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83 results in Research methods in sociology and criminology

Page 1 of 5

Comprehensive Deterrence Theory
  • The Science and Policy of Punishment
  • Daniel P. Mears, Mark C. Stafford
  • Published online:
    06 March 2025
    Print publication:
    13 March 2025
  • First articulated more than 250 years ago, deterrence remains a central theory in criminology and continues to be the bedrock of the vast bulk of criminal justice policy. But few updates to the original theory of deterrence have been made, and crime-based punishment has only grown tougher, resulting in a historically unprecedented growth in imprisonment and an even greater reliance on deterrence to justify all kinds of punishment. These changes have occurred despite consistent or strong evidence to show that such punishments actually deter crime. In this book, renowned criminologists Daniel P. Mears and Mark C. Stafford provide an in-depth understanding of the classical account of deterrence theory, its limitations, and a reconceptualized version that establishes a more complete and powerful picture of how legal punishments can deter crime. Thorough and corrective, Comprehensive Deterrence Theory gives readers a new way of thinking about and understanding legal punishment.

Multiverse Analysis
  • Computational Methods for Robust Results
  • Cristobal Young, Erin Cumberworth
  • Published online:
    28 February 2025
    Print publication:
    06 March 2025
  • There are many ways of conducting an analysis, but most studies show only a few carefully curated estimates. Applied research involves a complex array of analytical decisions, often leading to a 'garden of forking paths' where each choice can lead to different results. By systematically exploring how alternative analytical choices affect the findings, Multiverse Analysis reveals the full range of estimates that the data can support and uncovers insights that single-path analyses often miss. It shows which modelling decisions are most critical to the results and reveals how data and assumptions work together to produce empirical estimates. Focusing on intuitive understanding rather than complex mathematics, and drawing on real-world datasets, this book provides a step-by-step guide to comprehensive multiverse analysis. Go beyond traditional, single-path methods and discover how multiverse analysis can lead to more transparent, illuminating, and persuasive empirical contributions to science.

Experimental Sociology
  • Outline of a Scientific Field
  • Davide Barrera, Klarita Gërxhani, Bernhard Kittel, Luis Miller, Tobias Wolbring
  • Published online:
    23 November 2024
    Print publication:
    21 November 2024
  • Experiments have gained prominence in sociology in recent years. Increased interest in testing causal theories through experimental designs has ignited a debate about which experimental designs can facilitate scientific progress in sociology. This book discusses the implications of research interests for the design of experiments, identifies points of commonality and disagreement among the different perspectives within sociology, and elaborates on the rationales of each. It helps experimental sociologists find appropriate designs for answering specific research questions while alerting them to the challenges. Offering more than just a guide, this book explores both the historical roots of experimental sociology and the cutting-edge techniques of rigorous sociology. It concludes with a tantalizing peek into the future and provides a roadmap to the exciting prospects and uncharted territories of experimental sociology.

Designing Empirical Social Networks Research
  • Jennifer M. Larson
  • Published online:
    07 November 2024
    Print publication:
    21 November 2024
  • A user-friendly introductory guide to the empirical study of social networks. Jennifer M. Larson presents the fundamentals of social networks in an intuition-forward way which guides theory-driven research design. Substantial attention is devoted to a framework for developing a network theory that will steer data collection to be maximally informative and minimally frustrating. Other features include: Coverage of a range of practical topics including selecting operationalizations, cutting survey costs, and cleaning data; A tutorial for getting started in analyzing networks in R; Technical sections full of examples, points to hone intuition, and practice problems with solutions. Designing Empirical Social Networks Research will be a valuable tool for advanced undergraduates, Ph.D. students in the social sciences, especially political science, and researchers across the social sciences who are new to the study of networks.

Morphogenesis Answers Its Critics
  • Margaret S. Archer
  • Published online:
    28 March 2024
    Print publication:
    04 April 2024
  • In this final book by renowned sociologist Margaret S. Archer, her groundbreaking morphogenetic approach is defended, refined and extended through a series of engagements with her critics. Archer, a pioneer of critical realism, addresses key debates surrounding her work on structure, agency, and social change. Each chapter responds to critiques from a different scholar, using these exchanges as springboards to further develop her powerful explanatory framework. Through these lively dialogues, Archer elaborates her tools for analysing social and cultural dynamics. This book offers readers a unique window into Archer's thought as she clarifies, sharpens and expands her theoretical contributions in response to constructive criticism. It will be an essential read for scholars and students across the social sciences, and for anyone seeking to understand the forces that shape our social world and how we can reshape it.

