overall – students will learn and understand why:
▪ the explosive growth in data, computational power, and social media create new opportunities for innovating governance and policy-making ▪ global information and communications technology (ICT) developments affect policy-making cycle and result in drastic changes in the policy development
▪ organizations need the digital developments, new approaches, concepts, instruments, and methods as they operate in the complex and uncertain societies
▪ e-government policy, e-policy, policy informatics, and data science are different

1. Intro to Policy-Making in the Digital Age
❖ Identification of complexity and uncertainty in policy-making
▪ policy-making is driven by the need to solve societal problems
❖ Developments
▪ developments that influence the traditional way of policy-making
❖ Availability of Big and Open Linked Data (BOLD)
▪ Learn and understand the needs for multiple perspectives to stimulate new practices
❖ Rise of hybrid simulation approaches
▪ allows decision-makers to understand the essence of a policy…
❖ Ubiquitous user engagement
▪ considerable complexities encountered in the design of public policy
❖ Combining disciplines in e-government policy-making
▪ practice driven, employs modeling techniques, needs knowledge from various fields, and maintains focus on governance and policy-making

2. Why educate public managers and policy analysts in the era of informatics
❖ Types of practitioner orientations to policy informatics
▪ two “ideal types” of policy informatics practitioner, require greater and greater levels of technical mastery of analytics techniques and approaches
❖ Policy informatics-savvy public managers
▪ need to know what kinds of questions that policy informatics projects or programs can answer or not answer
▪ need to know how to contract with and/or manage data managers, policy analysts, and modelers
❖ Second type of practitioners – policy informatics analysts
▪ need for policy analysts – move beyond basic surveys of research methods
❖ Applications to professional masters programs
▪ PA 301: Foundations of Public Administration
▪ PA 306: Policy Systems ▪ PA 308: Decision-Making Models ▪ PA 317: Systems Analysis and Strategic Management

3. The quality of social simulation: An example from research policy modeling
❖ Communicative skills, patience, willingness to compromise
▪ policy-making is driven by the need to solve societal problems
❖ Quality in social simulation
▪ develop models from a simulation as “an illusory appearance that manages a reality effect” (cf. Norris 1992)
❖ Assessing quality: the example – the SKIN approach
▪ policy modeling of SKIN – birth of the SKIN inspired by the idea of bringing theory on innovation networks stemming from innovation economics and economic sociology, onto the computer— a computer theory instantiated, calibrated, tested, and validated by empirical data
❖ INFO-SKIN – the constructivist view
▪ ability to use scenario-based modeling as a worksite for “reality constructions
❖ INFO-SKIN – the user community view
▪ stakeholders must learn about the scope and applicability of the methods; researchers get acquainted with the problems policy makers have to solve