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Does the public trust science? Scientists? Scientific organizations? What roles do trust and the lack of trust play in public debates about how science can be used to address such societal concerns as childhood vaccination, cancer screening, and a warming planet? What could happen if social trust in science or scientists faded? These types of questions led the Roundtable on Public Interfaces of the Life Sciences of the National Academies of Sciences, Engineering, and Medicine to convene a 2-day workshop on May 5-6, 2015 on public trust in science. This report explores empirical evidence on public opinion and attitudes toward life sciences as they relate to societal issues, whether and how contentious debate about select life science topics mediates trust, and the roles that scientists, business, media, community groups, and other stakeholders play in creating and maintaining public confidence in life sciences. Does the Public Trust Science? Trust and Confidence at the Interfaces of the Life Sciences and Society highlights research on the elements of trust and how to build, mend, or maintain trust; and examine best practices in the context of scientist engagement with lay audiences around social issues.
Examines the problem of how governments can most effectively make use of scientists, and tells the story of the wartime enmity between two powerful British scientists.
In this previously unpublished manuscript, found in the Rothbard Archives, Rothbard deftly turns the tables on the supporters of big government and their mandate for control of research and development in all areas of the hard sciences. What R&D should be encouraged and funded, what inventions should be supported, and what areas should be given research grants, etc.? These decisions can only be decided by markets unburdened by government meddling and intervention. Rothbard shows that science best advances under the free market: the claims to the contrary of the centralizers are spurious. The best course of action for government is to get out of the way ...
This daring attempt to juxtapose the histories of Britain, western science, and imperialism shows how colonial expansion, from the age of Alexander the Great to the 20th century, led to complex kinds of knowledge.
Margaret Thatcher was prime minister from 1979 to 1990, during which time her Conservative administration transformed the political landscape of Britain. Science Policy under Thatcher is the first book to examine systematically the interplay of science and government under her leadership. Thatcher was a working scientist before she became a professional politician, and she maintained a close watch on science matters as prime minister. Scientific knowledge and advice were important to many urgent issues of the 1980s, from late Cold War questions of defence to emerging environmental problems such as acid rain and climate change. Drawing on newly released primary sources, Jon Agar explores how Thatcher worked with and occasionally against the structures of scientific advice, as the scientific aspects of such issues were balanced or conflicted with other demands and values. To what extent, for example, was the freedom of the individual scientist to choose research projects balanced against the desire to secure more commercial applications? What was Thatcher’s stance towards European scientific collaboration and commitments? How did cuts in public expenditure affect the publicly funded research and teaching of universities? In weaving together numerous topics, including AIDS and bioethics, the nuclear industry and strategic defence, Agar adds to the picture we have of Thatcher and her radically Conservative agenda, and argues that the science policy devised under her leadership, not least in relation to industrial strategy, had a prolonged influence on the culture of British science.
A new, substantially updated, and expanded version of a classic work on how to evaluate public policy published over a decade ago.
The integrity of knowledge that emerges from research is based on individual and collective adherence to core values of objectivity, honesty, openness, fairness, accountability, and stewardship. Integrity in science means that the organizations in which research is conducted encourage those involved to exemplify these values in every step of the research process. Understanding the dynamics that support â€" or distort â€" practices that uphold the integrity of research by all participants ensures that the research enterprise advances knowledge. The 1992 report Responsible Science: Ensuring the Integrity of the Research Process evaluated issues related to scientific responsibility and the conduct of research. It provided a valuable service in describing and analyzing a very complicated set of issues, and has served as a crucial basis for thinking about research integrity for more than two decades. However, as experience has accumulated with various forms of research misconduct, detrimental research practices, and other forms of misconduct, as subsequent empirical research has revealed more about the nature of scientific misconduct, and because technological and social changes have altered the environment in which science is conducted, it is clear that the framework established more than two decades ago needs to be updated. Responsible Science served as a valuable benchmark to set the context for this most recent analysis and to help guide the committee's thought process. Fostering Integrity in Research identifies best practices in research and recommends practical options for discouraging and addressing research misconduct and detrimental research practices.
Public Policy Analytics: Code & Context for Data Science in Government teaches readers how to address complex public policy problems with data and analytics using reproducible methods in R. Each of the eight chapters provides a detailed case study, showing readers: how to develop exploratory indicators; understand ‘spatial process’ and develop spatial analytics; how to develop ‘useful’ predictive analytics; how to convey these outputs to non-technical decision-makers through the medium of data visualization; and why, ultimately, data science and ‘Planning’ are one and the same. A graduate-level introduction to data science, this book will appeal to researchers and data scientists at the intersection of data analytics and public policy, as well as readers who wish to understand how algorithms will affect the future of government.
"The guide is designed to direct the reader to the vast and diverse scientific and technical information available from the United States government." Discusses and references fellowships and other awards; research in progress; technical reports; periodicals; patents; translations; standards; audiovisual sources; indexes and abstracts; data bases; information analysis centers; and reference sources. Entries give descriptive information. Index.