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.

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.

From the AgAnda for Education in a Democracy Series

Sponsored by the National Network for Educational Renewal

Introduction by John I. Goodlad

This volume from the AgAnda for Education in a Democracy series introduces the four-part mission that guides the National Network for Educational Renewal's agAnda:

Enculturate the young in a democracy
• Ensure access to knowledge for all students
• Provide caring and effective pedagogy

Using real-life case examples from an innovative national leadership program and its local and regional affiliates, the authors demonstrate why effective leadership is essential to advancing this vital agAnda and how leadership capacity and commitment can be cultivated. From curriculum to evaluation, this important guide outlines the core concepts and winning strategies for building leadership skills in school administrators, teachers, teacher educators, and other university faculty.

Originally published in 1920, this book contains a selection of passages from Rabelais. Detailed notes and a biography of Rabelais are also included. This book will be of value to anyone with an interest in the works of Rabelais and French Renaissance literature.