Brenner [1] has published a logical characterization of Nature in which ‘A’ and ‘non-A’ are nonseparable, where ‘A’ and ‘non-A’ are not the terms of standard bivalent logics but refer to elements of evolving processes or systems, and in which a third ‘T-state’ can or will emerge from their interaction in terms of actual and potential. This leads also to the non-separability of ontology and epistemology. We accept that Brenner’s characterization is valid, and have previously addressed [2] its relationship to the representation of hierarchical structure, following the insistence of Havel [3] that scale should be presumed to be a necessary constituent of all theory. In this paper we extend our treatment to the domain of information, which we picture as a coupling between structure and process. Hierarchy is naturally partially birational, between entity and context, and we find that this duality matches Brenner’s characterization. As indicated in Figure 1, the directly-inaccessible duality of scaled data and its scaled context presents itself as the precursor of a partial hyperscalar duality which is ‘the real contextual nature’ [4] of the entity in its temporal and spatial context. These two partial hyperscales self-re-integrate resulting in a singular metascalar T-state which is information. Representation is then the abductive metascalar interpretation of the unification of the dual partial hyperscales which constitutes information. Metascalar information is both objective and subjective, in indivision. The first, entity partial hierarchy is of individual subjective scales of data, while the second is of individual subjective scales of context; a scaled form of von Uexkull’s [5] umwelts. Havel [3] has presented the notion that scientific ‘objectivity’ is in fact societal group subjectivity. The two partial hyperscales are ‘objective’ 2 in Havel’s group-subjective sense. We hypothesize that this duality is at the roots of the real and imaginary parts of evolved complex algebra, in a manner similar to the way that inter-scale data-loss is at the roots of the evolved hierarchical nature of mathematical equations. Figure 1. Scale, context, hyperscale and metascale in a hierarchical system. contextual hyperscale entity hyperscale unified metascale scale hyperscale metascale
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