Platform Advocacy and the Threat to Deliberative Democracy

Businesses have long tried to influence political outcomes, but today, there is a new and potent form of corporate political power—Platform Advocacy. Internet-based platforms, such as Facebook, Google, and Uber, mobilize their user bases through direct solicitation of support and the more troubling exploitation of irrational behavior. Platform Advocacy helps platforms push policy agendas that create favorable legal environments for themselves, thereby strengthening their own dominance in the marketplace. This new form of advocacy will have radical effects on deliberative democracy. In the age of constant digital noise and uncertainty, it is more important than ever to detect and analyze new forms of political power. This Article will contribute to our understanding of one such new form and provide a way forward to ensure the exceptional power of platforms do not improperly influence consumers and, by extension, lawmakers

A cross-cultural study of High School teachers’ tacit knowledge of interpersonal skills

Effective teachers are characterized not only by pedagogical abilities and subject area mastery, but also by interpersonal skills. Using the Tacit Knowledge Inventory for High School Teachers (TKI-HS) – a situational judgement test consisting of 11 challenging interpersonal scenarios – this study compared how experienced teachers in England (n=108), Ireland (n=45) and Russia (n=492) rated seven possible response options for each scenario, to examine the extent to which the concept of “skilled interpersonal behavior” varies across cultures. The results indicate that judgments of “bad” responses are more similar across these three cultures, whereas there seems to be less agreement about what constitutes a “good” response. The importance of teachers’ tacit knowledge and how it varies across cultural contexts are discussed

What exactly are the properties of scale-free and other networks?

The concept of scale-free networks has been widely applied across natural and physical sciences. Many claims are made about the properties of these networks, even though the concept of scale-free is often vaguely defined. We present tools and procedures to analyse the statistical properties of networks defined by arbitrary degree distributions and other constraints. Doing so reveals the highly likely properties, and some unrecognised richness, of scale-free networks, and casts doubt on some previously claimed properties being due to a scale-free characteristic.Comment: Preprint - submitted, 6 pages, 3 figure

Noise reduction in chaotic time series by a local projection with nonlinear constraints

On the basis of a local-projective (LP) approach we develop a method of noise reduction in time series that makes use of nonlinear constraints appearing due to the deterministic character of the underlying dynamical system. The Delaunay triangulation approach is used to find the optimal nearest neighboring points in time series. The efficiency of our method is comparable to standard LP methods but our method is more robust to the input parameter estimation. The approach has been successfully applied for separating a signal from noise in the chaotic Henon and Lorenz models as well as for noisy experimental data obtained from an electronic Chua circuit. The method works properly for a mixture of additive and dynamical noise and can be used for the noise-level detection.Comment: 11 pages, 12 figures. See http://www.chaosandnoise.or