Data Science in the Public Interest Improving Government Performance in the Workforce

This book PDF is perfect for those who love Political Science genre, written by Joshua D. Hawley and published by W.E. Upjohn Institute which was released on 22 July 2020 with total hardcover pages 152. You could read this book directly on your devices with pdf, epub and kindle format, check detail and related Data Science in the Public Interest Improving Government Performance in the Workforce books below.

Data Science in the Public Interest Improving Government Performance in the Workforce

Author	: Joshua D. Hawley
File Size	: 46,6 Mb
Publisher	: W.E. Upjohn Institute
Language	: English
Release Date	: 22 July 2020
ISBN	: 9780880996747
Pages	: 152 pages

Get Book

Data Science in the Public Interest Improving Government Performance in the Workforce by Joshua D. Hawley Book PDF Summary

This book is about how new and underutilized types of big data sources can inform public policy decisions related to workforce development. Hawley describes how government is currently using data to inform decisions about the workforce at the state and local levels. He then moves beyond standardized performance metrics designed to serve federal agency requirements and discusses how government can improve data gathering and analysis to provide better, up-to-date information for government decision making.

Data Science in the Public Interest Improving Government Performance in the Workforce by Joshua D. Hawley

Get Book

Ethical Data Science by Anne L. Washington

Can data science truly serve the public interest? Data-driven analysis shapes many interpersonal, consumer, and cultural experiences yet scientific solutions to social problems routinely stumble. All too often, predictions remain solely a technocratic instrument that sets financial interests against service to humanity. Amidst a growing movement to use science for

Get Book

Elgar Encyclopedia of Law and Data Science by Comandé, Giovanni

This Encyclopedia brings together jurists, computer scientists, and data analysts to map the emerging field of data science and law for the first time, uncovering the challenges, opportunities, and fault lines that arise as these groups are increasingly thrown together by expanding attempts to regulate and adapt to a data-driven

Get Book

Ethical Data Science by Anne L. Washington

Download or read online Ethical Data Science written by Anne L. Washington, published by Unknown which was released on 2023. Get Ethical Data Science Books now! Available in PDF, ePub and Kindle.

Get Book

Data Science for Social Good by Massimo Lapucci,Ciro Cattuto

This book is a collection of reflections by thought leaders at first-mover organizations in the exploding field of "Data Science for Social Good", meant as the application of knowledge from computer science, complex systems and computational social science to challenges such as humanitarian response, public health, sustainable development. The book

Get Book

How to Think about Data Science by Diego Miranda-Saavedra

This book is a timely and critical introduction for those interested in what data science is (and isn’t), and how it should be applied. The language is conversational and the content is accessible for readers without a quantitative or computational background; but, at the same time, it is also

Get Book

Data Science for Public Policy by Jeffrey C. Chen,Edward A. Rubin,Gary J. Cornwall

This textbook presents the essential tools and core concepts of data science to public officials, policy analysts, and economists among others in order to further their application in the public sector. An expansion of the quantitative economics frameworks presented in policy and business schools, this book emphasizes the process of

Get Book

Frontiers in Data Science by Matthias Dehmer,Frank Emmert-Streib

Frontiers in Data Science deals with philosophical and practical results in Data Science. A broad definition of Data Science describes the process of analyzing data to transform data into insights. This also involves asking philosophical, legal and social questions in the context of data generation and analysis. In fact, Big

Get Book