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that are difficult to locate. Similarly, the health and environmental information
literatures have acknowledged differences in information acquisition and issue-
specific attitudes across rural to urban gradients (Morrone and Meredith 2003 ) and
proximity to relevant features like rivers and lakes in the biophysical environment
(Larson and Santelmann 2008 ; Brody et al. 2002 ). These literatures have also noted
that information use and pro-environmental attitudes tend to correlate negatively
with the degree to which an individual identifies with commonly marginalized
groups (racial, ethnic, and cultural minorities, low socioeconomic status, and low
educational attainment).
3.3 Objective
This research develops a method to assess the likelihood that the public encounters
public information given that (a) there are differences in record keeping systems
and standards across organizations and (b) public information that is provided
through different mechanisms may have different impacts.
3.4 PGIS Case Study
Through interviews and surveys (described in Cutts et al. 2008 ), water information
providers expressed an interest in understanding the spatial patterns of effort to
inform the public to water about water issues in metropolitan Phoenix, Arizona.
The process described here is an aim to quantify the differences in the public's
exposure to these programs over the course of a year. The aim is to test the hypo-
thesis that the effort organizations make to inform the public about water issues
varies across the metropolitan Phoenix. The prediction is that regions characterized
by populations typified as less engaged in environmental issues in studies of
individual environmental attitudes will be less likely to live in regions of the city
with a lot of locally available information so that: (1) the percent of the population
that is Latino/a will be higher in regions with low information availability, (2) the
percent of the population that rents their homes (a proxy for income that is not highly
correlated with ethnicity in Phoenix) will be higher in regions with low information
availability, (3) the larger the population of school-aged children, the greater the
likelihood that the region will have high amounts of water information, and (4)
the relationship between the variables above may vary across regional geographic
identities of the East Valley, West Valley, and Phoenix (see Fig. 3.1 ). These
predictions are derived from the expressed perceptions of water information
providers about the characteristics of program users. In this paper however,
I focus more specifically on the process and methods used to create the data set.
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