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March 09, 2005

Grids and Networks

I posted an effort to work through Taylor’s grid stuff over at my joint. I’m going to try something similar here in regard to his treatment of the network.

If Taylor’s grid is “the figure of the all-encompassing logic manifest through the marriage of social and mechanical engineering” (31), his network is a polar opposite; “a linked system that entangles everyone in multiple, mutating, and mutually defining connections in which nobody is really in control” (23).

As I noted in my grid grapple, I’m a bit leery of this binary. Is the network, by its structure, nature, and function, more accommodating to contradictions than the grid? How does the rectilinear frame of the grid cause the structure itself to reject all contradictions?
Both the grid and the network assume implicitly that each node in the structure is a separate entity. But it seems we need a way to take into account the interactions between and among nodes if we are to quantify such interactions (isn’t this what Taylor is attempting to do through his architectural analysis?). To complicate it; do the metrics we use to quantify the interactions necessarily have to be verified by empirical data rather than the subjective metrics used in architectural analysis. My gut tells me this would be incredibly hard to do even on the micro-scales that were discussed in Six Degrees.

There are some simple metrics that have been used in object-oriented software design that might lend themselves to such an analysis -- specifically Yourdon’s Fan-in/Fan-out metrics (where fan-in is a count of the number of modules that call a given module, and fan-out is a count of the number of modules that are called by a given module). This model could be easily extended to apply to the nodes of a network or grid. In general, nodes with a large fan-in would be relatively small and simple, and are probably located at the lower layers of the network structure (as defined by Watts). In contrast, large and complex nodes will likely have a small fan-in. Therefore, nodes that have a large fan-in and large fan-out may indicate a weakness in the network/grid design (whether the design was intentional or organic). From the complexity and defect point of view (since I’m pretty sure that Taylor was exploring the “defects” of networked designs), nodes with a large fan-in would be expected to have negative or insignificant correlation with defect levels, and nodes with a large fan-out would be expected to have a positive correlation.

Holy cr*p, I don’t even think I can follow that without working through it four times. I’m just hung up on this need to quantify in order to analyze beyond subjective statements about function.

Posted by mfrascie at March 9, 2005 07:53 PM

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