Sean Bergin – författare

This book is a comprehensive look at the brutal and extensive genocide that occurred in Cambodia in the mid- to late 1970s at the hands of Pol Pot and the Khmer Rouge. It provides background history as well as a description of the genocide itself, and its aftermath.

The appalling Cambodian genocide remains barely studied even to this day. Yet nearly two million Cambodians (around 20 percent of Cambodia’s population) died between 1975 and 1979 as a result of the dictator Pol Pot and the Khmer Rouge Communist government. Innocent Cambodians were murdered, starved, and tortured. This fascinating book offers an overview of this tiny Asian country’s history, framing the events that led up to this tragic genocide. Readers will learn about the key players in the genocide, as well as the complications in obtaining justice in its aftermath.

Where would we be without paper? We’d have no books or magazines, no paper money, and no material on which to paint or draw. But fortunately, paper has been around for thousands of years—and we have ancient China to thank for that! This detailed volume explains the history of paper, from its likely origins with hemp fiber to its use for books and documents and its growing spread to other areas of the world. Photos of historical artifacts bring history to life, and further sources encourage readers to learn more.

This book highlights new and innovative approaches to archaeological research using computational modeling while focusing on the Neolithic transition around the world.The transformative effect of the spread and adoption of agriculture in prehistory cannot be overstated. Consequently, archaeologists have often focused their research on this transition, hoping to understand both the ecological causes and impacts of this shift, as well as the social motivations and constraints involved. Given the complex interplay of socio-ecological factors, the answers to these types of questions cannot be found using traditional archaeological methods alone. Computational modeling techniques have emerged as an effective approach for better understanding prehistoric data sets and the linkages between social and ecological factors at play during periods of subsistence change. Such techniques include agent-based modeling, Bayesian modeling, GIS modeling of the prehistoric environment, and the modeling of small-scale agriculture. As more archaeological data sets aggregate regarding the transition to agriculture, researchers are often left with few ways to relate these sets to one another.Computational modeling techniques such as those described above represent a critical next step in providing archaeological analyses that are important for understanding human prehistory around the world.  Given its scope, this book will appeal to the many interdisciplinary scientists and researchers whose work involves archaeology and computational social science. Chapter “The Spread of Agriculture: Quantitative Laws in Prehistory?” is available open access under a Creative Commons Attribution 4.0 International License via springer.com.

This book highlights new and innovative approaches to archaeological research using computational modeling while focusing on the Neolithic transition around the world.

The transformative effect of the spread and adoption of agriculture in prehistory cannot be overstated. Consequently, archaeologists have often focused their research on this transition, hoping to understand both the ecological causes and impacts of this shift, as well as the social motivations and constraints involved. Given the complex interplay of socio-ecological factors, the answers to these types of questions cannot be found using traditional archaeological methods alone. Computational modeling techniques have emerged as an effective approach for better understanding prehistoric data sets and the linkages between social and ecological factors at play during periods of subsistence change. Such techniques include agent-based modeling, Bayesian modeling, GIS modeling of the prehistoric environment, and the modeling of small-scale agriculture. As more archaeological data sets aggregate regarding the transition to agriculture, researchers are often left with few ways to relate these sets to one another.

Computational modeling techniques such as those described above represent a critical next step in providing archaeological analyses that are important for understanding human prehistory around the world.  Given its scope, this book will appeal to the many interdisciplinary scientists and researchers whose work involves archaeology and computational social science. 

Chapter “The Spread of Agriculture: Quantitative Laws in Prehistory?” is available open access under a Creative Commons Attribution 4.0 International License via springer.com.