While filmic techniques allow Bennett to visual aspects of the intercalated disc in motion, she also works with colleagues to render the disc's structural features using architectural modeling software like AutoCAD. As at right, we see a schematized simulation of the disc’s three dimensional structure. Electron tomography visualization of microscopic cell contractions in the heart thus lead to an architectural modeling of the parameters of a feature of special
interest, the intercalated disc. So, if visualization begets architectural modeling, Bennett and
her colleagues also return to the lab where they treat the diseased hearts of mice
as surrogates for—model organisms of—pathological human hearts.
A comparable to-and-fro can be found in conservation and materials science. At the Courtauld Institute of Art in London, conservator Christina Young aims to understand and ultimately minimize sagging canvases and the havoc they can wreak on the painted images they carry. To study the strain levied on fabric supports when pulled taut on a
stretcher to form vaunted Greenbergian flatness, Young prepares an idealized model canvas—one free of all the shortcuts, material weakness and other contingencies of normal artistic practice. She then subjects it to a battery of tests under laboratory conditions and studies their tensile filaments under pressure with a microscope.
Then, she studies the manipulated model object with an electronic speckle pattern interferometer whose laser refractions can be measured
by a digital camera. These data are then modeled in the computer simulation we
see at left where the effects of tension on the fabric surface are visualized (in completely arbitrary assignments) with
red for most intensive strain, blue for the least.
Meanwhile, just across the Strand at the London School of Economics,
philosopher of science Roman Frigg theorizes these iterative procedures. Modeling, Frigg argues, is a two-part enterprise.
The model is what philosopher Kendall Walton calls a "prop" in a game of make-believe. That is, the modeler creates an
idealized, exaggerated or otherwise fictionalized version of the object or
phenomenon under investigation. This “p-representation” (prop-representation) is then run, manipulated
or otherwise explored. Mathematical coordinates are possibly applied as a means of fleshing out the implications of rules instantiated by the prop’s design.
Secondly, in t or target representation, the modeler contrives a method—so far as that is possible between the conclusions
yielded by exploration of the prop in the modeling scenario and what is known about the "target system," whether this be the effects of economic policies, the physiological structures of the heart or how a seventeenth century canvas will behave.
Crucial for all of these strategies is that a simplified, exaggerated or otherwise fictionalized model becomes the object and field of inquiry from which knowledge about a real-world target is built indirectly. “Model systems are interesting,” writes Frigg, “exactly because more is true of them than what the
initial description specifies; no one would spend time studying models if all
there was to know about them was the explicit content of the initial
description.” Or, as philosophers Tarja Knuuttila and Atro Voutilainen have pithily put it: “A
model has an existence of its own. For this reason we cannot be totally in
charge of it, however purposefully fabricated it may be.” How might we use this approach to think about the ways that artists use models?
