John Chandler – författare

The book contains a wealth of detailed and fascinating case studies of New Public Management (NPM) in practice in the UK, exploring the enactment of NPM in its specific organizational contexts. A range of public services are covered including local government, education, social work and the police, with particular attention paid to the National Health Service. The editors introduce the case studies through an examination of the 'hydra-headed' nature of NPM, its variability between sectors and its contested character. This provides themes that are developed within the case studies, where, in varying organizational contexts, the meaning of NPM is negotiated and its impact on those working in the organization is explored. The book points to the complex, fluid and negotiated character of NPM, as well as its centrality in reconfiguring occupational identities and relations within public service organizations.

The book contains a wealth of detailed and fascinating case studies of New Public Management (NPM) in practice in the UK, exploring the enactment of NPM in its specific organizational contexts. A range of public services are covered including local government, education, social work and the police, with particular attention paid to the National Health Service. The editors introduce the case studies through an examination of the 'hydra-headed' nature of NPM, its variability between sectors and its contested character. This provides themes that are developed within the case studies, where, in varying organizational contexts, the meaning of NPM is negotiated and its impact on those working in the organization is explored. The book points to the complex, fluid and negotiated character of NPM, as well as its centrality in reconfiguring occupational identities and relations within public service organizations.

This insightful book draws on a range of contemporary and classic studies to explore the connection between the personal experience of work and the wider social structures in which it takes place.Identity at Work examines key social identities relevant to the workplace, such as those based on gender, sexual orientation, ethnicity and race, disability, age, occupation, class and organizational membership. Using research from a wide variety of countries and academic approaches, this book provides a readable and engaging introduction to the issues, exploring how people experience work, understand and present themselves at work, and relate to others. Providing an accessible investigation of work and identity, this text will be valuable to students looking at organizational behaviour, HRM, diversity management and the sociology of work.

This insightful book draws on a range of contemporary and classic studies to explore the connection between the personal experience of work and the wider social structures in which it takes place.Identity at Work examines key social identities relevant to the workplace, such as those based on gender, sexual orientation, ethnicity and race, disability, age, occupation, class and organizational membership. Using research from a wide variety of countries and academic approaches, this book provides a readable and engaging introduction to the issues, exploring how people experience work, understand and present themselves at work, and relate to others. Providing an accessible investigation of work and identity, this text will be valuable to students looking at organizational behaviour, HRM, diversity management and the sociology of work.

In 2001, George W. Bush created the White House Office of Faith-Based and Community Initiatives. The driving force behind the policy was to create a “level playing field” where faith-based organizations could compete on an equal footing with secular organizations for government funding of social aid programs. Given, on the one hand, the continuation of faith-based policy under Barack Obama and, on the other, the continued support by the vast majority of the American people for some form of such policy, the need has emerged to clearly understand what this policy is and the issues that it raises. Why? First, because the policy reveals new paradigms that explode traditional political and religious designations such as conservative–liberal or evangelical–progressive. Secondly, it is a policy which is setting precedents that with time will only become more entrenched in the institutional fabric of American government and the values of the culture. Finally, it does not seem to be a policy that is likely to just go away. And if it won’t go away, then, how should responsible policy be conducted?While John Chandler's Faith-Based Policy: A Litmus Test for Understanding Contemporary Americaresponds to this need to understand, it also acknowledges that there is already a substantial amount of documentation available, which, taken together, provides a comprehensive, though sometimes biased, picture of faith-based policy. This book contributes a relatively brief, impartial analysis that draws on and synthesizes the available information. More specifically, in order to dissipate the confusion surrounding the perceptions that many have had concerning the intention and meaning of the policy, this book provides insight into: 1) the theological visions of the faith-based actors behind the policy; 2) how these actors have tried to apply these visions as the program has evolved in the 2000s; 3) the divisiveness and debate that has characterized the faith-based experiment, and; 4) how all of the above may be held up for contemplation by the reader as a mirror of developing American culture.

Organization and Management: A Critical Text goes beyond the descriptive and managerial accounts of organizational behaviour. It offers a more critical and reflective text which contextualises and criticises conventional wisdom and attempts to re-orient the field by offering alternative approaches to the study of organizational behaviour. The authors take account of historical developments and key issues and ideas in their social, political, economic and global context. Areas examined include labour process issues, gender and other identities, flexibility and globalisation. More recent post-structuralist and post-modern approaches are also explored.

