Henri Lefebvre Merrifield, Andy
2006., 2006, 20131018, 2013, 2013-10-18, 20060101
eBook
Philosopher, sociologist and urban theorist, Henri Lefebvre is one of the great social theorists of the twentieth century. This accessible and innovative introduction to the work of Lefebvre combines ...biography and theory in a critical assessment of the dynamics of Lefebvre's character, thought, and times. Exploring key Lefebvrian concepts, Andy Merrifield demonstrates the evolution of Lefebvre's philosophy, while stressing the way his long and adventurous life of ideas and political engagement live on as an enduring and inspiring interrelated whole.
Father and Daughter provides a unique 'insider perspective' on two key figures in twentieth-century British social science, combining biography of Richard Titmuss and autobiography by his daughter ...Ann Oakley.
The book proposes a new interpretation of Alexis de Tocqueville that views him first and foremost as a social scientist rather than as a political theorist. Drawing on his earlier work on the ...explanation of social behavior, Elster argues that Tocqueville's main claim to our attention today rests on the large number of exportable causal mechanisms to be found in his work, many of which are still worthy of further exploration. Elster proposes a novel reading of Democracy in America in which the key explanatory variable is the rapid economic and political turnover rather than equality of wealth at any given point in time. He also offers a reading of The Ancien Régime and the Revolution as grounded in the psychological relations among the peasantry, the bourgeoisie, and the nobility. Consistently going beyond exegetical commentary, he argues that Tocqueville is eminently worth reading today for his substantive and methodological insights.
Through an historical analysis of the theme of Oriental despotism, Michael Curtis reveals the complex positive and negative interaction between Europe and the Orient. The book also criticizes the ...misconception that the Orient was the constant victim of Western imperialism and the view that Westerners cannot comment objectively on Eastern and Muslim societies. The book views the European concept of Oriental despotism as based not on arbitrary prejudicial observation, but rather on perceptions of real processes and behavior in Eastern systems of government. Curtis considers how the concept developed and was expressed in the context of Western political thought and intellectual history, and of the changing realities in the Middle East and India. The book includes discussion of the observations of Western travelers in Muslim countries and analysis of the reflections of seven major thinkers: Montesquieu, Edmund Burke, Tocqueville, James and John Stuart Mill, Karl Marx, and Max Weber.
This open access textbook offers a practical guide into research ethics for undergraduate students in the social sciences. A step-by-step approach of the most viable issues, in-depth discussions of ...case histories and a variety of didactical tools will aid the student to grasp the issues at hand and help him or her develop strategies to deal with them. This book addresses problems and questions that any bachelor student in the social sciences should be aware of, including plagiarism, data fabrication and other types of fraud, data augmentation, various forms of research bias, but also peer pressure, issues with confidentiality and questions regarding conflicts of interest. Cheating, ‘free riding’, and broader issues that relate to the place of the social sciences in society are also included. The book concludes with a step-by-step approach designed to coach a student through a research application process.
In principle, experiments offer a straightforward method for social scientists to accurately estimate causal effects. However, scholars often unwittingly distort treatment effect estimates by ...conditioning on variables that could be affected by their experimental manipulation. Typical examples include controlling for posttreatment variables in statistical models, eliminating observations based on posttreatment criteria, or subsetting the data based on posttreatment variables. Though these modeling choices are intended to address common problems encountered when conducting experiments, they can bias estimates of causal effects. Moreover, problems associated with conditioning on posttreatment variables remain largely unrecognized in the field, which we show frequently publishes experimental studies using these practices in our discipline's most prestigious journals. We demonstrate the severity of experimental posttreatment bias analytically and document the magnitude of the potential distortions it induces using visualizations and reanalyses of real-world data. We conclude by providing applied researchers with recommendations for best practice.
The example of Old Regime France provides a source for many of the ideas about capitalism, modernization, and peasant protest that concern social scientists today. Hilton Root challenges traditional ...assumptions and proposes a new interpretation of the relationship between state and society.
Behavioral scientists use mediation analysis to understand the mechanism(s) by which an effect operates and moderation analysis to understand the contingencies or boundary conditions of effects. Yet ...how effects operate (i.e., the mechanism at work) and their boundary conditions (when they occur) are not necessarily independent, though they are often treated as such. Conditional process analysis is an analytical strategy that integrates mediation and moderation analysis with the goal of examining and testing hypotheses about how mechanisms vary as a function of context or individual differences. In this article, we provide a conceptual primer on conditional process analysis for those not familiar with the integration of moderation and mediation analysis, while also describing some recent advances and innovations for the more experienced conditional process analyst. After overviewing fundamental modeling principles using ordinary least squares regression, we discuss the extension of these fundamentals to models with more than one mediator and more than one moderator. We describe a differential dominance conditional process model and overview the concepts of partial, conditional, and moderated moderated mediation. We also discuss multilevel conditional process analysis and comment on implementation of conditional process analysis in statistical computing software.
This article addresses potential effects on reflexivity of researcher’s social position (e.g. gender, age, race, immigration status, sexual orientation), personal experiences, and political and ...professional beliefs. Because reflexivity is a major strategy for quality control in qualitative research, understanding how it may be impacted by the characteristics and experiences of the researcher is of paramount importance. Benefits and challenges to reflexivity under three types of researcher’s position are discussed and illustrated by means of case examples: (1) reflexivity when researcher shares the experience of study participants, (2) reflexivity when researcher moves from the position of an outsider to the position of an insider in the course of the study, and (3) reflexivity when researcher has no personal familiarity or experience with what is being studied. Strategies are offered for harvesting the benefits of researcher’s familiarity with the subject and for curbing its potentially negative effects. Directions for future research are suggested.
Social scientists are now in an era of data abundance, and machine learning tools are increasingly used to extract meaning from data sets both massive and small. We explain how the inclusion of ...machine learning in the social sciences requires us to rethink not only applications of machine learning methods but also best practices in the social sciences. In contrast to the traditional tasks for machine learning in computer science and statistics, when machine learning is applied to social scientific data, it is used to discover new concepts, measure the prevalence of those concepts, assess causal effects, and make predictions. The abundance of data and resources facilitates the move away from a deductive social science to a more sequential, interactive, and ultimately inductive approach to inference. We explain how an agnostic approach to machine learning methods focused on the social science tasks facilitates progress across a wide range of questions.
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