Questions we could ask of the data

[alexsoble]

Right now we're busy scraping, cleaning, appending, merging, and double-checking data. @yahwes and @DGalt and @banoonoo2 have made enormous progress on this over the past week.

Once the data is in a highly usable and double checked form, we can start asking it questions. Here are a couple that @ithinkidunno and I started brainstorming on Friday. Please add your own to this thread.

Questions for the data

• What patterns do we notice in terms of the officers most frequently associated with each category (involved / accused)?
• Do we see any patterns in terms of officer age and rank?
• How are the incidents distributed across the city? (Geocode every incident on a map)
• Do we see different patterns for victims of different races when it comes to initial category vs. current category?
• Do we see different patterns for victims of different races when it comes to change in outcome (“finding code”)?
• Do we see different patterns for victims of different races when it comes to length of investigation?
• What does the data have to say, if anything, about the highest-ranking CPD officers?

[alexsoble]

Oh and depending on what we find, the answers to these questions could be visual as well as text.

[banoonoo2]

I'd like to explore the social networks and command hierarchy that correlate with more complaints. Are there people who are frequently on-scene or behind-the-scenes on interactions that result in complaints? Do they also get complaints against them? Or does their involvement go unnoticed?

We could ask the current data:

• What are the units with the most complaints?
• What are the beats with the most complaints?

The first 2 digits in the beat number are the district number, and then the districts are organized into 3 areas (see http://gis.chicagopolice.org/pdfs/district_beat.pdf), so also:

• What are the districts with the most complaints?
• Which area has the most complaints?

At some point, I'd like to manually capture/confirm data from the June 3 PDFs, which would give us other officers on scene, supervisor on scene, watch/unit commander, reviewing supervisor, and approving supervisor. This would let us look at individuals and see if their presence in a unit correlated with more complaints. This would also be amenable to a network graph like @rajivsinclair posted on June 4.

[alexsoble]

These are fantastic questions and ideas @banoonoo2!

[herdingbats]

Correlations and risk factors for police complaints that we can compare/look at (based on time and place):

• weather
• crime (do police incidents rise in response to increases in crime?) Obviously reporting is confounded.
• density of patrol? if a neighborhood is saturated, do officers feel less vulnerable?
• are there any directives coming out to precincts? ("We want to focus on enforcing ___")
• paydays/other regular professional events in police calendar?
• locations by type: public/private.

[evanwsun]

Some of the stuff we brainstormed from last night: Gender roles, mob mentality (correlation between shootings and groups of officers?) and possibly looking to see if there's any trend over the months

[banoonoo2]

Answering another data question, I came across 2 cases where CPD fatally shot someone. One was a home invasion. The other was a stop-and-frisk.

I'd like to know:

• How many incidents (and as a subset, shootings) arise from CPD being called?
• How many incidents (and as a subset, shootings) are initiated by CPD (stop-and-frisk, traffic stop)?
• What is the frequency of various crimes the subjects are alleged to have committed? (How many armed robberies? How many objects dangling from rearview mirrors?) (Would need to discount high numbers of "resisting arrest.")
• What is the frequency of no crimes being listed in the OCIR?