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"How many citizens take part in moral and political decisions concerning the results obtained by the contemporary life sciences? Should they blindly follow skilled demagogues or false and deceptive leaders? Should they adhere to the voice of the majority, or should they take a different decisional path? Deliberative democracy answers these questions, but what is deliberative democracy? Can we really deliberate if we are completely ignorant of the relevant issue? What about ethical or political expertise, is it strictly necessary? Finally, and most significantly, can a deliberative process take place if we ignore the techniques governing it; that is, the techniques required to be minimally skilled in rational argumentation?Giovanni Boniolo goes back to the historical and theoretical foundations of deliberation showing us, with some irony, that deliberation is a matter of competence, and not just a matter of a right to decide. His conclusion might not delight everyone: “anyone who is not sufficiently acquainted with the subject matter or lacks the sufficient deliberative competence ought not be admitted to deliberative discussions. This restriction makes both good deliberation and a proper deliberative democracy possible, otherwise debate degenerates into demagogy and hypocrisy”."

"The constitutional referendum has become a vital feature of modern constitution-making and reform. This book provides the first full-length analysis of the theoretical foundations of constitutional referendums, assessing their democratic credentials and the design decisions that affect the value and legitimacy of the referendum process. "

"This volume, reviewing and describing major threads in the mathematical modeling of science dynamics for a wider academic and professional audience. The model classes presented cover stochastic and statistical models, system-dynamics approaches, agent-based simulations, population-dynamics models, and complex-network models. The book comprises an introduction and a foundational chapter that defines and operationalizes terminology used in the study of science, as well as a review chapter that discusses the history of mathematical approaches to modeling science from an algorithmic-historiography perspective. It concludes with a survey of remaining challenges for future science models and their relevance for science and science policy."