Group diversity and group identification:the moderating role of diversity beliefs

Research on diversity in teams and organizations has revealed ambiguous results regarding the effects of group composition on workgroup performance. The categorization—elaboration model (van Knippenberg et al., 2004) accounts for this variety and proposes two different underlying processes. On the one hand diversity may bring about intergroup bias which leads to less group identification, which in turn is followed by more conflict and decreased workgroup performance. On the other hand, the information processing approach proposes positive effects of diversity because of a more elaborate processing of information brought about by a wider pool and variety of perspectives in more diverse groups. We propose that the former process is contingent on individual team members' beliefs that diversity is good or bad for achieving the team's aims. We predict that the relationship between subjective diversity and identification is more positive in ethnically diverse project teams when group members hold beliefs that are pro-diversity. Results of two longitudinal studies involving postgraduate students working in project teams confirm this hypothesis. Analyses further reveal that group identification is positively related to students' desire to stay in their groups and to their information elaboration. Finally, we found evidence for the expected moderated mediation model with indirect effects of subjective diversity on elaboration and the desire to stay, mediated through group identification, moderated by diversity beliefs

Reproducibility in the absence of selective reporting : An illustration from large-scale brain asymmetry research

Altres ajuts: Max Planck Society (Germany).The problem of poor reproducibility of scientific findings has received much attention over recent years, in a variety of fields including psychology and neuroscience. The problem has been partly attributed to publication bias and unwanted practices such as p-hacking. Low statistical power in individual studies is also understood to be an important factor. In a recent multisite collaborative study, we mapped brain anatomical left-right asymmetries for regional measures of surface area and cortical thickness, in 99 MRI datasets from around the world, for a total of over 17,000 participants. In the present study, we revisited these hemispheric effects from the perspective of reproducibility. Within each dataset, we considered that an effect had been reproduced when it matched the meta-analytic effect from the 98 other datasets, in terms of effect direction and significance threshold. In this sense, the results within each dataset were viewed as coming from separate studies in an "ideal publishing environment," that is, free from selective reporting and p hacking. We found an average reproducibility rate of 63.2% (SD = 22.9%, min = 22.2%, max = 97.0%). As expected, reproducibility was higher for larger effects and in larger datasets. Reproducibility was not obviously related to the age of participants, scanner field strength, FreeSurfer software version, cortical regional measurement reliability, or regional size. These findings constitute an empirical illustration of reproducibility in the absence of publication bias or p hacking, when assessing realistic biological effects in heterogeneous neuroscience data, and given typically-used sample sizes