Chapter 6, from Great America City, was one of the more enjoyable chapters that I've read from this book. This is likely due to the fact that I happen to have more background knowledge on the "Broken Windows Theory." Because of this, it was easier for me to follow along and understand what Sampson was talking about, which was a nice change.
In this chapter, it quickly becomes apparent that Sampson doesn't subscribe (at least not completely) to the theory of "Broken Windows". However, it takes a while to understand his reasoning. I personally had embraced this theory before reading the chapter, so at first, I was reluctant to throw it out.
Sampson argues that it's not so much disorder itself that is the main causal factor for public issues such as crime. Instead, Sampson suggests that its the appearance of disorder that plays a more crucial role. It is in this idea of the perception of disorder, in which Sampson places his thesis. His thesis proposes that "perceptions of disorder constitute a fundamental dimension of social inequality at the neighborhood level and perhaps larger areas."
As the chapter continues, Sampson begins to back up his thesis with buckets of data. For me, I found the data illustrated in figures 6.4 and 6.6 to be especially interesting. Figure 6.4 shows the differences in perceived disorder from black vs whites and immigrants in neighborhoods of varying race ratios. I was surprised to learn that perceived disorder increases with increased ratios of black or immigrant within a neighborhood, across the spectrum. Sampson's research reveals that blacks and immigrants also perceive higher levels of disorder in neighborhoods that have more immigrants or black individuals. I would not have expected such a blatant portrayal of inequality in a modern America city such as Chicago.
In figure 6.6, Sampson illustrates how socially perceived disorder can accurately predict later poverty on the community level. The graph clearly demonstrates the legitimacy of perceived disorder within local communities. Prior to reading this chapter, I never would have thought that perception could have such a powerful impact on social issues.
After finishing this chapter, I searched Google for an article on the subject, and found an article titled, Can You Tell How Dangerous A Neighborhood Is From Just A Picture?. The article explains a fascinating research project currently being done involving Google Maps. César A. Hidalgo from MIT has created a web tool that shows users various images of New York neighborhoods (taken from Google Maps). The tool compares images of different neighborhoods while asking users questions that reveal the users perception of the pictures shown. In some ways, the research being compiled by this program brings validity to the broken windows theory. The author of the article explains:
"Hidalgo’s team actually found a strong correlation between incidence of violent crime and perceptions of danger based on visual cues, which could support BWT, or perhaps the inverse--that people avoid unattractive neighborhoods, making them unsafe. 'There’s not a unique explanation of the correlation that will serve,' Hidalgo explains. 'Both explanations are perfectly reasonable. There could be a third variable that is causing this correlation,' he adds."
In a way, Hidalgo's research supports Sampson's theory and the broken windows theory at the same time. I also like how he suggests that there could be a third variable causing the correlation. I'm interested to see how this research will develop and how it might support or influence future research for Sampson.
Finally, I consider my major emphasis, Biology and Sociology and how they can relate to this research. In this chapter I was able to make clear connections to both. Making the connection to Sociology is relatively easy since most of the issues being studied are social issues. Although I don't fully comprehend all of the reading, I feel like Sampson's research is a good intro into sociology for me. It's fascinating to see how the cohesion of different communities affect surrounding neighborhoods as a whole. It's more difficult for me to relate biology to these issues, but when I consider the connections a community shares, it becomes a little easier. Perhaps the evolution of communities can be compared to the evolution of species, where the best characteristics will produce the most beneficial results. Sampson hints towards the end of this chapter that collective efficacy could be one of these beneficial characteristic.
