Nigel Gilbert – författare

The profound changes in the labour market during the 1980s are examined in this book in relation to the ideas of flexible specialization and the "flexible firm" and Marxist regulation theory, supplemented by fresh empirical evidence concerning changes in the labour process. Three related concepts have emerged around which there has been a dramatic crystallization: Fordism, post-Fordism and, supposedly linking the two, various manifestations of economic flexibility. There has been, it is suggested, a profound change in the labour process towards the "flexible worker" and in the labour market towards a "flexible workforce". Three approaches to explain these changes are especially important and provide the major focus for this book: Marxist regulation theory; the notion of flexible specialization associated with the "new" institutional economics; and the model of the flexible firm derived from the managerialist literature. In the book, the diverse claims made by these three approaches are subject to empirical and theoretical investigation and their wider implications are examined in relation to emerging patterns of work in advanced societies.

What can computer simulation contribute to the social sciences?Which of the many approaches to simulation would be best for my social science project?How do I design, carry out and analyse the results from a computer simulation?Interest in social simulation has been growing rapidly worldwide as a result of increasingly powerful hardware and software and also a rising interest in the application of ideas of complexity, evolution, adaptation and chaos in the social sciences. Simulation for the Social Scientist is a practical textbook on the techniques of building computer simulations to assist understanding of social and economic issues and problems.

This authoritative book details all the common approaches to social simulation, to provide social scientists with an appreciation of the literature and allow those with some programming skills to create their own simulations.

New for this edition:

A new chapter on designing multi-agent systems, to support the fact that multi-agent modelling has become the most common approach to simulationNew examples and guides to current softwareUpdated throughout to take new approaches into accountThe book is an essential tool for social scientists in a wide range of fields, particularly sociology, economics, anthropology, geography, organizational theory, political science, social policy, cognitive psychology and cognitive science. It will also appeal to computer scientists interested in distributed artificial intelligence, multi-agent systems and agent technologies.

Using data taken from a major European Union funded project on speech understanding, the SunDial project, this book considers current perspectives on human computer interaction and argues for the value of an approach taken from sociology which is based on conversation analysis.

Using data taken from a major European Union funded project on speech understanding, the SunDial project, this book considers current perspectives on human computer interaction and argues for the value of an approach taken from sociology which is based on conversation analysis.

From Postgraduate to Social Scientist is essential reading for any postgraduate or new researcher who is interested in a career in the social sciences. The book describes the skills needed for success in moving from being a student to becoming an academic or professional social scientist. Written by experts in the field, Gilbert et al. offer a unique insider's view of how to make the transition.

By adopting a clear and accessible approach, this book encourages students embarking on the journey towards becoming a social scientist to engage with every aspect of the process:

Reviewing and writing skills Using the Internet Research ethics Intellectual property rights Writing research proposals Project management Writing a thesis and reports Creating presentations, press releases and popular articles Teaching skills Careers in social science.

From Postgraduate to Social Scientist is designed for postgraduate students and researchers across the social sciences. It will be invaluable for courses that aim to satisfy the Economic and Social Research Council's 'Training Guidelines' requirements for doctoral programmes.

SAGE Study Skills are essential study guides for students of all levels. From how to write great essays and succeeding at university, to writing your undergraduate dissertation and doing postgraduate research, SAGE Study Skills help you get the best from your time at university. Visit the SAGE Study Skills hub for tips, resources and videos on study success!

 

From Postgraduate to Social Scientist is essential reading for any postgraduate or new researcher who is interested in a career in the social sciences. The book describes the skills needed for success in moving from being a student to becoming an academic or professional social scientist. Written by experts in the field, Gilbert et al. offer a unique insider's view of how to make the transition.

By adopting a clear and accessible approach, this book encourages students embarking on the journey towards becoming a social scientist to engage with every aspect of the process:

Reviewing and writing skills Using the Internet Research ethics Intellectual property rights Writing research proposals Project management Writing a thesis and reports Creating presentations, press releases and popular articles Teaching skills Careers in social science.