Regression Inside Out
  • Eric W. Schoon, David Melamed, Ronald L. Breiger
  • Published online:
    21 March 2024
    Print publication:
    22 February 2024
  • Linear regression analysis, with its many generalizations, is the predominant quantitative method used throughout the social sciences and beyond. The goal of the method is to study relations among variables. In this book, Schoon, Melamed and Breiger turn regression modeling inside out to put the emphasis on the cases (people, organizations, and nations) that comprise the variables. By re-analyzing influential published research, they reveal new insights and present a principled way to unlock a set of more nuanced interpretations than has previously been attainable. The emphasis is on intuition and examples that can be reproduced using the code and datasets provided. Relating their contributions to methodologies that operate under quite different philosophical assumptions, the authors advance multi-method social science and help to bridge the divide between quantitative and qualitative research. The result is a modern, accessible, and innovative take on extracting knowledge from data.

Set-Theoretic Multi-Method Research
  • A Guide to Combining QCA and Case Studies
  • Carsten Q. Schneider
  • Published online:
    22 February 2024
    Print publication:
    29 February 2024
  • A state-of-the-art comprehensive exposition of combining Qualitative Comparative Analysis (QCA) and case studies, this book facilitates the efficient use and independent learning of this form of SMMR (set-theoretic multi-method research) with the best available software. It will reduce the time and effort required when performing both QCA and case studies within the same research project. This is achieved by spelling out the conceptual principles and practices in SMMR, and by introducing a tailor-made R software package. With an applied and practical focus, this is an intuitive resource for implementing the most complete protocol of SMMR. Features include Learning Goals, Core Points, and Empirical Examples, as well as boxed examples of R codes and the R output it produces. There is also a glossary for key SMMR terms. Additional online material is available, comprising machine-readable datasets and R scripts for replication and independent learning.

Interaction Models
  • Specification and Interpretation
  • William Roberts Clark, Matt Golder
  • Published online:
    02 November 2023
    Print publication:
    16 November 2023
  • The radical interdependence between humans who live together makes virtually all human behavior conditional. The behavior of individuals is conditional upon the expectations of those around them, and those expectations are conditional upon the rules (institutions) and norms (culture) constructed to monitor, reward, and punish different behaviors. As a result, nearly all hypotheses about humans are conditional – conditional upon the resources they possess, the institutions they inhabit, or the cultural practices that tell them how to behave. Interaction Models provides a stand-alone, accessible overview of how interaction models, which are frequently used across the social and natural sciences, capture the intuition behind conditional claims and context dependence. It also addresses the simple specification and interpretation errors that are, unfortunately, commonplace. By providing a comprehensive and unified introduction to the use and critical evaluation of interaction models, this book shows how they can be used to test theoretically-derived claims of conditionality.

Integrated Inferences
  • Causal Models for Qualitative and Mixed-Method Research
  • Macartan Humphreys, Alan M. Jacobs
  • Published online:
    13 October 2023
    Print publication:
    30 November 2023
  • There is a growing consensus in the social sciences on the virtues of research strategies that combine quantitative with qualitative tools of inference. Integrated Inferences develops a framework for using causal models and Bayesian updating for qualitative and mixed-methods research. By making, updating, and querying causal models, researchers are able to integrate information from different data sources while connecting theory and empirics in a far more systematic and transparent manner than standard qualitative and quantitative approaches allow. This book provides an introduction to fundamental principles of causal inference and Bayesian updating and shows how these tools can be used to implement and justify inferences using within-case (process tracing) evidence, correlational patterns across many cases, or a mix of the two. The authors also demonstrate how causal models can guide research design, informing choices about which cases, observations, and mixes of methods will be most useful for addressing any given question.

Network Analysis
  • Integrating Social Network Theory, Method, and Application with R
  • Craig M. Rawlings, Jeffrey A. Smith, James Moody, Daniel A. McFarland
  • Published online:
    21 September 2023
    Print publication:
    05 October 2023
  • The size and availability of network information has exploded over the last decade. Social scientists now share the stage of network analysis with computer scientists, physicists, and statisticians. While a number of introductions to network analysis are now available, most focus on theory, methods, or application alone. This book integrates all three. Network Analysis is an introduction to both the why and how of Social Network Analysis (SNA). It presents a broad theoretical overview rooted in social scientific approaches and guides users in how network analysis can answer core theoretical questions. It provides a comprehensive overview of descriptive and analytical approaches, including practical tutorials in R with sample data sets. Using an integrated approach, this book aims to quickly bring novice network researchers up to speed while avoiding common programming and analysis mistakes so that they might gain insight into the fundamental theories, key concepts, and methodological application of SNA.

