In this paper, we show that the certain elaborations of the French sociologist Gariel Tarde may be traced throughout Schumpeter’s works. More specifically, we show that Joseph Schumpeter’s views were influenced by the French social philosopher and theoretician Gabriel Tarde who delivered a theory of Social Evolution based on Technological Change as its driving force, closely related to the profiteering function of the economy. Also, we demonstrate that Tarde’s approach has striking similarities with the Schumpeterian vision of Economic Development, Change and Social Evolution. But there are similarities in their respective methodological approaches as well. For instance, the most striking similarity is that despite the importance he gave to the social stratum, Tarde, just like Schumpeter’s early approach, never fully admitted the determination of the individual’s will by the social forces. In other words, they both attempted to explain social evolution by means of individual initiative. At this point it should be mentioned that Tarde’s theory has been delivered and published about a decade before the publication of the first edition of Schumpeter’s influential Theory of Economic Development.

While China’s dramatic economic rise has attracted global attention, its political and institutional changes have been little noticed or deliberately ignored for ideological reasons. In fact, without much fanfare, Beijing has introduced significant reforms into its way of governance and established an elaborate system of what can be called “selection plus election.” Briefly, competent leaders are selected based on merit and popular support through a vigorous process of screening, opinion surveys, internal evaluations and various small-scale elections. The Communist Party of China may arguably be one of the world’s most meritocratic institutions.

Obviously for Western countries accustomed to the hundreds-year-old capitalist system, it is very difficult for them to understand China’s socialist path. When these countries found that a fast-developing China has not been incorporated into the capitalist order, they criticize China for state capitalism or mercantilism. Nevertheless, this kind of criticism ignores the fact that socialism, which suffered huge setbacks in Europe, has enjoyed prosperous development in China. It is the socialist theory and path that have propelled China to its current status as the world’s second-largest economy. In the future 10 or 15 years, the socialist path with Chinese characteristics is likely to make China become the largest economy. In sum, the difference between China’s development path and the Western mode lies in socialism. Socialism with Chinese characteristics was the basic feature of the country’s development. For a thorough understanding of China, one must learn much about this country’s socialism.

Ramón Ramos Torre Resumen: En este artículo se reconstruye selectivamente la sociología del futuro de los últimos cincuenta años para rescatar algunos de sus elementos y construir una analítica y una problemática del futuro en tiempos de crisis. En su marco se reconstruye la evidencia empírica sobre el futuro social proporcionada por nueve grupos de […]

Despite recent advances driven by machine learning algorithms, experts agree that such algorithms are still often unable to match the experience-based and intuitive problem solving skills of humans in highly complex settings. Recent studies have demonstrated how the intuition of lay people in citizen science games [1] and the experience of fusion-scientists [2] have assisted automated search algorithms by restricting the size of the active search space leading to optimized results. Humans, thus, have an uncanny ability to detect patterns and solution strategies based on observations, calculations, or physical insight. Here we explore the fundamental question: Are these strategies truly distinct or merely labels we attach to different points in a high dimensional continuum of solutions? In the latter case, our human desire to identify patterns may lead us to terminate search too early. We demonstrate that this is the case in a theoretical study of single atom transport in an optical tweezer, where more than 200,000 citizen scientists helped probe the Quantum Speed Limit

While perception tasks such as visual object recognition and text understanding play an important role in human intelligence, the subsequent tasks that involve inference, reasoning and planning require an even higher level of intelligence. The past few years have seen major advances in many perception tasks using deep learning models. For higher-level inference, however, probabilistic graphical models with their Bayesian nature are still more powerful and flexible. To achieve integrated intelligence that involves both perception and inference, it is naturally desirable to tightly integrate deep learning and Bayesian models within a principled probabilistic framework, which we call Bayesian deep learning. In this unified framework, the perception of text or images using deep learning can boost the performance of higher-level inference and in return, the feedback from the inference process is able to enhance the perception of text or images. This survey provides a general introduction to Bayesian deep learning and reviews its recent applications on recommender systems, topic models, and control.

La Revolución Bolivariana fue el primer intento de llevar a cabo una transformación socialista en el siglo XXI en todo el mundo. En consecuencia, los debates sobre la experiencia venezolana se han referido no solo a las dinámicas propias del proceso de transformación en el país desde que Chávez llegó a la presidencia en el año 1999, sino también, en términos más amplios sobre las posibilidades, potencialidades y límites del socialismo en este siglo. Este texto está focalizado en el análisis de la experiencia venezolana, pero esto se realiza dentro del contexto de los debates latinoamericanos sobre el desplazamiento a la izquierda con la emergencia de los gobiernos progresistas en la mayor parte de América del Sur y de los debates globales sobre alternativas viables para trascender el capitalismo.

The complex nature of organizational culture challenges our ability to infers its underlying dynamics from observational studies. Recent computational studies have adopted a distinct different view, where plausible mechanisms are proposed to describe a wide range of social phenomena, including the onset and evolution of organizational culture. In this spirit, this work introduces an empirically-grounded, agent-based model which relaxes a set of assumptions that describes past work – (a) omittance of an individual’s strive for achieving cognitive coherence, (b) limited integration of important contextual factors – by utilizing networks of beliefs and incorporating social rank into the dynamics. As a result, we illustrate that: (i) an organization may appear to be increasingly coherent in terms of organizational culture, yet be composed of individuals with reduced levels of coherence, (ii) the components of social conformity – peer-pressure and social rank – are influential at different aggregation levels.

Arrow’s Impossibility Theorem in social choice finds different interpretations. Bordes-Tideman (1991) and Tideman (2006) suggest that collective rationality would be an illusion and that practical voting procedures do not tend to require completeness or transitivity. Colignatus (1990 and 2011) makes the distinction between voting and deciding. A voting field arises when pairwise comparisons are made without an overall winner, like in chess or basketball matches. Such (complete) comparisons can form cycles that need not be transitive. When transitivity is imposed then a decision is made who is the best. A cycle or deadlock may turn into indifference, that can be resolved by a tie-breaking rule. Since the objective behind a voting process is to determine a winner, then it is part of the very definition of collective rationality that there is completeness and transitivity, and then the voting field is extended with a decisión.

We search an autocatalytic structure in networks of technological fields and evaluate its significance for technological change. To this aim we define a technology network based on the International Patents Classification, and we study if autocatalytic structures in the network foster innovation as measured by the rate of production of patents. The network is identified through patenting activity of geographical regions in different technology fields. Through our analysis we show how the technological landscape of the patents database evolves as a self-organising autocatalytic structure that grows in size, and arrives to cover the most part of the technology network. Technology classes in the core of the autocatalytic structure perform better in terms of their innovativeness, as measured by the rate of growth of the number of patents. Finally, the links between classes that define the autocatalytic structure of the technology network break the hierarchical structure of the database, and indicate that recombinant innovation and its autocatalytic patterns are an important stylised fact of technological change.