Domains, ranges and strategy-proofness: the case of single-dipped preferences

We characterize the set of all individual and group strategy-proof rules on the domain of all single-dipped preferences on a line. For rules defined on this domain, and on several of its subdomains, we explore the implications of these strategy-proofness requirements on the maximum size of the rules’ range. We show that when all single-dipped preferences are admissible, the range must contain two alternatives at most. But this bound changes as we consider different subclasses of single-dipped preferences: we provide examples of subdomains admitting strategy-proof rules with larger ranges. We establish exact bounds on the maximal size of strategy-proof functions on each of these domains, and prove that the relationship between the sizes of the subdomains and those of the ranges of strategy-proof functions on them need not be monotonic. Our results exhibit a sharp contrast between the structure of strategy-proof rules defined on subdomains of single-dipped preferences and those defined on subsets of single-peaked ones.     

Testing non-oblique hypotheses

This paper considers a likelihood ratio test for testing hypotheses defined by non-oblique closed convex cones, satisfying the so called iteration projection property, in a set of k normal means. We obtain the critical values of the test using the Chi-Bar-Squared distribution. The obtuse cones are introduced as a particular class of cones which are non-oblique with every one of their faces. Examples with the simple tree order cone and the total order cone are given to illustrate the results.     

Bayesian monitoring of local residual autocorrelations taking into account the run-length

This paper proposes new two-sided monitoring algorithms for detecting the presence of first order residual autocorrelations in Dynamic Normal Models. The methodology uses a Bayesian decision approach with loss function which takes into account the run-length of the process. The power and mean run-length of the proposed algorithms are analysed by Monte Carlo methods. The results obtained improve those corresponding to the monitoring algorithm for residual autocorrelations proposed in Gargallo and Salvador [2003. Monitoring residual autocorrelations in dynamic linear models. Comm. Statist. Simulation Comput. 32(4), 1079–1104.] with respect to the run-length, and also exhibit more homogeneous behaviour.     

Population Change and Changing Educational Attainment of Ethnic Groups in the United States, 1980–2000

This study assesses the effect of population change on decade changes in the educational attainments of country of origin populations in the United States. Our data are derived from decennial censuses, NLMS, the World Bank, and INS. We find that changes in the share of country of origin populations with one or more years of post-secondary schooling are associated with selected components of population change during the 1980–1990 and 1990–2000 decades. The specific components include survivors during the decade, in-migration, and emigration of the foreign-born. Likewise, intra-generational mobility is found to be an important determinant of changes in educational attainment. The discussion addresses limitations of the data and suggests directions for future research as well as policy implications.     

W. E. B. Du Bois as Interactionist: Reflections on the Canonical Incorporation of a Marginalized Scholar

Recent scholarship explores the relevance and canonical status of W. E. B. Du Bois in sociological theory; yet less is said about his contributions to symbolic interactionism. This paper interrogates the emerging meaning of W. E. B. Du Bois for sociology, and the nature of his canonical incorporation. We explore the less “official” dimensions of Du Boisian theory, and in particular two of his contributions to symbolic interactionism: double consciousness and autoethnography. In the last part of the paper, we suggest that Du Bois's incorporation into the sociological canon can be viewed as a process of “centering,” and argue that this form of sponsoring of Du Bois's work can elevate some interpretations of Du Bois to the detriment of others.     

Looking Inside Glitch Mitigation Capability: The Effect of Intraorganizational Communication Channels

Manufacturers can reduce the occurrence of glitches in their operations by building capabilities to prevent them, yet mitigation capabilities are also needed to contain the effects of the glitches that will still inevitably occur every now and then. We examine the glitch mitigation capability of a production process from an information‐processing perspective and propose that (i) the impact of operational glitches on delivery performance is contingent on the formalization of intrafirm communication channels and (ii) this effect is stronger when formal communication channels are complemented with informal channels. We test our model in a sample of 163 make‐to‐order production processes and find support for the first hypothesis and partial support for the second hypothesis. The statistical analyses also reveal nonhypothesized empirical regularities, which we explore through an additional qualitative study based on 34 site visits and 30 interviews with production planners. The results have practical implications for the design of intraorganizational communication channels, and they also contribute to the research on organizational resilience and communications by showing that when coping with disruptions, the formal communication channels have advantages that are seldom discussed in the literature or recognized by practitioners.     

Estimating Listeria monocytogenes Growth in Ready-to-Eat Chicken Salad Using a Challenge Test for Quantitative Microbial Risk Assessment

Currently, there is a growing preference for convenience food products, such as ready-to-eat (RTE) foods, associated with long refrigerated shelf-lives, not requiring a heat treatment prior to consumption. Because Listeria monocytogenes is able to grow at refrigeration temperatures, inconsistent temperatures during production, distribution, and at consumer's household may allow for the pathogen to thrive, reaching unsafe limits. L. monocytogenes is the causative agent of listeriosis, a rare but severe human illness, with high fatality rates, transmitted almost exclusively by food consumption. With the aim of assessing the quantitative microbial risk of L. monocytogenes in RTE chicken salads, a challenge test was performed. Salads were inoculated with a three-strain mixture of cold-adapted L. monocytogenes and stored at 4, 12, and 16 °C for eight days. Results revealed that the salad was able to support L. monocytogenes’ growth, even at refrigeration temperatures. The Baranyi primary model was fitted to microbiological data to estimate the pathogen's growth kinetic parameters. Temperature effect on the maximum specific growth rate (μ_max) was modeled using a square-root-type model. Storage temperature significantly influenced μ_max of L. monocytogenes (p < 0.05). These predicted growth models for L. monocytogenes were subsequently used to develop a quantitative microbial risk assessment, estimating a median number of 0.00008726 listeriosis cases per year linked to the consumption of these RTE salads. Sensitivity analysis considering different time–temperature scenarios indicated a very low median risk per portion (<−7 log), even if the assessed RTE chicken salad was kept in abuse storage conditions.