From Postgraduate to Social Scientist is designed for postgraduate students and researchers across the social sciences. It will be invaluable for courses that aim to satisfy the Economic and Social Research Council's 'Training Guidelines' requirements for doctoral programmes.

SAGE Study Skills are essential study guides for students of all levels. From how to write great essays and succeeding at university, to writing your undergraduate dissertation and doing postgraduate research, SAGE Study Skills help you get the best from your time at university. Visit the SAGE Study Skills hub for tips, resources and videos on study success!

 

The most exciting and productive areas of academic inquiry are often where the interests of two disciplines meet. This is certainly the case for the subject of this book, originally published in 1994, which explores the contribution that computer-based modelling and artificial intelligence can make to understanding fundamental issues in social science. Simulating Societies shows how computer simulations can help to clarify theoretical approaches, contribute to the evaluation of alternative theories, and illuminate one of the major issues of the social sciences: how social phenomena can "emerge" from individual action. The authors discuss how simulation models can be constructed using recently developed artificial intelligence techniques and they consider the methodological issues involved in using such models for theory development, testing and experiment. The introductory chapters situate the book within social science, and suggest why the time was ripe for significant progress, before defining basic terminology, showing how simulation has been used to theorize about organizations, and indicating through examples some of the fundamental issues involved in simulation. The main body of the text provides case studies drawn from economics, anthropology, archaeology, planning, social psychology and sociology.The appeal of this path-breaking book was twofold. It offered an essential introduction to simulation for social scientists and it provided case study applications for computer scientists interested in the latest advances in the burgeoning area of distributed artificial intelligence (DAI) at the time.

The most exciting and productive areas of academic inquiry are often where the interests of two disciplines meet. This is certainly the case for the subject of this book, originally published in 1994, which explores the contribution that computer-based modelling and artificial intelligence can make to understanding fundamental issues in social science. Simulating Societies shows how computer simulations can help to clarify theoretical approaches, contribute to the evaluation of alternative theories, and illuminate one of the major issues of the social sciences: how social phenomena can "emerge" from individual action. The authors discuss how simulation models can be constructed using recently developed artificial intelligence techniques and they consider the methodological issues involved in using such models for theory development, testing and experiment. The introductory chapters situate the book within social science, and suggest why the time was ripe for significant progress, before defining basic terminology, showing how simulation has been used to theorize about organizations, and indicating through examples some of the fundamental issues involved in simulation. The main body of the text provides case studies drawn from economics, anthropology, archaeology, planning, social psychology and sociology.The appeal of this path-breaking book was twofold. It offered an essential introduction to simulation for social scientists and it provided case study applications for computer scientists interested in the latest advances in the burgeoning area of distributed artificial intelligence (DAI) at the time.

First published in 1993, Analyzing Tabular Data is an accessible text introducing a powerful range of analytical methods. Empirical social research almost invariably requires the presentation and analysis of tables, and this book is for those who have little prior knowledge of quantitative analysis or statistics, but who have a practical need to extract the most from their data. The book begins with an introduction to the process of data analysis and the basic structure of cross-tabulations. At the core of the methods described in the text is the loglinear model. This and the logistic model, are explained and their application to causal modelling, to event history analysis, and to social mobility research are described in detail. Each chapter concludes with sample programs to show how analysis on typical datasets can be carried out using either the popular computer packages, SPSS, or the statistical programme, GLIM. The book is packed with examples which apply the methods to social science research.Sociologists, geographers, psychologists, economists, market researchers and those involved in survey research in the fields of planning, evaluation and policy will find the book to be a clear and thorough exposition of methods for the analysis of tabular data.

First published in 1993, Analyzing Tabular Data is an accessible text introducing a powerful range of analytical methods. Empirical social research almost invariably requires the presentation and analysis of tables, and this book is for those who have little prior knowledge of quantitative analysis or statistics, but who have a practical need to extract the most from their data. The book begins with an introduction to the process of data analysis and the basic structure of cross-tabulations. At the core of the methods described in the text is the loglinear model. This and the logistic model, are explained and their application to causal modelling, to event history analysis, and to social mobility research are described in detail. Each chapter concludes with sample programs to show how analysis on typical datasets can be carried out using either the popular computer packages, SPSS, or the statistical programme, GLIM. The book is packed with examples which apply the methods to social science research.Sociologists, geographers, psychologists, economists, market researchers and those involved in survey research in the fields of planning, evaluation and policy will find the book to be a clear and thorough exposition of methods for the analysis of tabular data.

