Ethnic diversity as a multilevel construct:the combined effects of dissimilarity, group diversity, and societal status on learning performance in work groups

The authors present a model of the multilevel effects of diversity on individual learning performance in work groups. For ethnically diverse work groups, the model predicts that group diversity elicits either positive or negative effects on individual learning performance, depending on whether a focal individual’s ethnic dissimilarity from other group members is high or low. By further considering the societal status of an individual’s ethnic origin within society (Anglo versus non-Anglo for our U.K. context), the authors hypothesize that the model’s predictions hold more strongly for non-Anglo group members than for Anglo group members. We test this model with data from 412 individuals working on a 24-week business simulation in 87 four- to seven-person groups with varying degrees of ethnic diversity. Two of the three hypotheses derived from the model received full support and one hypothesis received partial support. Implications for theory development, methods, and practice in applied group diversity research are discussed.

Discriminating antigen and non-antigen using proteome dissimilarity:bacterial antigens

It has been postulated that immunogenicity results from the overall dissimilarity of pathogenic proteins versus the host proteome. We have sought to use this concept to discriminate between antigens and non-antigens of bacterial origin. Sets of 100 known antigenic and nonantigenic peptide sequences from bacteria were compared to human and mouse proteomes. Both antigenic and non-antigenic sequences lacked human or mouse homologues. Observed distributions were compared using the non-parametric Mann-Whitney test. The statistical null hypothesis was accepted, indicating that antigen and non-antigens did not differ significantly. Likewise, we were unable to determine a threshold able to separate meaningfully antigen from non-antigen. Thus, antigens cannot be predicted from pathogen genomes based solely on their dissimilarity to the human genome.

Discriminating antigen and non-antigen using proteome dissimilarity III:tumour and parasite antigens

Computational genome analysis enables systematic identification of potential immunogenic proteins within a pathogen. Immunogenicity is a system property that arises through the interaction of host and pathogen as mediated through the medium of a immunogenic protein. The overt dissimilarity of pathogenic proteins when compared to the host proteome is conjectured by some to be the determining principal of immunogenicity. Previously, we explored this idea in the context of Bacterial, Viral, and Fungal antigen. In this paper, we broaden and extend our analysis to include complex antigens of eukaryotic origin, arising from tumours and from parasite pathogens. For both types of antigen, known antigenic and non-antigenic protein sequences were compared to human and mouse proteomes. In contrast to our previous results, both visual inspection and statistical evaluation indicate a much wider range of homologues and a significant level of discrimination; but, as before, we could not determine a viable threshold capable of properly separating non-antigen from antigen. In concert with our previous work, we conclude that global proteome dissimilarity is not a useful metric for immunogenicity for presently available antigens arising from Bacteria, viruses, fungi, parasites, and tumours. While we see some signal for certain antigen types, using dissimilarity is not a useful approach to identifying antigenic molecules within pathogen genomes.

Discriminating antigen and non-antigen using proteome dissimilarity II:viral and fungal antigens

Immunogenicity arises via many synergistic mechanisms, yet the overall dissimilarity of pathogenic proteins versus the host proteome has been proposed as a key arbiter. We have previously explored this concept in relation to Bacterial antigens; here we extend our analysis to antigens of viral and fungal origin. Sets of known viral and fungal antigenic and non-antigenic protein sequences were compared to human and mouse proteomes. Both antigenic and non-antigenic sequences lacked human or mouse homologues. Observed distributions were compared using the non-parametric Mann-Whitney test. The statistical null hypothesis was accepted, indicating that antigen and non-antigens did not differ significantly. Likewise, we could not determine a threshold able meaningfully to separate non-antigen from antigen. We conclude that viral and fungal antigens cannot be predicted from pathogen genomes based solely on their dissimilarity to mammalian genomes.

Supervisor-subordinate age dissimilarity and performance ratings:the buffering effects of supervisory relationship practice

Using 394 pairs of employees and their immediate supervisors working in the Information and Communication Technology (ICT) sector in three northern European countries, this study examined the effect of workplace moderators on the link between relational demography and supervisor ratings of performance. Directional age differences between superior and subordinate (i.e., status incongruence caused when the supervisor is older or younger than his/her subordinate) and non-directional age differences were used as predictors of supervisor ratings of occupational expertise. The quality of the supervisor-subordinate relationship and the existence of positive age-related supervisory practices were examined as moderators of this relationship. The results provide no support for a relationship between directional age differences and age-related stereotyping by supervisors in ratings of performance, neither for the effects of age-related supervisory practices. However, high quality supervisor-subordinate relationships did moderate the effects of age dissimilarity on supervisory ratings. The implications of these findings for performance appraisal methodologies and recommendations for further research are discussed.

