Review 4 – Disparities

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DISPARTIES
This week I was introduced to the concept of disparities using race as an example. In the context of use, the disparity was defined as significant if the percentage of a particular race killed was higher than their percentage contribution to the population of the county they were killed in. I have embraced this approach and decided to look at age disparities and see if any counties have age disparities within any specific time periods
Examples of disparities that we can look at are: Race, age. We can assess this disparities over the whole 9-10 years or a time within that period.
lets see what we find and what it tells us when analyzed with other findings.

Review 3 – Data Analysis Start

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I am looking at Mathematica as a tool for analyzing the data through diagrams (graphs, charts, etc) and seeing if I can find any reason for these killings or at least trends that mean something substantial. Here are some of the diagrams i have in mind that might unveil meaningful trends:
* ORGANIZATION AND DATA COORDINATION (python, mathematica)
* List police county data
    * Graph of when the shootings took place (number of shootings vs time period in weeks/months)
    * Graph of where the shootings took place (number of shootings vs location)
    * Graph of police county and average number of shootings
* List population
    * County population vs police killings in county
    * Racial population composition vs police killings (Multiple lines to represent each race)
* List age
    * county population vs age group in county (histogram/barchart of each age group and their population)
* List threat
    * population of people shot who had weapons (gun, knives, other, unarmed)

Review 2 – Creating some structure

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Hello, It’s the second review and there have been some new developments.

I have been asking random questions along with other classmates, some of things which may or may not have any abnormal activity or even have enough numbers to be considered linked to the police killings. There’s only one way to find out.

I have put together a bunch of questions and classified them by group, the point of this is to see how many answers I can get to those questions and hopefully that can point me in the right direction to figuring one major question of “What is responsible for these killings or somewhat has a positive or negative impact on them?”

 

my classifications look like this:

 

 

* Any reason to believe the police officers felt threatened?
   * How many cases were there of no threat on paper
   * What police station did this situation occur most
   * What was the situation with the mentally ill that made them a threat?
   * percentage of men to women killed that were mentally ill
* Police station effect
   * What police stations accounted for most of the shootings (counties)
   * How many police stations are around each police station?
   * What percentage of the victims were armed
   * What police stations have access to body cams (are they using it?)
* Population effect
   * what was the population of people in the areas with high shootings compared to the are with low shootings
   * How is the percentage of races shot changing over time
   * What counties are body cams used more or less(which ever stands out) (area with High vs area with low)
*Age effect
   * Age group of the race shot majorly in the different areas (how it has changed over time)
   * race of Age group shot the most
* What situation has occurred the most (mentally ill, armed, fled) – Maybe there might be another factor affecting the cases that doesn’t normally stand out.

Review 1

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This week I was introduced to activity theory, at first emphasis was placed on “Rules” but as discussions went on I had the opportunity to visit the other attributes like: Subject, Object, Tools, Community, Division of Labor, and Outcome.

 

We were given access to Fatal police shootings data which contains information about Victims, Locations of the shootings, officers involved and few other relevant information. I spoke to a few classmates, and we delegated on what each entity represented, we plan to see where the analysis takes us and how much more data we can access that can help answer our questions. Some of the questions we came up with from our view of the data were:

 

  1.  What is he difference in percentages of shootings of the different races (how are the numbers changing for the races with time in the different regions)
  2. What is the cause for the different killings?
  3. Why were the individuals killed instead of contained, even in situations that may not have been dangerous for the officers.