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"What can employee participation processes learn from Wikipedia and Obama's election campaign?" In an environment of steadily growing interest in collective intelligence in the society this dissertation deals with the systematization and assessment of participation processes based on collective intelligence. It follows a transdisciplinary approach and examines processes from three areas: Policy, Economy and New Media. Applying the theory of the psychology of personal constructs and the repertory grid interviewing technique a multi-dimensional model for participation processes is constructed. Using these defined dimensions then selected processes of all three areas are evaluated and compared. A special chapter deals with identifying gaps of economical participation processes and formulating hypotheses for scientific and applied improvement potential.

collective intelligence, participation, personal constructs, repertory grids, nextexeprtizer, wikipedia, facebook, systems theory, great man theory, leadership, network. - "What can employee participation processes learn from Wikipedia and Obama's election campaign?" In an environment of steadily growing interest in collective intelligence in the society this dissertation deals with the systematization and assessment of participation processes based on collective intelligence. It follows a transdisciplinary approach and examines processes from three areas: Policy, Economy and New Media. Applying the theory of the psychology of personal constructs and the repertory grid interviewing technique a multi-dimensional model for participation processes is constructed. Using these defined dimensions then selected processes of all three areas are evaluated and compared. A special chapter deals with identifying gaps of economical participation processes and formulating hypotheses for scientific and applied improvement potential.

This article examines the obstacles to public participation in a representative democracy and the approaches that can help to overcome these obstacles. Democracy is never perfect because of the inherent difficulties of developing democratic institutions, yet the drawbacks of representative democracy are considerably greater than those of direct democracy. We consider public participation as an element of direct democracy integrated into the structure of representative democracy in order to balance the power of the centre with that of the constituent members of the democratic system. We underscore the role of nomocracy, by which we mean promoting the power of equitable legal and other social rules over the power of the centre. In public participation, the functioning of rules faces greater obstacles than in other forms of democracy. Thus, the professionalism of planners and public administrators is particularly important in formulating these rules; it is even more important when the challenges of establishing rules are major or insuperable. We distinguish between two types of planning professionalism: teleocratic (based primarily on technocratic skills) and nomocratic (based on the nomocratic liberal approach). We recognize the significance of the former, but our main contribution to the debate on public participation is to emphasize the crucial importance and priority of nomocratic professionalism in overcoming the difficulties of citizen involvement and the shortcomings of representative democracy. To test our conclusions, we explore the practice of citizen engagement in the process of planning bikeway networks in several large Bulgarian cities, where public participation is frustrated by the prevalence of the teleocratic approach and the lack of nomocratic traditions.

With numerous endemic subspecies representing four of its five evolutionary lineages, Europe holds a large fraction of Apis mellifera genetic diversity. This diversity and the natural distribution range have been altered by anthropogenic factors. The conservation of this natural heritage relies on the availability of accurate tools for subspecies diagnosis. Based on pool-sequence data from 2145 worker bees representing 22 populations sampled across Europe, we employed two highly discriminative approaches (PCA and FST) to select the most informative SNPs for ancestry inference. Results: Using a supervised machine learning (ML) approach and a set of 3896 genotyped individuals, we could show that the 4094 selected single nucleotide polymorphisms (SNPs) provide an accurate prediction of ancestry inference in European honey bees. The best ML model was Linear Support Vector Classifier (Linear SVC) which correctly assigned most individuals to one of the 14 subspecies or different genetic origins with a mean accuracy of 96.2% ± 0.8 SD. A total of 3.8% of test individuals were misclassified, most probably due to limited differentiation between the subspecies caused by close geographical proximity, or human interference of genetic integrity of reference subspecies, or a combination thereof. Conclusions: The diagnostic tool presented here will contribute to a sustainable conservation and support breeding activities in order to preserve the genetic heritage of European honey bees. ; The SmartBees project was funded by the European Commission under its FP7 KBBE programme (2013.1.3–02, SmartBees Grant Agreement number 613960) https://ec.europa.eu/research/fp7. MP was supported by a Basque Government grant (IT1233–19). The funders provided the financial support to the research, but had no role in the design of the study, analysis, interpretations of data and in writing the manuscript. ; info:eu-repo/semantics/publishedVersion