Science for Policy Handbook provides advice on how to bring science to the attention of policymakers. This resource is dedicated to researchers and research organizations aiming to achieve policy impacts. The book includes lessons learned along the way, advice on new skills, practices for individual researchers, elements necessary for institutional change, and knowledge areas and processes in which to invest. It puts co-creation at the centre of Science for Policy 2.0, a more integrated model of knowledge-policy relationship. Covers the vital area of science for policymaking Includes contributions from leading practitioners from the Joint Research Centre/European Commission Provides key skills based on the science-policy interface needed for effective evidence-informed policymaking Presents processes of knowledge production relevant for a more holistic science-policy relationship, along with the types of knowledge that are useful in policymaking

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.

Governments fail to provide the public goods needed for development when its leaders knowingly and deliberately ignore sound technical advice or are unable to follow it, despite the best of intentions, because of political constraints. This report focuses on two forces—citizen engagement and transparency—that hold the key to solving government failures by shaping how political markets function. Citizens are not only queueing at voting booths, but are also taking to the streets and using diverse media to pressure, sanction and select the leaders who wield power within government, including by entering as contenders for leadership. This political engagement can function in highly nuanced ways within the same formal institutional context and across the political spectrum, from autocracies to democracies. Unhealthy political engagement, when leaders are selected and sanctioned on the basis of their provision of private benefits rather than public goods, gives rise to government failures. The solutions to these failures lie in fostering healthy political engagement within any institutional context, and not in circumventing or suppressing it. Transparency, which is citizen access to publicly available information about the actions of those in government, and the consequences of these actions, can play a crucial role by nourishing political engagement.

One of the pathways by which the scientific community confirms the validity of a new scientific discovery is by repeating the research that produced it. When a scientific effort fails to independently confirm the computations or results of a previous study, some fear that it may be a symptom of a lack of rigor in science, while others argue that such an observed inconsistency can be an important precursor to new discovery. Concerns about reproducibility and replicability have been expressed in both scientific and popular media. As these concerns came to light, Congress requested that the National Academies of Sciences, Engineering, and Medicine conduct a study to assess the extent of issues related to reproducibility and replicability and to offer recommendations for improving rigor and transparency in scientific research. Reproducibility and Replicability in Science defines reproducibility and replicability and examines the factors that may lead to non-reproducibility and non-replicability in research. Unlike the typical expectation of reproducibility between two computations, expectations about replicability are more nuanced, and in some cases a lack of replicability can aid the process of scientific discovery. This report provides recommendations to researchers, academic institutions, journals, and funders on steps they can take to improve reproducibility and replicability in science.

Science and technology are embedded in virtually every aspect of modern life. As a result, people face an increasing need to integrate information from science with their personal values and other considerations as they make important life decisions about medical care, the safety of foods, what to do about climate change, and many other issues. Communicating science effectively, however, is a complex task and an acquired skill. Moreover, the approaches to communicating science that will be most effective for specific audiences and circumstances are not obvious. Fortunately, there is an expanding science base from diverse disciplines that can support science communicators in making these determinations. Communicating Science Effectively offers a research agenda for science communicators and researchers seeking to apply this research and fill gaps in knowledge about how to communicate effectively about science, focusing in particular on issues that are contentious in the public sphere. To inform this research agenda, this publication identifies important influences â€" psychological, economic, political, social, cultural, and media-related â€" on how science related to such issues is understood, perceived, and used.

A state-of-the-art account of what we know and do not know about the effects of digital technology on democracy.

"In Playing Politics with Science, David B. Resnik explores the philosophical, political, and ethical issues related to the politicization of science and develops a conceptual framework for thinking about government restrictions on scientific practice."--BOOK JACKET.

This report examines the influence of trust on policy making and explores some of the steps governments can take to strengthen public trust.

This open access book presents a ground-breaking approach to developing micro-foundations for demography and migration studies. It offers a unique and novel methodology for creating empirically grounded agent-based models of international migration – one of the most uncertain population processes and a top-priority policy area. The book discusses in detail the process of building a simulation model of migration, based on a population of intelligent, cognitive agents, their networks and institutions, all interacting with one another. The proposed model-based approach integrates behavioural and social theory with formal modelling, by embedding the interdisciplinary modelling process within a wider inductive framework based on the Bayesian statistical reasoning. Principles of uncertainty quantification are used to devise innovative computer-based simulations, and to learn about modelling the simulated individuals and the way they make decisions. The identified knowledge gaps are subsequently filled with information from dedicated laboratory experiments on cognitive aspects of human decision-making under uncertainty. In this way, the models are built iteratively, from the bottom up, filling an important epistemological gap in migration studies, and social sciences more broadly.