idéalisations

Idealisations are deliberate simplifications used in reasoning, theory construction, and modeling to focus on essential features of a system by neglecting or fixing other aspects. They are methodological tools rather than claims about how the world actually is, and they help researchers analyze complex phenomena, derive general laws, and generate predictions.

In science and mathematics, idealisations appear in many forms. In physics, common idealisations include a frictionless plane, a point mass, a rigid body, or a continuous, empty space, and the use of Newtonian gravity or instantaneous action at a distance. In economics and social sciences, models often assume perfect competition, rational agents, or infinite divisibility of goods to study core dynamics before introducing complications. In mathematics, idealisations are seen in axiomatic systems and abstract structures (for example, Euclidean geometry or real-number continuity) that enable precise reasoning before applying results to the real world.

The use of idealisations involves a trade-off between tractability and realism. Their validity is judged by the scope of the model, its predictive success, and coherence with empirical data. A key distinction is that an idealisation is a deliberate simplifying assumption, whereas an approximation emphasizes that there is a discrepancy between the model and reality. When assumptions prove inadequate, models are refined by relaxing or replacing idealisations, or by adding layers of complexity in a controlled, iterative way.

Idealisations therefore play a central role in theory-building: they illuminate mechanisms, guide experiments, and provide a baseline against which more realistic models can be compared.