Applied Regression Models in the Social Sciences
  • Dudley L. Poston, Jr, Eugenia Conde, Layton M. Field
  • Published online:
    17 August 2023
    Print publication:
    17 August 2023
  • This accessible and practical textbook gives students the perfect guide to the use of regression models in testing and evaluating hypotheses dealing with social relationships. A range of statistical methods suited to a wide variety of dependent variables is explained, which will allow students to read, understand, and interpret complex statistical analyses of social data. Each chapter contains example applications using relevant statistical methods in both Stata and R, giving students direct experience of applying their knowledge. A full suite of online resources - including statistical command files, datasets and results files, homework assignments, class discussion topics, PowerPoint slides, and exam questions - supports the student to work independently with the data, and the instructor to deliver the most effective possible course. This is the ideal textbook for advanced undergraduate and beginning graduate students taking courses in applied social statistics.

Data Science for Complex Systems
  • Anindya S. Chakrabarti, K. Shuvo Bakar, Anirban Chakraborti
  • Published online:
    11 May 2023
    Print publication:
    25 May 2023
  • Many real-life systems are dynamic, evolving, and intertwined. Examples of such systems displaying 'complexity', can be found in a wide variety of contexts ranging from economics to biology, to the environmental and physical sciences. The study of complex systems involves analysis and interpretation of vast quantities of data, which necessitates the application of many classical and modern tools and techniques from statistics, network science, machine learning, and agent-based modelling. Drawing from the latest research, this self-contained and pedagogical text describes some of the most important and widely used methods, emphasising both empirical and theoretical approaches. More broadly, this book provides an accessible guide to a data-driven toolkit for scientists, engineers, and social scientists who require effective analysis of large quantities of data, whether that be related to social networks, financial markets, economies or other types of complex systems.

The Grammar of Time
  • A Toolbox for Comparative Historical Analysis
  • Marcus Kreuzer
  • Published online:
    11 May 2023
    Print publication:
    25 May 2023
  • Kreuzer offers guidance to scholars looking to comparative historical analysis (CHA) for the tools to analyze macro-historical questions. Like history, CHA uses the past to formulate research questions, describe social transformations, and generate inductive insights. Like social science, CHA compares those patterns to explicate generalizable and testable theories. It operates in two different worlds—one constantly changing and full of cultural particularities and another static and full of orderly uniformities. CHA draws attention to the ontological constructions of these worlds; how scholars background historical and geographic particularities to create a social reality orderly enough for theorizing, while others foreground those particularities to re-complexify it to generate new inductive insights. CHA engages in ontological triage, dialogue between exploration and confirmation, and conversation in how to translate test results into genuine answers. This book is supplemented by online materials including introductory videos, diagnostic quizzes, advanced exercises, and annotated bibliographies.

Social Media as Social Science Data
  • Steven Lloyd Wilson
  • Published online:
    03 November 2022
    Print publication:
    17 November 2022
  • Social media has put mass communication in the hands of normal people on an unprecedented scale, and has also given social scientists the tools necessary to listen to the voices of everyday people around the world. This book gives social scientists the skills necessary to leverage that opportunity, and transform social media's vast stream of information into social science data. The book combines the big data techniques of computer science with social science methodology. Intended as a text for advanced undergraduates, graduate students, and researchers in the social sciences, this book provides a methodological pathway for scholars who want to make use of this new and evolving source of data. It provides a framework for building one's own data collection and analysis infrastructure, a toolkit of content analysis, geographic analysis, and network analysis, and meditations on the ethical implications of social media data.

The Fundamentals of Social Research
  • Paul M. Kellstedt, Guy D. Whitten, Steven A. Tuch
  • Published online:
    07 October 2022
    Print publication:
    08 September 2022
  • This textbook provides an introduction to the scientific study of sociology and other social sciences. It offers the basic tools necessary for readers to become both critical consumers and beginning producers of scientific research on society. The authors present an integrated approach to research design and empirical analyses in which researchers can develop and test causal theories. They use examples from social science research that students will find engaging and inspiring and that will help them to understand key concepts. The book makes technical materials accessible to students who might otherwise be intimidated by mathematical examples. This new text, with the addition of sociologist Steven A. Tuch to the author team, follows the successful format, approach, and pedagogical features in Paul M. Kellstedt and Guy D. Whitten's bestselling text, The Fundamentals of Political Science Research, now in its third edition. Workbooks in Stata, SPSS, and R, three of the most popular statistical analysis programs, are available as separate purchases to accompany this textbook, enabling students to connect the lessons of this book to hands-on applications of the software.