Agent-based modelling in economics  Lynne Hamill and Nigel Gilbert, Centre for Research in Social Simulation (CRESS), University of Surrey, UK  New methods of economic modelling have been sought as a result of the global economic downturn in 2008.This unique book highlights the benefits of an agent-based modelling (ABM) approach. It demonstrates how ABM can easily handle complexity: heterogeneous people, households and firms interacting dynamically. Unlike traditional methods, ABM does not require people or firms to optimise or economic systems to reach equilibrium. ABM offers a way to link micro foundations directly to the macro situation.   Key features: Introduces the concept of agent-based modelling and shows how it differs from existing approaches.Provides a theoretical and methodological rationale for using ABM in economics, along with practical advice on how to design and create the models.Each chapter starts with a short summary of the relevant economic theory and then shows how to apply ABM.Explores both topics covered in basic economics textbooks and current important policy themes; unemployment, exchange rates, banking and environmental issues.Describes the models in pseudocode, enabling the reader to develop programs in their chosen language.Supported by a website featuring the NetLogo models described in the book.  Agent-based Modelling in Economics provides students and researchers with the skills to design, implement, and analyze agent-based models. Third year undergraduate, master and doctoral students, faculty and professional economists will find this book an invaluable resource.

`This book is highly recommended for libraries and departments to adopt. If I had to teach a statistics class for sociology students this would be a book I would surely choose. The book achieves two very important goals: it teaches students a software package and trains them in the statistical analysis of sociological data' - Journal of Applied Statistics

This fully revised, expanded and updated Second Edition of the best-selling textbook by Jane Fielding and Nigel Gilbert provides a comprehensive yet accessible guide to quantitative data analysis. Designed to help take the fear out of the use of numbers in social research, this textbook introduces students to statistics as a powerful means of revealing patterns in human behaviour.

The textbook covers everything typically included in an introductory course on social statistics for students in the social sciences and the authors have taken the opportunity of this Second Edition to bring the data sources as current as possible. The book is full of up-to-date examples and useful and clear illustrations using the latest SPSS software.

While maintaining the student-friendly elements of the first, such as chapter summaries, exercises at the end of each chapter, and a glossary of key terms, new features to this edition include:

-Updated examples and references

SPSS coverage and screen-shots now incorporate the current version 14.0 and are used to demonstrate the latest social statistics datasets;

-Additions to content include a brand new section on developing a coding frame and an additional discussion of weighting counts as a means of analyzing published statistics;

-Enhanced design aids navigation which is further simplified by the addition of core objectives for each chapter and bullet-pointed chapter summaries;

-The updated Website at http:/www.soc.surrey.ac.uk/uss/index.html reflects changes made to the text and provides updated datasets;

A valuable and practical guide for students dealing with the large amounts of data that are typically collected in social surveys, the Second Edition of Understanding Social Statistics is an essential textbook for courses on statistics and quantitative research across the social sciences.

Paul Stoneman and Nigel Gilbert breathe new energy into this classic bestselling textbook providing clear, relevant advice and extensive coverage of all the research methods you need to understand today’s society.

Packed full of examples from across the social sciences, Researching Social Life sets out all of the challenges and opportunities of interpreting and conducting research with qualitative, quantitative and mixed methods.

The book follows the chronology of a typical research project, from initial conception through to the collection, management and analysis of data; it also includes material on how best to write up and disseminate your research. This pragmatic approach mirrors the reality of conducting research and allows the handpicked, internationally renowned contributors to embed real case studies from their own research in each chapter.

