Social democracy, embeddedness and decommodification: On the conceptual innovations and intellectual affiliations of Karl Polanyi

Of the several debates that revolve around the work of the economic historian and political economist Karl Polanyi, one that continues to exercise minds concerns his analysis of, and political attitudes toward, post-war capitalism and the welfare state. Simplified a little, it is a debate with two sides. To borrow Iván Szelényi's terms, one side constructs a ‘hard’ Karl Polanyi, the other a ‘soft’ one. The former advocated a socialist mixed economy dominated by redistributive mechanisms. He was a radical socialist for whom the market should never be the dominant mechanism of economic coordination. His ‘soft’ alter ego insisted that the market system remain essentially intact but be complemented by redistributive mechanisms. The ‘double movement’ – the central thesis of his ‘Great Transformation’ – acts, in this reading, as a self-correcting mechanism that moderates the excesses of market fundamentalism; its author was positioned within the social-democratic mainstream for which the only realistic desirable goal is a regulated form of capitalism. In terms of textual evidence there is much to be said for both interpretations. In this article I suggest a different approach, one that focuses upon the meaning of Polanyi's concepts in relation to their socio-political and intellectual environment

Twitter-based analysis of the dynamics of collective attention to political parties

Large-scale data from social media have a significant potential to describe complex phenomena in real world and to anticipate collective behaviors such as information spreading and social trends. One specific case of study is represented by the collective attention to the action of political parties. Not surprisingly, researchers and stakeholders tried to correlate parties' presence on social media with their performances in elections. Despite the many efforts, results are still inconclusive since this kind of data is often very noisy and significant signals could be covered by (largely unknown) statistical fluctuations. In this paper we consider the number of tweets (tweet volume) of a party as a proxy of collective attention to the party, identify the dynamics of the volume, and show that this quantity has some information on the elections outcome. We find that the distribution of the tweet volume for each party follows a log-normal distribution with a positive autocorrelation of the volume over short terms, which indicates the volume has large fluctuations of the log-normal distribution yet with a short-term tendency. Furthermore, by measuring the ratio of two consecutive daily tweet volumes, we find that the evolution of the daily volume of a party can be described by means of a geometric Brownian motion (i.e., the logarithm of the volume moves randomly with a trend). Finally, we determine the optimal period of averaging tweet volume for reducing fluctuations and extracting short-term tendencies. We conclude that the tweet volume is a good indicator of parties' success in the elections when considered over an optimal time window. Our study identifies the statistical nature of collective attention to political issues and sheds light on how to model the dynamics of collective attention in social media.Comment: 16 pages, 7 figures, 3 tables. Published in PLoS ON

The Effects of Twitter Sentiment on Stock Price Returns

Social media are increasingly reflecting and influencing behavior of other complex systems. In this paper we investigate the relations between a well-know micro-blogging platform Twitter and financial markets. In particular, we consider, in a period of 15 months, the Twitter volume and sentiment about the 30 stock companies that form the Dow Jones Industrial Average (DJIA) index. We find a relatively low Pearson correlation and Granger causality between the corresponding time series over the entire time period. However, we find a significant dependence between the Twitter sentiment and abnormal returns during the peaks of Twitter volume. This is valid not only for the expected Twitter volume peaks (e.g., quarterly announcements), but also for peaks corresponding to less obvious events. We formalize the procedure by adapting the well-known "event study" from economics and finance to the analysis of Twitter data. The procedure allows to automatically identify events as Twitter volume peaks, to compute the prevailing sentiment (positive or negative) expressed in tweets at these peaks, and finally to apply the "event study" methodology to relate them to stock returns. We show that sentiment polarity of Twitter peaks implies the direction of cumulative abnormal returns. The amount of cumulative abnormal returns is relatively low (about 1-2%), but the dependence is statistically significant for several days after the events

Dispersal similarly shapes both population genetics and community patterns in the marine realm.

Dispersal plays a key role to connect populations and, if limited, is one of the main processes to maintain and generate regional biodiversity. According to neutral theories of molecular evolution and biodiversity, dispersal limitation of propagules and population stochasticity are integral to shaping both genetic and community structure. We conducted a parallel analysis of biological connectivity at genetic and community levels in marine groups with different dispersal traits. We compiled large data sets of population genetic structure (98 benthic macroinvertebrate and 35 planktonic species) and biogeographic data (2193 benthic macroinvertebrate and 734 planktonic species). We estimated dispersal distances from population genetic data (i.e., FST vs. geographic distance) and from β-diversity at the community level. Dispersal distances ranked the biological groups in the same order at both genetic and community levels, as predicted by organism dispersal ability and seascape connectivity: macrozoobenthic species without dispersing larvae, followed by macrozoobenthic species with dispersing larvae and plankton (phyto- and zooplankton). This ranking order is associated with constraints to the movement of macrozoobenthos within the seabed compared with the pelagic habitat. We showed that dispersal limitation similarly determines the connectivity degree of communities and populations, supporting the predictions of neutral theories in marine biodiversity patterns.RADIALES (IEO)Versión del edito