Finding your Social Science Project
  • The Research Sandbox
  • John Gerring, Jason Seawright
  • Published online:
    06 October 2022
    Print publication:
    13 October 2022
  • The most important step in social science research is the first step – finding a topic. Unfortunately, little guidance on this crucial and difficult challenge is available. Methodological studies and courses tend to focus on theory testing rather than theory generation. This book aims to redress that imbalance. The first part of the book offers an overview of the book's central concerns. How do social scientists arrive at ideas for their work? What are the different ways in which a study can contribute to knowledge in a field? The second part of the book offers suggestions about how to think creatively, including general strategies for finding a topic and heuristics for discovery. The third part of the book shows how data exploration may assist in generating theories and hypotheses. The fourth part of the book offers suggestions about how to fashion disparate ideas into a theory.

A Stata Companion for The Fundamentals of Social Research
  • Paul M. Kellstedt, Guy D. Whitten, Steven A. Tuch
  • Published online:
    29 September 2022
    Print publication:
    08 September 2022
  • A Stata Companion for The Fundamentals of Social Research offers students the opportunity to delve into the world of Stata using real data sets and statistical analysis techniques directly from Paul M. Kellstedt, Guy D. Whitten, and Steven A. Tuch's new textbook. Workbook sections parallel chapters in the main text, giving students a chance to apply the lessons and techniques learned in each chapter in a statistical software setting. Detailed chapters teach students to reproduce results presented in the textbook, allowing them to become comfortable performing statistical analyses for evaluating causal claims through repeated practice. Step-by-step instructions for using Stata are provided, along with command lines and screenshots to demonstrate proper use of the software. Instructions for producing the figures and tables in the main text are integrated throughout the workbook. End-of-chapter exercises encourage students to formulate and evaluate their own hypotheses.

An R Companion for The Fundamentals of Social Research
  • Paul M. Kellstedt, Guy D. Whitten, Steven A. Tuch
  • Published online:
    23 September 2022
    Print publication:
    08 September 2022
  • An R Companion for The Fundamentals of Social Research offers students the opportunity to delve into the world of R using real data sets and statistical analysis techniques directly from Paul M. Kellstedt, Guy D. Whitten, and Steven A. Tuch's new textbook. Workbook sections parallel chapters in the main text, giving students a chance to apply the lessons and techniques learned in each chapter in a statistical software setting. Detailed chapters teach students to reproduce results presented in the textbook, allowing them to become comfortable performing statistical analyses for evaluating causal claims through repeated practice. Step-by-step instructions for using R are provided, along with command lines and screenshots to demonstrate proper use of the software. Instructions for producing the figures and tables in the main text are integrated throughout the workbook. End-of-chapter exercises encourage students to formulate and evaluate their own hypotheses.

An SPSS Companion for The Fundamentals of Social Research
  • Paul M. Kellstedt, Guy D. Whitten, Steven A. Tuch
  • Published online:
    23 September 2022
    Print publication:
    08 September 2022
  • An SPSS Companion for The Fundamentals of Social Research offers students the opportunity to delve into the world of SPSS using real data sets and statistical analysis techniques directly from Paul M. Kellstedt, Guy D. Whitten, and Steven A. Tuch's new textbook. Workbook sections parallel chapters in the main text, giving students a chance to apply the lessons and techniques learned in each chapter in a statistical software setting. Detailed chapters teach students to reproduce results presented in the textbook, allowing them to become comfortable performing statistical analyses for evaluating causal claims through repeated practice. Step-by-step instructions for using SPSS are provided, along with command lines and screenshots to demonstrate proper use of the software. Instructions for producing the figures and tables in the main text are integrated throughout the workbook. End-of-chapter exercises encourage students to formulate and evaluate their own hypotheses.

Social Inquiry and Bayesian Inference
  • Rethinking Qualitative Research
  • Tasha Fairfield, Andrew E. Charman
  • Published online:
    28 July 2022
    Print publication:
    04 August 2022
  • Fairfield and Charman provide a modern, rigorous and intuitive methodology for case-study research to help social scientists and analysts make better inferences from qualitative evidence. The book develops concrete guidelines for conducting inference to best explanation given incomplete information; no previous exposure to Bayesian analysis or specialized mathematical skills are needed. Topics covered include constructing rival hypotheses that are neither too simple nor overly complex, assessing the inferential weight of evidence, counteracting cognitive biases, selecting cases, and iterating between theory development, data collection, and analysis. Extensive worked examples apply Bayesian guidelines, showcasing both exemplars of intuitive Bayesian reasoning and departures from Bayesian principles in published case studies drawn from process-tracing, comparative, and multimethod research. Beyond improving inference and analytic transparency, an overarching goal of this book is to revalue qualitative research and place it on more equal footing with respect to quantitative and experimental traditions by illustrating that Bayesianism provides a universally applicable inferential framework.

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