Toward Less Division of Labor? New Production Concepts in the Automotive, Chemical, Clothing, and Machine Tool Industries

In this contribution, we focus on the results ofthe Belgian Trend Study. The intention of this study wasto examine the prevalence of new production conceptswithin the widest possible range of companies in the automotive, the machine tool, thechemical, and the clothing industries. The Trend Studyaimed to answer the following questions: is theTaylorist division of labor a thing of the past? Whatare the alternatives? Are shifts in the division oflabor accompanied by another type of personnel policy,and do traditional industrial relations have to make wayfor this new approach? The methodological concept used had to guarantee that the findingsat the level of each industry could be generalized.Though the picture emerging from the empirical datacollected in the four industrial sectors is inevitablydiverse, the data make it possible merely to suggest aneo- rather than a post-Taylorist or -Fordistconcept.     

Applying the capability approach to policy-making: The impact assessment of the EU-proposal on organ donation

We show that the capability approach can greatly facilitate ex ante policy evaluations, in particular those that are geared towards multiple goals. It enables a structured discussion on policy benefits, distributional issues, freedom and ethics. We illustrate our general ideas with a real-world application: the impact assessment of an EU-proposal on organ donation.     

Experts in experiments

An ever increasing number of experiments attempts to elicit risk preferences of a population of interest with the aim of calibrating parameters used in economic models. We are concerned with two types of selection effects, which may affect the external validity of standard experiments: Sampling from a narrowly defined population of students (??experimenter-induced selection??) and self-selection due to non-response or incomplete response of participants in a random sample from a broad population. We find that both types of selection lead to a sample of experts: Participants perform significantly better than the general population, in the sense of fewer violations of revealed preference conditions. Self-selection within a broad population does not seem to matter for average preferences. In contrast, sampling from a student population leads to lower estimates of average risk aversion and loss aversion parameters. Furthermore, it dramatically reduces the amount of heterogeneity in all parameters.     

Equivalence testing for similarity in bioassays using bioequivalence criteria on the relative bioactivity

Similarity in bioassays means that the test preparation behaves as a dilution of the standard preparation with respect to their biological effect. Thus, similarity must be investigated to confirm this biological property. Historically, this was typically conducted with traditional hypothesis testing, but this has received substantial criticism. Failing to reject similarity does not imply that the 2 preparations are similar. Also, rejecting similarity when bioassay variability is small might simply demonstrate a nonrelevant deviation in similarity. To remedy these concerns, equivalence testing has been proposed as an alternative to traditional hypothesis testing, and it has found its way in the official guidelines. However, similarity has been discussed mainly in terms of the parameters in the dose‐response curves of the standard and test preparations, but the consequences of nonsimilarity on the relative bioactivity have never been investigated. This article provides a general equivalence approach to evaluate similarity that is directly related to bioequivalence on the relative bioactivity of the standard and test preparations. Bioequivalence on the relative bioactivity can only be guaranteed for positive (only nonblanks) and finite dose intervals. The approach is demonstrated on 4 case studies in which we also show how to calculate a sample size and how to investigate the power of equivalence on similarity.     

A regularized bridge sampler for sparsely sampled diffusions

Sparsely sampled diffusion processes, in this paper interpreted as data sampled sparsely in time relative to the time constant, is a challenging statistical problem. Most approximations of the transition kernel are derived under the assumption that data is frequently sampled and these approximations are often severely biased for sparsely sampled data. Monte Carlo methods can be used for this problem as the transition density can be estimated with arbitrary accuracy regardless of the sampling frequency, but this is computationally expensive or even prohibited unless effective variance reduction is applied.     

Making hermeneutics explicit: how QCA supports an insightful dialogue between theory and cases

Typically, qualitative comparative analysis (QCA) is praised for its hermeneutic dialogue between theory and empirical cases. However, in reporting research with QCA, these hermeneutic processes will usually not be illustrated. This paper aims at showing clear how QCA induces this dialogue between theory and data. As an illustrative example, I use a research situation dealing with a genuine research question of Legislative Studies: the causes of party unity. Using the classical dichotomous and the MV-QCA approach, the paper mainly shows how to deal productively with contradictory theoretical statements and how stepping from simpler to more complex models adds explanation while still making clear further routes to improve insights into the substantive research topic: both theoretically and empirically. Finally, non-observed configuration (‘logical remainders’) will be used to simplify the resulting theory, and its theoretical and empirical plausibility will be evaluated. The whole paper makes explicit how the QCA approach forces researchers to reveal the dialogue between theory and cases – just as it was intended by the inventor of this analytical tool.     

The rise in absenteeism: disentangling the impacts of cohort, age and time

In recent years, a number of welfare state economies, including Norway, have experienced substantial increases in sickness absence. Using longitudinal individual register data for virtually all Norwegian employees, we examine the remarkable rise since the early 1990s, with emphasis on disentangling the roles of cohort, age, and time. We show that individual age-adjusted absence propensities have risen even more than aggregate absence rates from 1993 to 2005, which casts doubt on the popular hypotheses that the rise was due to the inclusion into the workforce of young or marginal workers with weaker work-norms or poorer health.     

Genocide Reconsidered: A Pragmatist Approach

The recent literature on genocide shows signs of taking what might be called a “processual turn,” with genocide increasingly understood as a contingent process rather than a singular event. But while this second generation's turn may be clear to those within the literature, the theory guiding the change is insufficiently specified. The theory regarding process and contingency is implicit, and, as such, genocide theory does not realize its full generative potential. The primary goal of this article is to provide a more robust theoretical framework for making sense of the continually evolving dimensions of genocide. It builds on the literature's existing foundations, most notably Mann's (2005) notion of “contingent escalations.” In the spirit of the recent revival of American Pragmatism in sociology, it draws on the work of Dewey, Mills, Follett, and Addams (among others) as part of a theoretical reconstruction using pragmatist concepts such as rupture, perplexity, vocabularies of motive, and experimentation to consider examples from the Rwandan genocide and show how we might explore the potential for non‐teleological intentionality on the part of genocidal actors. The result is an enhanced theoretical framework that offers “fresh eyes” for considering one of the worst (and most under‐theorized) social problems.     

A Facet Theory Approach to Examining Overall and Life Facet Satisfaction Relationships

Multiple Discrepancies Theory – MDT – (Michalos, 1985)has been established as a leading theory of lifesatisfaction, on the basis of which numerous studieson satisfaction have been designed. Previous researchexamining overall and life facet satisfactionrelationships combined various approaches tounderstanding the interrelationships between thevariables by which individuals measure theirsatisfaction in life. Recently, Lance, Mallard andMichalos (1995) extended the scope of study byexamining the theoretical relationship between overalllife satisfaction (OLS) and satisfaction in variouslife facets (life facet satisfaction – LFS) among1,354 US college students. The present study extendsMDT one step further by applying a Facet Theory (FT)statistical approach to our understanding of the sameset of data. In this way a holistic model emerges,presenting not only the relationship between OLS andLFS, but also the interrelationships between and amongeach and every facet. Results of this analysis arepresented through the correlation matrix and SmallestSpace Analysis (SSA) diagrams. These results arecompared to Levy and Guttmans (1975) figures in theirstudy on the structure of well-being; although the twostudies examined different populations and askeddifferent questions, the final structural organizationof the data is strikingly similar.