Development of socio-historical models as acognitive process: a cross-disciplinary analysis
Автор: Anikeeva Olga Aleksandrovna
Журнал: Сервис plus @servis-plus
Рубрика: Общественные науки
Статья в выпуске: 2 т.8, 2014 года.
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The article analyses the problems of modeling as a means of socio-historical cognition. The major discrepancy lies in the fact that the practice of cognition, as well as change-oriented activity, frequently employ modeling, while the principles and methods of model-development have not been clearly defined. The article considers the correlation between modeling and the conventional methods of historical research, and identifies the common and specific aspects of their implementation, the peculiarities of socio-historical modeling and its functions. Modern science regards a model as analogous to a protoimage (a fact, an event, a process), its symbolic representation, or an idealized pattern (actions, behavior). The article highlights the basic principles underlying the development of socio-historical models: a model is representational (reflecting the ontological features of the protoimage), relevant, both conditional and autonomous, moreover, a model has its individual life cycle, with the existence and development of the model determined by its cognitive value. Modeling as a cognitive method emerged in response to the new perspective which viewed socio-historical processes as products of the meaningful activity of the agent. One of the most significant constituents of the model is its axiological motivation, which reflects the axiological system and the ideology immanent to the protoimage, and, thus, accounts for both the specifics and the essence of modeling. Another peculiarity and forte of modeling is the possibility and tolerance of the quantification of socio-historical processes, that is, translating qualitative characteristics onto the quantitative plane and developing mathematical models which lend themselves to mathematical study and interpretation, reducing ideological and axiological influences.
Functions of modeling, quantification, modeling as a cognitive methods, modeling principles, forecasting-and-simulation model
Короткий адрес: https://sciup.org/140210244
IDR: 140210244 | DOI: 10.12737/3886