The student-oriented pedagogy is carefully woven throughout the book and further supported by a cutting-edge website. Key tools include:

In-depth worked examples Case studies Discussion questions Checklists Annotated further reading Practical top tips for doing research.

With unparalleled breadth and depth this trusted and respected textbook is an essential guide for anyone engaging with social research.

Paul Stoneman and Nigel Gilbert breathe new energy into this classic bestselling textbook providing clear, relevant advice and extensive coverage of all the research methods you need to understand today’s society.

Packed full of examples from across the social sciences, Researching Social Life sets out all of the challenges and opportunities of interpreting and conducting research with qualitative, quantitative and mixed methods.

The book follows the chronology of a typical research project, from initial conception through to the collection, management and analysis of data; it also includes material on how best to write up and disseminate your research. This pragmatic approach mirrors the reality of conducting research and allows the handpicked, internationally renowned contributors to embed real case studies from their own research in each chapter.

The student-oriented pedagogy is carefully woven throughout the book and further supported by a cutting-edge website. Key tools include:

In-depth worked examples Case studies Discussion questions Checklists Annotated further reading Practical top tips for doing research.

With unparalleled breadth and depth this trusted and respected textbook is an essential guide for anyone engaging with social research.

This book brings together computer models and simulation approaches that allow the investigation of a wide range of innovation related issues, and hence will be of interest for academics and researchers from a variety of innovation related disciplines.'- Mercedes Bleda, Journal of Artificial Societies and Social SimulationChristopher Watts and Nigel Gilbert explore the generation, diffusion and impact of innovations, which can now be studied using computer simulations.Agent-based simulation models can be used to explain the innovation that emerges from interactions among complex, adaptive, diverse networks of firms, people, technologies, practices and resources. This book provides a critical review of recent advances in agent-based modeling and other forms of the simulation of innovation. Elements explored include: diffusion of innovations, social networks, organizational learning, science models, adopting and adapting, and technological evolution and innovation networks. Many of the models featured in the book can be downloaded from the book's accompanying website.Bringing together simulation models from several innovation-related fields, this book will prove a fascinating read for academics and researchers in a wide range of disciplines, including: innovation studies, evolutionary economics, complexity science, organization studies, social networks, and science and technology studies. Scholars and researchers in the areas of computer science, operational research and management science will also be interested in the uses of simulation models to improve the understanding of organization.

This open access volume showcases a series of models - particularly agent-based simulations - that explore pressing issues on national policy agendas, engaging with frontier questions around artificial intelligence (AI), welfare-related social assessment, and value diversity. These themes have profound implications for policy, cultural and societal life. The volume underscores the role of policy modelling in addressing how AI can be made context-specific, adaptive, and responsive within the public sector. Drawing on case studies from nine countries with differing value frameworks, the models examine welfare service provision choices and assess the demands, limitations, and effects of using AI to augment or replace traditional practices. The analyses reflect the pluralism of societal norms and values, while also considering the political, economic, and social pressures that shape them. The volume advocates for a participatory methodology and socio-technical infrastructure that can enable the development of more responsible, value-sensitive, and context-aware AI, and policies to implement it. By situating AI research, innovation and policy in close collaboration with society, it offers a fresh perspective for industry and innovation leaders. Ultimately, it presents a model for how participatory design and responsible technology production can better meet societal needs.

This book presents a multi-disciplinary investigation into extortion rackets with a particular focus on the structures of criminal organisations and their collapse, societal processes in which extortion rackets strive and fail and the impacts of bottom-up and top-down ways of fighting extortion racketeering. Through integrating a range of disciplines and methods the book provides an extensive case study of empirically based computational social science. It is based on a wealth of qualitative data regarding multiple extortion rackets, such as the Sicilian Mafia, an international money laundering organisation and a predatory extortion case in Germany. Computational methods are used for data analysis, to help in operationalising data for use in agent-based models and to explore structures and dynamics of extortion racketeering through simulations. In addition to textual data sources, stakeholders and experts are extensively involved, providing narratives for analysis and qualitative validation of models. The book presents a systematic application of computational social science methods to the substantive area of extortion racketeering. The reader will gain a deep understanding of extortion rackets, in particular their entrenchment in society and processes supporting and undermining extortion rackets. Also covered are computational social science methods, in particular computationally assisted text analysis and agent-based modelling, and the integration of empirical, theoretical and computational social science.

