Ranking of Countries for Accelerated Social Evolution in Conditions of Global Crisis
Year: 2026
Type: preprint
Abstract: This paper proposes a comparative framework for evaluating countries not only by their long-term economic or investment attractiveness, but by their capacity to transform systemic crisis into accelerated social adaptation. The model is derived from the broader concept of the Evolutionary Architecture of Society (Nosalsky, 2026e; 2026h), in which society is treated as an adaptive structure whose long-term performance depends on the openness of social selection, the ability of institutions to discover competence, and the capacity to revise their own selection mechanisms. The framework contains five variables: Selection Pressure (S), Mobility and Meritocratic Openness (M), Generational Adaptive Capacity (G), Institutional Learning and Retention (R), and Excessive Destruction (X). The central proposition is that crisis pressure alone does not predict successful adaptation; the decisive factor should be the interaction between pressure and the openness of social selection. This idea formalizes the hypothesis that crisis is a forced and extremely costly reopening of closed selection loops (Nosalsky, 2026e), and in structure it is close to the concept of “critical junctures” developed by Acemoglu and Robinson (2012). The paper’s own contribution lies in separating the variables, in distinguishing formal from operational meritocracy, in the generational channel, and in falsifiable predictions for the current case of Ukraine. The paper compares the framework with the long-term approach of Volodymyr Stus and with the closest academic predecessors: Acemoglu and Robinson, Olson, Scheidel, and Turchin. This is a research release, not a final econometric ranking. Where internationally comparable data exist, they are used; where measurement is not yet available, the variable is explicitly identified as a hypothesis. The table of “ranking” is an order of research priority, not a forecast of national success. Artificial intelligence tools (including ChatGPT and Claude) were used in the preparation of this manuscript to assist with research organization, literature presentation, drafting, comparison of conceptual models, source verification, and linguistic refinement. The underlying research questions, theoretical framework, hypotheses, and interpretive direction were developed by the human author. The author is responsible for the final content, verification, and conclusions.
Author: Nosalsky, Andriy
Language: English
Subfield: Economics and Econometrics
Domain: Social Sciences
Open Access status: green
OpenAlex ID: W7220938263