I often use the metaphor of “sliding scale” to indicate a situation that can be described as having two end points and a continuum of blended conditions between those two points. The image came about first when talking about the different social relations indicated by the two end points “network” and “hierarchy” — and how any particular social system can be characterized as sitting somewhere along the line between those two (theoretical!) end points. I’ve always been uncomfortable with the geometric linearity of such a metaphoric illustration, though, as is relies on a limited Cartesian model. And, indeed, in an open system there are no end points to any particular description system. So, does “spectrum” OR “spectral range” perform an adequate substitution?

To speak of or to “re-present” an open system is to close the system. Language and re-presentation is a process of reduction and modeling of reality (where reality is the open system). The question of the adequacy of representation is core in this Age of Data Mining. The challenge of rendering digital data into human-readable analog information that can be effectively interpreted will always be the limiting factor in any data-driven decision-making process.

Back to the spectrum question: it is foundational to identify the (multi)variables that are of interest or crucial to what is being examined. A spectral space allows for this, but also allows for degrees of complexity that are greater than can be sensibly interpreted. This is where intuition, not analysis, comes into play. Forget artificial intelligence (what has intelligence brought us, anyway?); forget fast-Fourier-transformations (except in the case that they are generated through meat-space neural cascades; better to use a manual quasi-Gaussian blur by squinting and whatever analog output you can manage)… argh; the question of interpretation of what the spectral model presents is another challenge altogether.