34. Evolution As Adapting To Fit To Changing Contexts

On this model, then, the evolution of models of the experienceable world is a process of models adapting to each other in the contexts in which they function. Empirical science, for example, is not a matter of approximating the categories of Nature and their relations, quantitative and qualitative, because Nature has no categories independent of systems that categorise it. Science involves Nature selecting models of phenomena, these evolving as the context of model building changes — as a consequence of the evolving models and the technologies they engender. 

So, there is no end to ‘the march of science’. Over time, models are expanded — elaborated, extended and enhanced — providing greater delicacy of description and functionality for those who use them. As each model changes, it potentially changes the context in which other models function, triggering continuous cascades of change through systemically related models. The rate of evolution varies, in part, with the degree of selection pressure brought about by changes in its environment. In as much as this process takes time, models are variably adapted to past contexts.[1]

The ability of any model to evolve[2] at given period of its history varies with its capacity to generate potentially useful variation, the “raw material” that is shaped by selection. For example, the evolution of particle physics is partially dependent on the concomitant evolution that provides the technological devices used to observe subatomic events. 

Footnotes:

[1] It may also be that the increasing numbers of practitioners potentially increases the inertia of a discipline, ceteris paribus.

[2] Evolvability can be thought of as the potential of a lineage to exploit evolutionary time for adaptive purposes.

ChatGPT revised:

On this model, the evolution of models of the experienceable world is understood as a process of models adapting to each other within the contexts in which they function. Empirical science, for example, is not simply a matter of approximating the categories of Nature and their relations — whether quantitative or qualitative — because Nature does not have categories independent of the systems that categorise it. Rather, science is the process through which Nature selects models of phenomena. These models evolve as the contexts of model-building change, driven by the evolving models themselves and the technologies they enable.

Thus, the idea of the march of science has no definitive end. Over time, models are expanded, elaborated, extended, and enhanced, providing greater delicacy in description and functionality for those who use them. As each model evolves, it can change the context in which other models operate, triggering continuous cascades of change through systemically related models. The rate of this evolution varies, in part, with the degree of selection pressure brought about by changes in the environment. Models are, therefore, variably adapted to past contexts.

The ability of any model to evolve at a given period in its history is contingent on its capacity to generate potentially useful variation — the “raw material” shaped by the process of selection. For instance, the evolution of particle physics is partially dependent on the concomitant evolution of technological devices that enable the observation of subatomic events.

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Footnotes:

[1] It may also be the case that the increasing number of practitioners potentially increases the inertia of a discipline, assuming other factors are equal (ceteris paribus).

[2] Evolvability refers to the potential of a lineage to exploit evolutionary time for adaptive purposes.