Update README.md

README.md

@@ -9,7 +9,7 @@ This R project statistically analyzes self-reported data from the Baltimore Poli
 At its core, this is a personal attempt at civic understanding. Why are things the way they are? How can we think about an emotional issue intelligently and without fear? It is difficult to have productive conversations about crime.
 
 #### Motivation ####
-This project's goal is to better understand both crime and law enforcement. In that regard it was humbling. The largest problem I had was not technical but probably "epistemological". There is so much nuance to the data. Trying to reduce it down to generalizable categories presents a legibility problem. Is a bus depot classified as transportation, municipal, or industrial? It sounds municipal but does it make sense for a crime happening at a bus depot overnight and one in a courthouse in daylight to be classified as municipal? It's splitting hairs and agonizing. It made me think of the book [Seeing Like a State](https://en.wikipedia.org/wiki/Seeing_Like_a_State) and it's ideas of ["high modernism"](https://www.newyorker.com/magazine/2017/09/18/the-case-against-civilization). It's a common idea today to solve problems with large technical solutions. Like when Mark Zuckerberg testified in Congress and [proposed a new software system](http://calnewport.com/blog/2018/04/11/the-disturbing-high-modernism-of-silicon-valley/) to stop Facebook's already running software from being used to manipulate voters. We simply cannot solve all problems yet by writing more complicated software. [(a great discussion about it on hackernews)](https://news.ycombinator.com/item?id=16819675). So this is a response to those who propose greater software solutions to solve great societal problems. It's bold and visionary thinking, but it's reductive and dangerous too. Take this as a testament to the difficulty it. Science, statistics, and engineering sometimes need to dive into the nuance.
+This project's goal is to better understand both crime and law enforcement. In that regard it was humbling. The largest problem I had was not technical but probably "epistemological". There is so much nuance to the data. Trying to reduce it down to generalizable categories presents a legibility problem. Is a bus depot classified as transportation, municipal, or industrial? It sounds municipal but does it make sense for a crime happening at a bus depot overnight and one in a courthouse in daylight to be classified as municipal? It's splitting hairs and agonizing. It made me think of the book [Seeing Like a State](https://en.wikipedia.org/wiki/Seeing_Like_a_State) and it's ideas of ["high modernism"](https://www.newyorker.com/magazine/2017/09/18/the-case-against-civilization). High modernism is ["unfaltering confidence in science and technology as means to reorder the social and natural world"](https://en.wikipedia.org/wiki/High_modernism). It's a mantra that Silicon Valley and the Soviet Union both embody. It's a common idea today to solve problems with large technical solutions. Like when Mark Zuckerberg testified in Congress and [proposed a new software system](http://calnewport.com/blog/2018/04/11/the-disturbing-high-modernism-of-silicon-valley/) to stop Facebook's already running software from being used to manipulate voters. We simply cannot solve all problems yet by writing more complicated software. [(a great discussion about it on hackernews)](https://news.ycombinator.com/item?id=16819675). So this is a response to those who propose greater software solutions to solve great societal problems. It's bold and visionary thinking, but it's reductive and dangerous too. Take this as a testament to the difficulty it. Science, statistics, and engineering sometimes need to dive into the nuance.
 
 There are too many ways of thinking about law enforcement. It can be analyzed through the lenses of communal, societal, or familial structure. An aproachable angle for a data scientist is to examine crime as an intelligence problem. What can be learned? And what actions can be done from that knowledge?