Voter Migration and the Geographic Sorting of the American Electorate

This study shows that party ID voters relocate based on destination characteristics and constraints but also prefer to locate to destinations with people who share their political party’s ideology. While aiming to address the corresponding migration of individuals with locations that fit their political preferences the authors do take to consideration that geographic patterns may occur due to social processes and environments. They also note that relocation decisions are usually and primarily made due to constrained choices which are usually economic. However, if there is a desire for individuals to move to places that suit them socially and economically then the same can go for politically.
The authors find that 30% of those surveyed in their data take partisanship to be an important factor to their desired place of living. Liberal residential settings are typically urban, whereas conservatives prefer suburban and rural areas. For example, democrats are found to prefer densely populated areas more than Republicans.
According to the article republicans tend to sort rather than mix where as democrats don’t mind mixing, sometimes democrats will relocate to areas that are more conservative than their origin but this is probably because the most democratic locations are in big cities that have several social problems. The same negative features can go to the most republican places as well which are rural and have limited employment opportunities. Republicans prefer moving to more republican locations which keeps increasing the further the distance is. On the other hand Democrats can have similar preferences as republicans except their preferences are not as strong as the preferences republicans have. This can be seen in figure 1 which shows the migration in and from Portland, Oregon.

Cho, W. K., Gimpel, J. G., & Hui, I. S. (2013). Voter Migration and the Geographic Sorting of the American Electorate. Annals of the Association of American Geographers, 103(4), 856-870. doi:10.1080/00045608.2012.720229

A GIS-based spatial analysis on neighborhood effects and voter turn-out: a case study in College Station, Texas

This article explores the relationship between the individual voter turn outs and the city district's voting outcomes. Particularly the authors who conducted the study wanted to answer their question on whether the neighborhood effect influences the individual voter turnout in local politics. It is important to note that the key subject word "neighborhood effect" in the article is defined as where social interaction within residential communities affects people's voting choices and behaviors.
In pursuing their case study the authors choose College Station as a sample because the city's voting districts are fairly close to neighborhood communities. The authors concluded that the neighborhood effect is heavily influenced by the distribution of voters and that the neighborhood effect is related to the issues and the publicity of the issues.
To obtain their results the GIS based spatial analysis and the address matching tools mapped individual voter distribution and voting results at the local level for referendums. Arc GIS's Ripley K function and Getis-Ord's GI* was able to find the relationship between the distribution of actual voter turn-out and the neighborhood effect.
In figure 1 each point represents an individual voter and the positive z values signal high spatial clustering where as negative z values show low spatial clustering. Figure 1 shows the spatial distribution of the actual voter turn out done through the use of address matching and voting results in the local political level. The authors remarked that the neighborhood effects had a clear impact on voter turn out especially on a controversial issue that is important to voters.

This study proves that people who talk together vote together; in other words inter-personal communications and organizationally based interactions are part of the neighborhood effect which influences voting behavior. The study shows that the voter turn out’s spatial distribution influences the geographic patterns seen in voting results.

Sui, D. Z., & Hugill, P. J. (2002). A GIS-based spatial analysis on neighborhood effects and voter turn-out: a case study in College Station, Texas. Political Geography, 21(2), 159-173. doi:https://doi.org/10.1016/S0962-6298(01)00054-3

New York City: GIS Measures and Field Observation

This article maps out certain criteria that effect the lives of residents of New York, New York. The disparity the article focuses on is chronic disease related to lack of physical activity in poor neighborhoods of New York and non poor neighborhoods. 
It is true that the low-income neighborhoods of New York would be predisposed to physical activity because of their walkability, a phrase which here refers to intersecting factors such as land-use mix, and high population density). Yet, these opportunities for physical activity are not utilized because they are complicated by further economic disparities such as high crime rates, and lack of aesthetic appeal. It is difficult to decide if the the authors' conclusion would best be described as oblivious or hackneyed: that in order for low-income residents to utilize the walkability their neighborhoods , the architecture must be made more aesthetically pleasing, and crime must be reduced. Upon a cursory reading of this article, the authors' methods may seem straightforward and logical. When looked at on a more macro scale, however, reading the article becomes uncomfortable. That lack of physical activity despite walkability was the central issue seemed simple enough. Yet, the factors leading to lack of physical activity were not plugged into the greater socio-economic contect. To phrasing of the article makes the lack of physical activity in low-income neighborhoods of New York appears to prioritize physical activity, or lack-there-of, over the factors which caused it. Crime rates in low-income neighborhoods are often high, in part due to racial-biases embedded in law enforcement. I have often found that the aesthetics of high-income neighborhoods are often high quality due to scenarios such as: a corrupt city council members take donations from wealthy residents, and therefore delegate more of the city's funds to fixing the roads of wealthy streets, or creating historical markers.
In summation, the authors' attempt at mapping out a way to benefit impoverished New Yorkers was not successful. I do not know that such an attempt could be successful without treating racism and classicism with proportionate gravity.








Neckerman, K. M., Lovasi, G. S., Davies, S., Purciel, M., Quinn, J., Feder, E., ... & Rundle, A. (2009). Disparities in urban neighborhood conditions: evidence from GIS measures and field observation in New York City. Journal of Public Health Policy, 30(1), S264-S285.