As a geographer, Danielle Marceau’s article “The scale issue in social and natural sciences” is easily digestible. Familiar concepts such as the modifiable areal unit problem (MAUP) are presented in a very clear manner. The article focuses mainly on the effects of scale and aggregates on spatial inferences, and on linking sptial patterns and processes that occur across different scales.
Predicting and controlling for the MAUP can be very difficult, as pointed out by the authors. New technologies may be able to help us solve this problem with their advanced data acquisition and analysis, however even though these technologies exist, conducting such a stud would be nearly impossible. So many processes are connected across varying scale, and when you make statistical inferences about specific phenomena, these inferences surely cannot account for it. We may use GIS to create multiple scale maps to run statistical tests and analyze the appropriate scales, however even in the creation of these ‘test scales’ there is inherent bias, in that we assume we know the limits of the scales of these processes.
Though technology has advanced, I believe this comes down to a philosophical debate about science and about space; can we attempt to identify every exchange in process across scale, or do we simply attempt to understand using what seems to be in the most intuitive and apparent scale? We may be able to use technology to improve the accuracy of our models, but only to a certain point. At this point, perhaps efforts would be better spent improving the processing capacity of the technology itself, rather than attempting to use appropriate scale for phenomena, that in the end, we don’t even know is correct.
Point McPolygon