Theoretische und statistische Modellierung von Cross-Pressures in Kontextanalysen

Cross-pressures can be defined as individually perceived social pressure that results from heterogeneity in the social context, mainly due to conflicting social expectations of relevant social actors. In this paper we discuss the theoretical position of “cross-pressures” in the structural-individualist paradigm and present methods for modeling cross-pressures in multilevel regression models. We argue that cross pressures form a specific class of context effects, that is macro-micro links, and sketch a reconstruction as part of the problem of defining the social situation in the Model of Frame Selection. The theoretical model implies that empirical applications of the concept would ideally use multiplicative terms for the specification of cross-level interactions in multilevel models. Modeling random slopes and context fixed-effects the interaction can be identified empirically. As an example we analyze the relation between postmaterialism and environmental concern, moderated by national wealth using WVS data. Our results indicate that postmaterialism and environmental concern form an integrated value cluster in wealthy societies, but are separate constructs in poorer societies.     

SOCIAL PROGRESS AND SOCIAL PROBLEMS: Toward a Sociology of Gloom

Although significant social progress characterized the twentieth century, sociologists usually avoid acknowledging progress for fear of encouraging complacency about social problems. In four paradoxical ways, progress raises concern about social problems. The paradox of perfectionism is that optimistic beliefs in social perfectability highlight failures to achieve perfection and thereby foster pessimism. The paradox of proportion is that reducing large problems makes smaller problems seem relatively larger. The paradox of proliferation is that social progress encourages recognition of a larger number of problems. Finally, the paradox of paranoia is that progress fosters fears of social collapse. Sociologists need to consider the consequences of downplaying progress.     

Modellvergleich und Ergebnisinterpretation in Logit- und Probit-Regressionen

In the social sciences logit and probit models are often used multivariate data analysis procedures for binary dependent variables. Both procedures can be thought of as resting on a linear model for an unobserved variable y* from which a nonlinear model for the probability of y?=?1 is derived. We first show that compared to linear models this nonlinearity leads to problems of interpreting results from such analysis. In particular odds ratios (exponentiated logit coefficients) often used in logistic regression are problematic in this respect. Instead we recommend using graphical procedures and reporting (corrected) average marginal effects (AME). Based on a series of Monte-Carlo simulations we next demonstrate that the regression coefficients from logit and probit models should not be compared between nested models. Because model building in the social sciences often employs a stepwise procedure a method allowing valid comparisons of effect sizes between models would be advantageous. Results from our simulation study show that average marginal effects and regression coefficients corrected by a method proposed by Karlson et al. (Sociological Methodology 42, 2012) lead to satisfactory results in many different scenarios. In contrast, y*-standardized coefficients are of limited utility and coefficients from a linear probability model should only be used with normally distributed variables.     

Popular Hazards and Policy Rhetoric

Popular hazards are common activities that involve some risks of harm, such as driving a car, possessing or shooting a gun, drinking alcohol, or smoking marijuana. In each of these cases, many millions of Americans engage in the activity, but only a small fraction of them harm themselves or other people. Because the activity is so common, the number harmed may be substantial, although more serious harms tend to be much more infrequent than less serious harms. Social policy debates almost always focus on some particular popular hazard, yet we can see rhetorical similarities—parallel arguments—in how advocates frame what are understood to be very different social issues. Thus, discourse about legalizing recreational marijuana use tends to invoke claims that are quite similar to those opposing further gun control. The category of popular hazards allows us to recognize parallels in policy debates about seemingly unrelated social issues. Focusing on the underlying policy issue—balancing popularity and hazardousness—encourages considering alternative ways to construct social policies.     

Native subjects on display: reviving the colonial exposition in Marcos' Philippines

At the 1904 St. Louis World's Fair, 1100 Filipino ‘natives’ were used as human displays to argue for the colonial enterprise in the Philippines. Seventy years later, the Marcos regime staged Kasaysayan ng Lahi (History of the Race), a mass ceremony that reworked the visual, performative and commercial dynamics of the 1904 colonial exposition to promote heritage tourism in the Philippines. While the use of human displays in colonial expositions has been well documented and analyzed as a constitutive element of a Eurocentric ‘exhibitionary complex’, its uptake in developing nations seeking entry into an emergent cultural economy has yet to be explored. This article places critical analyses of colonial expositions, human displays and heritage tourism in productive dialogue, and examines the continuities and discontinuities between the Philippine exhibit at the 1904 St. Louis World's Fair and the 1974 staging of Kasaysayan ng Lahi by the Marcos regime. Against established views of ‘staged authenticities’ as either exploitative or socially empowering, this case study advances a more complex framework for critical histories of the exhibitionary complex, and foregrounds the internal contradictions that inhere within the staging of indigenous heritage for purposes of cultural revitalization and economic development.     

Statistical issues in the prospective monitoring of health outcomes across multiple units

Summary.  Following several recent inquiries in the UK into medical malpractice and failures to deliver appropriate standards of health care, there is pressure to introduce formal monitoring of performance outcomes routinely throughout the National Health Service. Statistical process control (SPC) charts have been widely used to monitor medical outcomes in a variety of contexts and have been specifically advocated for use in clinical governance. However, previous applications of SPC charts in medical monitoring have focused on surveillance of a single process over time. We consider some of the methodological and practical aspects that surround the routine surveillance of health outcomes and, in particular, we focus on two important methodological issues that arise when attempting to extend SPC charts to monitor outcomes at more than one unit simultaneously (where a unit could be, for example, a surgeon, general practitioner or hospital): the need to acknowledge the inevitable between-unit variation in 'acceptable' performance outcomes due to the net effect of many small unmeasured sources of variation (e.g. unmeasured case mix and data errors) and the problem of multiple testing over units as well as time. We address the former by using quasi-likelihood estimates of overdispersion, and the latter by using recently developed methods based on estimation of false discovery rates. We present an application of our approach to annual monitoring 'all-cause' mortality data between 1995 and 2000 from 169 National Health Service hospital trusts in England and Wales.