System and structural modelling of social vulnerability of the population: a conceptual and methodological approach

Abstract

The article proves that social resilience is the ability of the system to provide dynamic equilibrium. This approach made it possible to calculate empirical indicators of social resilience within the threshold limit and optimal values. The article substantiates that the emergence of new threats changes the previous state of the system, which can also be within acceptable limits (state of dynamic equilibrium). Social resilience enters into a new state, with different characteristics from the previous one, while not only the structure of the system (composition of elements) changes, but also the system relationships between indicators and the strength of influence of structural components on the system. The authors suggest carrying out studies of social vulnerability through the gradation of social resilience levels, which is a structural and compositional characteristic of the state of the economic system and reflects the functioning of such spheres as the quality of social and labour relations, the level and quality of life and demographic, environmental, and food security. The article proves that the effectiveness of monitoring social resilience for assessing the social vulnerability of the population correlates with the principles of complexity, consistency, hierarchy, adequacy, unambiguity, and continuity. The authors use a methodical approach to the calculation of vectors of threshold values of indicators of social resilience – (1) lower limit – upper limit; (2) lower optimal – upper optimal, which characterizes the permissible interval, the intersection of which means a violation of the equilibrium state. The proposed methodical approach to the study of social vulnerability is based on the formation of a system of components and indicators (grouped into regressors and catalysts), the substantiation of a rational methodology for normalizing indicators, determination of constant or dynamic coefficients of weight significance of indicators and components, as well as threshold values. The conceptual task of regulating catalysts, regressors, and components of social resistance is to determine their level (indicator value) in the system of indicators, which will ensure that the values of the compositional coefficient are found within the optimal threshold values.