Kinga Varga (MTA TK RECENS, ELTE): Optimisation of the clustering of signed graphs
Signed graphs contain different types of relations towards actors in SNA. The assignment of a positive or negative relationship finds its roots in structural balance theory. The mathematical formalization of this concept was later added by Harary (1953) and Cartwright (1956, 1979). The generalisation specify subgroups with similar characteristics related to their links to other actors in the network. Subdividing actors into prespecified homogeneous blocks provides for the analysis of such network data related to internal and external characteristics. Besides, the different clusters are interpreted in more precise and adequate ways in order to obtain coherent subgroups for the spatial and temporal analysis simultaneously. Extending the major concept of cluster analysis, blockmodeling is a method to delineate the underlying structure of a social network, transforming it into a smaller and rather comprehensible unit (Batagelj et al 2004). Compiling an interpretable model, we construct our analysis relying on both an indirect and direct approach in the framework of the corresponding and comparable blockmodels.
Gábor Péli (University of Utrecht, Netherlands): A new trend in publications. Why do sociologists publish in natural sciences journals?
The presentation concerns social science dynamics. Recently, a new international publication trend has been emerging among – mathematically oriented – sociologist: they have begun publishing their sociological results in physics outlets. As a preceding event, natural scientists, most prominently statistical physicists, had been evading certain social science domains. Their main entry point to sociology was network theory. To the disappointment of several sociologist colleagues, these physicists have been successfully harvesting results in social domains with their methods tuned to large data throughput. This is especially the case with large scale communication networks that provide tons of cheap data on agentscharacterized with a limited number of variables. Of course, sociologists can criticize these approaches as ’simplistic’ with good reason. But clearly, the sociology profession has overlooked an opportunity to be the first-mover of that kind of big data analysis concerning large-scale networks. But in the meanwhile, a new generation of network sociologists is growing up who see such physics-related methods as complements to ’traditional’ social network research. Even more interestingly, an increasing number of sociologists have recently begun paying back physicists’ visit, publishing (mathematically underpinned) sociological papers in natural science journals. Still, some intriguing asymmetries reside between physicists’ visit to social sciences and sociologists’ entering physics journals, - for which I’d like to suggest explanations. Intriguing and sensitive issues arise. In which sense do we witness some (partial) convergence between natural and social science research domains? Along which aspects would the division lines between these domains sustain, possibly in a reinforced manner?
Tamás Keller (TÁRKI, MTA TK RECENS): Why do school grades have an effect on subsequent academic achievement?
This paper argues that grades cannot be interpreted only as a reward for a given academic achievement, but they also reflect teachers’ ratings of pupils. Relative within-classroom differences in grades therefore contain valuable information about pupils’ own – usually unknown – ability, and could have an effect on subsequent academic achievement. Previous studies have found that school grading standards have a small but statistically significant positive effect on subsequent academic achievement. However, those studies have been less than forthcoming about why this is so. Here we analyse the impact of grades at the individual level and seek to answer the question of what happens if pupils receive better grades for the same academic achievement. Do better grades subsequently motivate students to achieve more, or is the effect actually demotivating? Moreover, is the impact of grades a compositional effect of the classroom (who are the peers, how good are the teachers, how good is the school) or is it universal? In addition, this article seeks to cast light on why school grades are important in later academic achievement. By applying first-difference and fixed effect estimators to various types of Hungarian educational panel datasets, we show that grades do have a positive effect on subsequent academic achievement. This holds true for those who have not switched classes. The estimated impact is independent of classroom composition, showing that the benefit arising from within-classroom differences in grades occurs in every classroom. The growth of self-confidence is offered as a possible underlying mechanism to explain this impact.
Beáta Oborny (ELTE): United we stand, divided we fall? Modularity and adaptive growth in biological organisms
Patchiness of the environment is a common challenge to all living organisms. Essential resources, e.g. water or food, are heterogeneously distributed in space, and can change over time. The task is to maximize resource uptake under two constraints: (1) the organism has only limited information about the location of resource patches, and (2) has limited resource that can be used for moving to patches. Thus, the behavioral pattern has to be adjusted to an (often largely unknown) habitat pattern, and mistakes are costly. Different species show a great diversity of solutions for this problem. An interesting way is offered by modular development, which occurs in several, large taxonomic groups in the living world (plants, sponges, cnidarians, etc.). Modules can take samples from multiple points in a habitat, and can share information and resources. There are two basic questions that emerge in any particular habitat type: (1) What is the optimal degree of integration between modules? (2) What is the optimal degree of plasticity, i.e., how easily a module should be changed according to the environment? I introduce these questions by some examples from plants, and by related computer simulations.