Factorial Ecology With Radiocentric Explanations Factorial Ecology

¶ … Factorial Ecology With Radiocentric Explanations

Factorial ecology vs. radiocentric explanations of urban development

Currently, two popular frameworks of statistical and geographical analysis of human populations offer themselves to students of urban development and planning. According to the sociologist Carl-Gunnar Janson, one of the more popular explanations during the 1970's, regarding particular urban populations' growth and expansion, was to be found through the sociological use of factorial ecology. Factorial ecology is the statistical study of various sociological and economic data, with the attempt to determine the most probable explanations behind the chosen variables that are being studied.

Very often most of the variance in a group of dozens of the factors taken under consideration can be accounted for by three or four possible reasons. (Janson, 1980). This is not necessarily a weakness of the model, however. For instance, a factorial ecology might take into consideration the ethnicity and gender composition of a particular area to determine why a city underwent a particular 'boom' period over the course of its development. For instance, Toronto's explosion in its Asian population after the United Kingdom's agreement to cede that nation back to Chinese ownership resulted in an influx of Asian professionals into particular areas of the city. (Bunting and Filion, 2000). Variables such as first-generation vs. second-generation ancestry, Asian ethnicity, etc. could all come into factoring a factorial ecology to account for the city's professional growth during the period, and specifically in the boom of the professional-class Asian immigrant population.

In contrast, radiocentric explanations of urban development do not focus on a series of interrelated factors pertaining to sociology, but focus instead on physical or radial explanations of urban growth and development. By studying the physical landscape of the population or map, aspects of urban development may be revealed -- such as, to use the abovementioned example, Toronto's exponential growth in its Asian sector or Chinatown. Radiocentric explanations often involve a long-range simulation of a city, in a map-like structure. (Nelson, 2000)

What are the factors that predict which model is explanatory?

Toronto is a mosaic-like city of ethnic and regional composition, one reason that radiocentric explanations are fairly popular in understanding its development. As with New York, the map-like spreading out of different communities are often instructive to how certain ethnicities have become part of the nation's fabric and to what extent they participate in a city's centrality or sectors of prosperity or poverty. However, once a city grows in age and second and third generation members become more integrated and dispersed within a city's fold, radiocentric explanations become more difficult to offer, unless specific communities continue built around specific urban industries, such as the city's garment district, or, to use another example, the case of Silicon Valley and its outer-lying suburbs, where an hitherto empty area of growth becomes filled because of its location around a certain nexus of the computer industry.

What are the weaknesses of each model?

Factorial analysis of variance has come under some criticism in recent years. Its strength is that it enables sociologists to consider the effects of two or more factors simultaneously without disregarding the possible interaction between these possibly disconnected variables. These factors may not appear to be interrelated, such as an increase in a city's overall female population and poor and urban Hispanic population, for example, but may become, under analysis, more apparently connected because of the fact that, for instance, a greater number of domestic jobs have opened up in the city that are traditionally filled by such workers of a particular ethnicity and gender. Other factorial correlations may be an increase in professional-level single mothers seeking childcare that might also be connected to the growth of other populations not connected by immediate, radial geography.

Thus, the main insights of social area analysis and factorial ecology are the interconnection of apparently disconnected social rather than purely geographic variables, but there are problems in the model in that relationships between factors can be drawn that have no real connection, other than the chance correlation that one population is rising while another is declining. Also, the personal prejudices of the analyst drawing correlations between the different social factors in analyzing the different human factors present in such urban communities can come to play.

Radiocentric models may give a more coherent model as to the presence of urban communities or clustering within cities based upon geography. However, radiocentric models are not without their drawbacks either, as they do not take into consideration the difference between voluntary and involuntary social segregation and clustering in cities. (Pacione, 2001). The inability for radiocentric models to provide much understanding as to the rational and the reasoning behind physical markings for the composition of a landscape is one reason some feminist and activist sociologists suggest that, despite its flaws, urban factorial ecology provides more insight into the social problems that create the rational for the growth and composition of certain areas of cities as opposed to others.