Grandpierre, A. 2014, A Model-Independent Method to Analyze The Logic of World Models. Published in: Phenomenological Paths in Post-Modernity, ed. D. Verducci, pp. 519-560.
In this paper we consider whether it is possible to agree on the basic
questions of scientific method and philosophy, in a way that has a most suitable, universally reliable basis, free from awkward commitments and presuppositions. The biggest obstacle on the road to develop philosophy into a universally acceptable science is that diVerent systems of philo- sophy attribute, somewhat awkwardly, diVerent weights to diVerent basic concepts. These attributions generally contain implicit metaphy- sical presuppositions about what exists, or what exists “really”. Such presuppositions play a crucial role in obtaining the main structure of the world models corresponding to diVerent philosophical schools, pri- marily determining the whole system of relations between their central and secondary concepts. We formulate these relations in a mathema- tical form expressing the logical inclinations of the world models. It is timely to consider the presuppositions in order to obtain a general, model–independent, universally acceptable and reliable approach. We extend the requirement of universal acceptability and reliability to the most basic presuppositions of science and philosophy and determine which of them are model–independent. We present a short picture about some world models (of Materialism, Idealism, Theism, Physicalism, Na- turalism, Dualism and Phenomenology) in the light of their central concepts and their conceptual weights. The obtained results indicate that phenomenology has a scientific attitude considering the utmost basis of knowledge in the immediate experience. Exploring the consequences of this recognition we found that phenomenology has a deeper concept about the nature of the Universe than natural sciences have at present, and it is suitable to explore how can the subject play a central role in the new scientific world picture. Finally, we consider how our results can contribute to optimize the world models for mankind’s future.