This book presents a multi-disciplinary investigation into extortion rackets with a particular focus on the structures of criminal organisations and their collapse, societal processes in which extortion rackets strive and fail and the impacts of bottom-up and top-down ways of fighting extortion racketeering.

This book gives an overview of the state of the art in five different approaches to social science simulation on the individual level. The volume contains microanalytical simulation models designed for policy implementation and evaluation, multilevel simulation methods designed for detecting emergent phenomena, dynamical game theory applications, the use of cellular automata to explain the emergence of structure in social systems, and multi-agent models using the experience from distributed artificial intelligence applied to special phenomena. The book collects the results of an international conference which brought together social scientists and computer scientists both engaged in a wide range of simulation approaches for the first time.

What is it about the structure and organisation of science and technology that has led to the spectacularly successful growth of knowledge during this century? This book answers this important and much debated question in an innovative way, by using computer simulations. The computer simulation of societies and social processes is a methodology which is rapidly becoming recognised for its potential in the social sciences. This book will be among the first to apply the tools of simulation systematically to a specific domain: science and technology studies. The first introductory section is followed by three application areas: simulations of scientific discovery and theory formation; evolutionary models of science and technology; and models which explore the conditions and dependencies of scientific work.

This book constitutes the thoroughly refereed post-workshop proceedings of the First International Workshop on Multi-Agent Systems and Agent-Based Simulation, MABS'98, held in Paris, France in July 1998 in conjunction with Agent World 1998. The 15 revised full papers presented together with an introduction by the volume editors were selected from a total of more than 50 submissions. Among the topics covered are multi-agent systems, social simulation, agent-based modelling, cognitive emergence, honey-bee colonies, artificial societies, economic aspects, cultural evolution, roles in agent systems, applications in various areas, etc.

This book gives an overview of the state of the art in five different approaches to social science simulation on the individual level. The volume contains microanalytical simulation models designed for policy implementation and evaluation, multilevel simulation methods designed for detecting emergent phenomena, dynamical game theory applications, the use of cellular automata to explain the emergence of structure in social systems, and multi-agent models using the experience from distributed artificial intelligence applied to special phenomena. The book collects the results of an international conference which brought together social scientists and computer scientists both engaged in a wide range of simulation approaches for the first time.

One common characteristics of a complex system is its ability to withstand major disturbances and the capacity to rebuild itself. Understanding how such systems demonstrate resilience by absorbing or recovering from major external perturbations requires both quantitative foundations and a multidisciplinary view on the topic.This book demonstrates how new methods can be used to identify the actions favouring the recovery from perturbations. Examples discussed include bacterial biofilms resisting detachment, grassland savannahs recovering from fire, the dynamics of language competition and Internet social networking sites overcoming vandalism.The reader is taken through an introduction to the idea of resilience and viability and shown the mathematical basis of the techniques used to analyse systems. The idea of individual or agent-based modelling of complex systems is introduced and related to analytically tractable approximations of such models. A set of case studies illustrates the use of the techniques in real applications, and the final section describes how one can use new and elaborate software tools for carrying out the necessary calculations.The book is intended for a general scientific audience of readers from the natural and social sciences, yet requires some mathematics to gain a full understanding of the more theoretical chapters.It is an essential point of reference for those interested in the practical application of the concepts of resilience and viability

