[-empyre-] scalable relations --> hung up on scalability

A. LaFarge alafarge at uci.edu
Wed Feb 18 03:04:29 EST 2009

>  > Scalability as a spatial/temporal
>  > transformation is readily available with digital activities, as 
>>  facile as other gestures such as translation and rotation and as 
>>  simple as a cinematic cut."

Hello all-- sorry to be jumping in so late-- it appears that although 
my brain scales reasonably well (!) to information overload, the 
24-hour day does not scale at all...

I keep getting hung up on two aspects of this discussion. One, the 
sense that the term 'scalable relations' is being used presumptively 
as to both its definition and its applicability. Sheldon's breakdown 
was very helpful, but each time the term is used, it seems to carry a 
slightly different sense. Mainly it seems to refer to the handling of 
ever larger data sets gracefully. But I wonder, do all the software 
infrastructures we are using in this exhibition really exhibit this 
property? Or only certain ones? Or only the ones being used in 
certain (normative) ways? I am somewhat puzzled to make this concept 
fit my own project, for one.

Secondly: I see a tendency to focus on the technology rather than its 
use-- on the system and dataset rather than the information, as if 
systems-with-datasets were neutral objects from which information 
spontaneously arises.  Scalability as a "spatial/temporal 
transformation." "Gestures such as translation and rotation." "The 
mutability of the processes of data collection, algorithmicization 
and dynamics simulation." Acknowledgment is made that these do affect 
"the production of meaning" and create "fundamental changes in 
representation", but absent any specifics, one is left rather with 
the sense that the techne itself is in the driver's seat. I part 
company with McLuhan here-- if the medium is the message, it is only 
part of the message. How do we address the fact that it is not only 
how we design scalable systems but what we do with them that creates 
good and bad datasets, and therefore good and bad information?


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