Surface- and deep-level dissimilarity effects on social integration and individual effectiveness related outcomes in work groups:a meta-analytic integration

Prior research linking demographic (e.g., age, ethnicity/race, gender, and tenure) and underlying psychological (e.g., personality, attitudes, and values) dissimilarity variables to individual group member's work-related outcomes produced mixed and contradictory results. To account for these findings, this study develops a contingency framework and tests it using meta-analytic and structural equation modelling techniques. In line with this framework, results showed different effects of surface-level (i.e., demographic) dissimilarity and deep-level (i.e., underlying psychological) dissimilarity on social integration, and ultimately on individual effectiveness related outcomes (i.e., turnover, task, and contextual performance). Specifically, surface-level dissimilarity had a negative effect on social integration under low but not under high team interdependence. In return, social integration fully mediated the negative relationship between surface-level dissimilarity and individual effectiveness related outcomes under low interdependence. In contrast, deep-level dissimilarity had a negative effect on social integration, which was stronger under high and weaker under low team interdependence. Contrary to our predictions, social integration did not mediate the negative relationship between deep-level dissimilarity and individual effectiveness related outcomes but suppressed positive direct effects of deep-level dissimilarity on individual effectiveness related outcomes. Possible explanations for these counterintuitive findings are discussed. © 2011 The British Psychological Society.

Nothing succeeds like moderation:a social self-regulation perspective on cultural dissimilarity and individual performance.

Addressing inconsistencies in relational demography research, we examine the relationship between cultural dissimilarity and individual performance through the lens of social self-regulation theory, which extends the social identity perspective in relational demography with the analysis of social self-regulation. We propose that social self-regulation in culturally diverse teams manifests itself as performance monitoring (i.e., individuals' actions to meet team performance standards and peer expectations). Contingent on the status associated with individuals' cultural background, performance monitoring is proposed to have a curvilinear relationship with individual performance and to mediate between cultural dissimilarity and performance. Multilevel moderated mediation analyses of time-lagged data from 316 members of 69 teams confirmed these hypotheses. Cultural dissimilarity had a negative relationship with performance monitoring for high cultural-status members, and a positive relationship for low cultural-status members. Performance monitoring had a curvilinear relationship with individual performance that became decreasingly positive. Cultural dissimilarity thus was increasingly negatively associated with performance for high culturalstatus members, and decreasingly positively for low cultural-status members. These findings suggest that cultural dissimilarity to the team is not unconditionally negative for the individual but, in moderation, may in fact have positive motivational effects.

Comparing dissimilarity measures for content-based image retrieval

Dissimilarity measurement plays a crucial role in content-based image retrieval, where data objects and queries are represented as vectors in high-dimensional content feature spaces. Given the large number of dissimilarity measures that exist in many fields, a crucial research question arises: Is there a dependency, if yes, what is the dependency, of a dissimilarity measure’s retrieval performance, on different feature spaces? In this paper, we summarize fourteen core dissimilarity measures and classify them into three categories. A systematic performance comparison is carried out to test the effectiveness of these dissimilarity measures with six different feature spaces and some of their combinations on the Corel image collection. From our experimental results, we have drawn a number of observations and insights on dissimilarity measurement in content-based image retrieval, which will lay a foundation for developing more effective image search technologies.

Das Wort zum Trauermarsch:Die gesammelten Songtexte und Aufzeichnungen von Joy Division-Sänger Ian Curtis

Die gesammelten Songtexte und Aufzeichnungen von Joy Division-Sänger Ian Curtis. Von Uwe Schütte

Improved data visualisation through multiple dissimilarity modelling

Popular dimension reduction and visualisation algorithms rely on the assumption that input dissimilarities are typically Euclidean, for instance Metric Multidimensional Scaling, t-distributed Stochastic Neighbour Embedding and the Gaussian Process Latent Variable Model. It is well known that this assumption does not hold for most datasets and often high-dimensional data sits upon a manifold of unknown global geometry. We present a method for improving the manifold charting process, coupled with Elastic MDS, such that we no longer assume that the manifold is Euclidean, or of any particular structure. We draw on the benefits of different dissimilarity measures allowing for the relative responsibilities, under a linear combination, to drive the visualisation process.