Phytoplankton across Tropical and Subtropical Regions of the Atlantic, Indian and Pacific Oceans

Postprint4,411

Marine Strategy Framework Directive - Descriptor 2, Non-Indigenous Species, Delivering solid recommendations for setting threshold values for non-indigenous species pressure on European seas

Marine Non-Indigenous Species (NIS) are animals and plants introduced accidently or deliberately into the European seas, originating from other seas of the globe. About 800 marine non-indigenous species (NIS) currently occur in the European Union national marine waters, several of which have negative impacts on marine ecosystem services and biodiversity. Under the Marine Strategy Framework Directive (MSFD) Descriptor 2 (D2), EU Member States (MSs) need to consider NIS in their marine management strategies. The Descriptor D2 includes one primary criterion (D2C1: new NIS introductions), and two secondary criteria (D2C2 and D2C3). The D2 implementation is characterized by a number of issues and uncertainties which can be applicable to the Descriptor level (e.g. geographical unit of assessment, assessment period, phytoplanktonic, parasitic, oligohaline NIS, etc.), to the primary criterion D2C1 level (e.g. threshold values, cryptogenic, questionable species, etc), and to the secondary criteria D2C2 and D2C3. The current report tackles these issues and provides practical recommendations aiming at a smoother and more efficient implementation of D2 and its criteria at EU level. They constitute a solid operational output which can result in more comparable D2 assessments among MSs and MSFD regions/subregions. When it comes to the policy-side, the current report calls for a number of different categories of NIS to be reported in D2 assessments, pointing the need for the species to be labelled/categorised appropriately in the MSFD reporting by the MSs. These suggestions are proposed to be communicated to the MSFD Working Group of Good Environmental Status (GES) and subsequently to the Marine Strategy Coordination Group (MSCG) of MSFD. Moreover, they can serve as an input for revising the Art. 8 Guidelines

Plasma-wall interaction studies within the EUROfusion consortium: Progress on plasma-facing components development and qualification

This work has been carried out within the framework of the EUROfusion Consortium and has received funding from the Euratom research and training programme 2014-2018 under grant agreement No 633053. The views and opinions expressed herein do not necessarily reflect those of the European Commission.The provision of a particle and power exhaust solution which is compatible with first-wall components and edge-plasma conditions is a key area of present-day fusion research and mandatory for a successful operation of ITER and DEMO. The work package plasma-facing components (WP PFC) within the European fusion programme complements with laboratory experiments, i.e. in linear plasma devices, electron and ion beam loading facilities, the studies performed in toroidally confined magnetic devices, such as JET, ASDEX Upgrade, WEST etc. The connection of both groups is done via common physics and engineering studies, including the qualification and specification of plasma-facing components, and by modelling codes that simulate edge-plasma conditions and the plasma-material interaction as well as the study of fundamental processes. WP PFC addresses these critical points in order to ensure reliable and efficient use of conventional, solid PFCs in ITER (Be and W) and DEMO (W and steel) with respect to heat-load capabilities (transient and steady-state heat and particle loads), lifetime estimates (erosion, material mixing and surface morphology), and safety aspects (fuel retention, fuel removal, material migration and dust formation) particularly for quasi-steady-state conditions. Alternative scenarios and concepts (liquid Sn or Li as PFCs) for DEMO are developed and tested in the event that the conventional solution turns out to not be functional. Here, we present an overview of the activities with an emphasis on a few key results: (i) the observed synergistic effects in particle and heat loading of ITER-grade W with the available set of exposition devices on material properties such as roughness, ductility and microstructure; (ii) the progress in understanding of fuel retention, diffusion and outgassing in different W-based materials, including the impact of damage and impurities like N; and (iii), the preferential sputtering of Fe in EUROFER steel providing an in situ W surface and a potential first-wall solution for DEMO.European Commission; Consortium for Ocean Leadership 633053; Institute of Solid State Physics, University of Latvia as the Center of Excellence has received funding from the European Union’s Horizon 2020 Framework Programme H2020-WIDESPREAD-01-2016-2017-TeamingPhase2 under grant agreement No. 739508, project CAMART

On Processing Temporal Observations in Monitoring of Discrete-Event Systems

Observations play a major role in monitoring and diagnosis of discrete-event systems (DESs). In a distributed, large-scale setting, the observation of a DES over a time interval is not perceived as a totally-ordered sequence of observable labels but, rather, as a directed acyclic graph, under uncertainty conditions. Problem solving, however, requires generating a surrogate of such a graph, the index space. Furthermore, the observation hypothesized so far has to be integrated at the reception of a new fragment of observation. This translates to the need for computing a new index space every time. Since such a computation is expensive, a naive generation of the index space from scratch at the occurrence of each observation fragment becomes prohibitive in real applications. To cope with this problem, the paper introduces an incremental technique for efficiently modeling and indexing temporal observations of DESs