John David – författare

This book should be useful to anyone interested in identifying the causes of civil conflict and doing something to end it. It even suggests a pathway for the lay reader. Civil conflict is a persistent source of misery to humankind. Its study, however, lacks a comprehensive theory of its causes. Nevertheless, the question of cooperation or conflict is at the heart of political economy. This book introduces Machine Learning to explore whether there even is a unified theory of conflict, and if there is, whether it is a ‘good’ one. A good theory is one that not only identifies the causes of conflict, but also identifies those causes that predict conflict. Machine learning algorithms use out of sample techniques to choose between competing hypotheses about the sources of conflict according to their predictive accuracy. This theoretically agnostic ‘picking’ has the added benefit of offering some protection against many of the problems noted in the current literature; the tangled causality between conflict and its correlates, the relative rarity of civil conflict at a global level, missing data, and spectacular statistical assumptions. This book argues that the search for a unified theory of conflict must begin among these more predictive sources of civil conflict. In fact, in the book, there is a clear sense that game theoretic rational choice models of bargaining/commitment failure predict conflict better than any other approach. In addition, the algorithms highlight the fact that conflict is path dependent - it tends to continue once started. This is intuitive in many ways but is roundly ignored as a matter of science. It should not. Further, those causes of conflict that best predict conflict can be used as policy levers to end or prevent conflict. This book should therefore be of interest to military and civil leaders engaged in ending civil conflict. Last, though not least, the book highlights how the sources of conflict affect conflict. This additional insight may allow the crafting of policies that match a country’s specific circumstance.

Practical Stone Masonry is the first major book in nearly seventy years on the craft of the stonemason. Today the work of the stonemason is almost exclusively confined to the repair of historic buildings, requiring a full working knowledge of the detailed traditional craft practices relating to repairs. This book addresses that need. It covers the basic methods of working stone, the making of specialized tools, and, for the first time, a full analysis of the procedures for setting-out for repairs. A broad description of the nature and problems of stone also includes guidance on selection. In addition, the authors look at the causes of decay in stone and outline methods for repair of both stone and mortar. "Practical Stone Masonry" contains essential advice for working masons and apprentices, and all those engaged in planning and supervising such works. It includes: the basic methods of working stone; how to make specialized tools; the procedures for setting-out for repairs explained; and, the nature and problems of stone plus a guide to selection.

This book uses machine-learning to identify the causes of conflict from among the top predictors of conflict. This methodology elevates some complex causal pathways that cause civil conflict over others, thus teasing out the complex interrelationships between the most important variables that cause civil conflict.