Paul Stretesky – författare

Drawing on the work of Allan Schnaiberg, this book returns political economy to green criminology and examines how the expansion of capitalism shapes environmental law, crime and justice. The book is organized around crimes of ecological withdrawals and ecological additions.The Treadmill of Crime is written by acclaimed experts on the subject of green criminology and examines issues such as the crime in the energy sector as well as the release of toxic waste into the environment and its impact on ecosystems. This book also sets a new research agenda by highlighting problems of ecological disorganization for animal abuse and social disorganization.This book will be of interest to students, researchers and academics in the fields of criminology, political science, environmental sociology, and natural resources.

Drawing on the work of Allan Schnaiberg, this book returns political economy to green criminology and examines how the expansion of capitalism shapes environmental law, crime and justice. The book is organized around crimes of ecological withdrawals and ecological additions.The Treadmill of Crime is written by acclaimed experts on the subject of green criminology and examines issues such as the crime in the energy sector as well as the release of toxic waste into the environment and its impact on ecosystems. This book also sets a new research agenda by highlighting problems of ecological disorganization for animal abuse and social disorganization.This book will be of interest to students, researchers and academics in the fields of criminology, political science, environmental sociology, and natural resources.

This book takes a unique approach to explaining permutation statistical methods for advanced undergraduate students, graduate students, faculty, researchers, and other professionals interested in the areas of criminology or criminal justice. The book integrates permutation statistical methods with a wide range of classical statistical methods. It opens with a comparison of two models of statistical inference: the classical population model espoused by J. Neyman and E. Pearson and the permutation model first introduced by R.A. Fisher and E.J.G. Pitman. Numerous comparisons of permutation and classical statistical methods are illustrated with examples from criminology and criminal justice and supplemented with a variety of R scripts for ease of computation. The text follows the general outline of an introductory textbook in statistics with chapters on central tendency, variability, one-sample tests, two-sample tests, matched-pairs tests, completely-randomized analysis of variance, randomized-blocks analysis of variance, simple linear regression and correlation, and the analysis of goodness of fit and contingency.Unlike classical statistical methods, permutation statistical methods do not rely on theoretical distributions, avoid the usual assumptions of normality and homogeneity, depend solely on the observed data, and do not require random sampling, making permutation statistical methods ideal for analyzing criminology and criminal justice databases. Permutation methods are relatively new in that it took modern computing power to make them available to those working in criminology and criminal justice research.The book contains detailed examples of permutation analyses. Each analysis is paired with a conventional analysis; for example, a permutation test of the difference between experimental and control groups is contrasted with Student's two-sample $t$ test. An added feature is the inclusion of multiple historical notes on the origin and development of both parametric and conventional tests and measures.  Designed for an audience with a basic statistical background and a strong interest in parametric and non-parametric statistics, the book can easily serve as a textbook for undergraduate and graduate students in criminology, criminal justice, or sociology, as well as serving as a research source for faculty, researchers, and other professionals in the area of criminology. No statistical training beyond a first course in statistics is required, but some knowledge of, or interest in, criminology or criminal justice is assumed.