One common characteristics of a complex system is its ability to withstand major disturbances and the capacity to rebuild itself. Understanding how such systems demonstrate resilience by absorbing or recovering from major external perturbations requires both quantitative foundations and a multidisciplinary view on the topic.This book demonstrates how new methods can be used to identify the actions favouring the recovery from perturbations. Examples discussed include bacterial biofilms resisting detachment, grassland savannahs recovering from fire, the dynamics of language competition and Internet social networking sites overcoming vandalism.The reader is taken through an introduction to the idea of resilience and viability and shown the mathematical basis of the techniques used to analyse systems. The idea of individual or agent-based modelling of complex systems is introduced and related to analytically tractable approximations of such models. A set of case studies illustrates the use of the techniques in real applications, and the final section describes how one can use new and elaborate software tools for carrying out the necessary calculations.The book is intended for a general scientific audience of readers from the natural and social sciences, yet requires some mathematics to gain a full understanding of the more theoretical chapters.It is an essential point of reference for those interested in the practical application of the concepts of resilience and viability

What is it about the structure and organisation of science and technology that has led to the spectacularly successful growth of knowledge during this century? This book explores this important and much debated question in an innovative way, by using computer simulations. The computer simulation of societies and social processes is a methodology which is rapidly becoming recognised for its potential in the social sciences. This book applies the tools of simulation systematically to a specific domain: science and technology studies. The book shows how computer simulation can be applied both to questions in the history and philosophy of science and to issues of concern to sociologists of science and technology. Chapters in the book demonstrate the use of simulation for clarifying the notion of creativity and for understanding the logical processes employed by eminent scientists to make their discoveries. The book begins with three introductory chapters. The first introduces simulation for the social sciences, surveying current work and explaining the advantages and pitfalls of this new methodology. The second and third chapters review recent work on theoretical aspects of social simulation, introducing fundamental concepts such as self­ organisation and complexity and relating these to the simulation of scientific discovery.

This text introduces SKIN (Simulation Knowledge Dynamics in Innovation Networks), an agent-based simulation model that primarily focuses on joint knowledge creation and exchange of knowledge in innovation co-operations and networks.

The competitiveness of firms, regions and countries greatly depends on the generation, dissemination and application of new knowledge. Modern innovation research is challenged by the need to incorporate knowledge generation and dissemination processes into the analysis so as to disentangle the complexity of these dynamic processes. With innovation, however, strong uncertainty, nonlinearities and actor heterogeneity become central factors that are at odds with traditional modeling techniques anchored in equilibrium and homogeneity. This text introduces SKIN (Simulation Knowledge Dynamics in Innovation Networks), an agent-based simulation model that primarily focuses on joint knowledge creation and exchange of knowledge in innovation co‐operations and networks. In this context, knowledge is explicitly modeled and not approximated by, for instance, the level of accumulated R&D investment. The SKIN approach supports applications in different domains ranging from sector-based research activities in knowledge-intensive industries to the activities of international research consortia engaged in basic and applied research. Following a general description of the SKIN model, several applications and modifications are presented. Each chapter introduces in detail the structure of the model, the relevant methodological considerations and the analysis of simulation results, while options for empirically validating the models’ structure and outcomes are also discussed. The book considers the scope of further applications and outlines prospects for the development of joint modeling strategies.

This book provides an overview of soical science simulation as a tool for modelling and theory building. It is shown how simulation may be applied to the analysis of social and economic problems using techniques such as multi-agent simulation, cellular automata and multi-level modelling. Particular attention is paid to the sensitivity analysis of model parameters. The book also describes the architecture and user interfaces of several simulation tools. The book is based on an international conference that brought together social scientists and computer scientists engaged in a wide range of simulation approaches. It represents a report on the state of the art in social science simulation.

The book focusses on questions of individual and collective action, the emergence and dynamics of social norms and the feedback between individual behaviour and social phenomena. It discusses traditional modelling approaches to social norms and shows the usefulness of agent-based modelling for the study of these micro-macro interactions. Existing agent-based models of social norms are discussed and it is shown that so far too much priority has been given to parsimonious models and questions of the emergence of norms, with many aspects of social norms, such as norm-change, not being modelled.  Juvenile delinquency, group radicalisation and moral decision making are used as case studies for agent-based models of collective action extending existing models by providing an embedding into social networks, social influence via argumentation and a causal action theory of moral decision making. The major contribution of the book is to highlight the multifaceted nature of the dynamics of social norms, consisting not only of emergence, and the importance of embedding of agent-based models into existing theory.