The underlying social dynamics of paradigm shifts

We develop here a multi-agent model of the creation of knowledge (scientific progress or technological evolution) within a community of researchers devoted to such endeavors. In the proposed model, agents learn in a physical-technological landscape, and weight is attached to both individual search and social influence. We find that the combination of these two forces together with random experimentation can account for both i) marginal change, that is, periods of normal science or refinements on the performance of a given technology (and in which the community stays in the neighborhood of the current paradigm); and ii) radical change, which takes the form of scientific paradigm shifts (or discontinuities in the structure of performance of a technology) that is observed as a swift migration of the knowledge community towards the new and superior paradigm. The efficiency of the search process is heavily dependent on the weight that agents posit on social influence. The occurrence of a paradigm shift becomes more likely when each member of the community attaches a small but positive weight to the experience of his/her peers. For this parameter region, nevertheless, a conservative force is exerted by the representatives of the current paradigm. However, social influence is not strong enough to seriously hamper individual discovery, and can act so as to empower successful individual pioneers who have conquered the new and superior paradigm.Fil: Rodriguez Sickert, Carlos. Universidad del Desarrollo; ChileFil: Cosmelli, Diego. Pontificia Universidad Católica de Chile; ChileFil: Claro, Francisco. Pontificia Universidad Católica de Chile; ChileFil: Fuentes, Miguel Angel. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad San Sebastián; Chil

In A Society of Strangers, Kin Is Still Key: Identified Family Relations In Large-Scale Mobile Phone Data

Mobile call networks have been widely used to investigate communication patterns and the network of interactions of humans at the societal scale. Yet, more detailed analysis is often hindered by having no information about the nature of the relationships, even if some metadata about the individuals are available. Using a unique, large mobile phone database with information about individual surnames in a population in which people inherit two surnames: one from their father, and one from their mother, we are able to differentiate among close kin relationship types. Here we focus on the difference between the most frequently called alters depending on whether they are family relationships or not. We find support in the data for two hypotheses: (1) phone calls between family members are more frequent and last longer than phone calls between non-kin, and (2) the phone call pattern between family members show a higher variation depending on the stage of life-course compared to non-family members. We give an interpretation of these findings within the framework of evolutionary anthropology: kinship matters even when demographic processes, such as low fertility, urbanisation and migration reduce the access to family members. Furthermore, our results provide tools for distinguishing between different kinds of kin relationships from mobile call data, when information about names are unavailable.Comment: 26 pages, 5 figures, 1 table, supplementary material at the en

The effect of social interactions in the primary life cycle of motion pictures

We model the consumption life cycle of theater attendance for single movies by taking into account the size of the targeted group and the effect of social interactions. We provide an analytical solution of such model, which we contrast with empirical data from the film industry obtaining good agreement with the diverse types of behaviors empirically found. The model grants a quantitative measure of the valorization of this cul- tural good based on the relative values of the coupling between agents who have watched the movie and those who have not. This represents a measurement of the observed quality of the good that is extracted solely from its dynamics, independently of critics reviews.Comment: 9 Pages, 3 figure

Optimal incentives with state-dependent preferences

Abstract In both experimental and natural settings incentives sometimes under-perform, generating smaller effects on the targeted behaviors than would be predicted for entirely self-regarding agents. A parsimonious explanation is that incentives that appeal to self-regarding economic motives may crowd out non-economic motives such as altruism, reciprocity, intrinsic motivation, ethical values and other social preferences, leading to disappointing and sometimes even counter-productive incentive effects. We present evidence from behavioral experiments that crowding may take two forms: categorical (the effect on preferences depends only on the presence or absence of the incentive) or marginal (the effect depends on the extent of the incentive). We extend an earlier contribution (Bowles and Hwang, 2008) to include categorical crowding, thus providing a more general framework for the study of optimal incentives and as a result, an expanded range of situations for which the sophisticated planner will (surprisingly) make greater use of incentives when incentives crowd out social preferences than when motivational crowding is absent

Institutions influence preferences: Evidence from a common pool resource experiment

We model the dynamic effects of external enforcement on the exploitation of a common pool resource. Fitting our model to experimental data we find that institutions influence social preferences. We solve two puzzles in the data: the increase and later erosion of cooperation when commoners vote against the imposition of a fine, and the high deterrence power of low fines. When fines are rejected, internalization of a social norm explains the increased cooperation; violations (accidental or not), coupled with reciprocal preferences, account for the erosion. Low fines stabilize cooperation by preventing a spiral of negative reciprocation.