This textbook on practical data analytics unites fundamental principles, algorithms, and data. Algorithms are the keystone of data analytics and the focal point of this textbook. Clear and intuitive explanations of the mathematical and statistical foundations make the algorithms transparent. But practical data analytics requires more than just the foundations. Problems and data are enormously variable and only the most elementary of algorithms can be used without modification. Programming fluency and experience with real and challenging data is indispensable and so the reader is immersed in Python and R and real data analysis. By the end of the book, the reader will have gained the ability to adapt algorithms to new problems and carry out innovative analyses.This book has three parts:(a) Data Reduction: Begins with the concepts of data reduction, data maps, and information extraction. The second chapter introduces associative statistics, themathematical foundation of scalable algorithms and distributed computing. Practical aspects of distributed computing is the subject of the Hadoop and MapReduce chapter.(b) Extracting Information from Data: Linear regression and data visualization are the principal topics of Part II. The authors dedicate a chapter to the critical domain of Healthcare Analytics for an extended example of practical data analytics. The algorithms and analytics will be of much interest to practitioners interested in utilizing the large and unwieldly data sets of the Centers for Disease Control and Prevention's Behavioral Risk Factor Surveillance System.(c) Predictive Analytics Two foundational and widely used algorithms, k-nearest neighbors and naive Bayes, are developed in detail. A chapter is dedicated to forecasting. The last chapter focuses on streaming data and uses publicly accessible data streams originating from the Twitter API and the NASDAQ stock market in the tutorials.This book is intended for a one- or two-semester course in data analytics for upper-division undergraduate and graduate students in mathematics, statistics, and computer science. The prerequisites are kept low, and students with one or two courses in probability or statistics, an exposure to vectors and matrices, and a programming course will have no difficulty. The core material of every chapter is accessible to all with these prerequisites. The chapters often expand at the close with innovations of interest to practitioners of data science. Each chapter includes exercises of varying levels of difficulty. The text is eminently suitable for self-study and an exceptional resource for practitioners.

This textbook on practical data analytics unites fundamental principles, algorithms, and data. Algorithms are the keystone of data analytics and the focal point of this textbook. Clear and intuitive explanations of the mathematical and statistical foundations make the algorithms transparent. But practical data analytics requires more than just the foundations. Problems and data are enormously variable and only the most elementary of algorithms can be used without modification. Programming fluency and experience with real and challenging data is indispensable and so the reader is immersed in Python and R and real data analysis. By the end of the book, the reader will have gained the ability to adapt algorithms to new problems and carry out innovative analyses.This book has three parts:(a) Data Reduction: Begins with the concepts of data reduction, data maps, and information extraction. The second chapter introduces associative statistics, themathematical foundation of scalable algorithms and distributed computing. Practical aspects of distributed computing is the subject of the Hadoop and MapReduce chapter.(b) Extracting Information from Data: Linear regression and data visualization are the principal topics of Part II. The authors dedicate a chapter to the critical domain of Healthcare Analytics for an extended example of practical data analytics. The algorithms and analytics will be of much interest to practitioners interested in utilizing the large and unwieldly data sets of the Centers for Disease Control and Prevention's Behavioral Risk Factor Surveillance System.(c) Predictive Analytics Two foundational and widely used algorithms, k-nearest neighbors and naive Bayes, are developed in detail. A chapter is dedicated to forecasting. The last chapter focuses on streaming data and uses publicly accessible data streams originating from the Twitter API and the NASDAQ stock market in the tutorials.This book is intended for a one- or two-semester course in data analytics for upper-division undergraduate and graduate students in mathematics, statistics, and computer science. The prerequisites are kept low, and students with one or two courses in probability or statistics, an exposure to vectors and matrices, and a programming course will have no difficulty. The core material of every chapter is accessible to all with these prerequisites. The chapters often expand at the close with innovations of interest to practitioners of data science. Each chapter includes exercises of varying levels of difficulty. The text is eminently suitable for self-study and an exceptional resource for practitioners.