The Ticket Trap: Front to Back
propublica.org
propublica.org
"Which Ward Owes The Most?": right, poor people can't afford to pay tickets and build up debt.
"Where People Are Ticketed Most": this seemed promising. I clicked and mostly majority-white neighborhoods popped to the top. This is explained away by saying they're more congested; OK, fair enough, but try to control for that by population density? Or something? How am I supposed to read "unfair to minorities" out of that?
"How Ticket Type Varies By Ward": maybe there's something here, but this seems just as related to other factors to me as the previous point. From what I've seen in Chicago, the majority-black neighborhoods are vastly different than the majority-white neighborhoods (I feel like ProPublica would agree), so a difference in ticket type seems incredibly logical. Yet here it's not dismissed like they dismissed the previous category.
"What Happens if You Don’t Pay": right, poor people can't afford to pay tickets and it ends in a property seizure or bankruptcy.
"Who Appeals and Wins": sorting by "Percent contested and won" the minority neighborhoods fair very well, consisting of 5 of the top 8.
The conclusion that tickets are enforced in a way that manifests injustice is probably broadly true, but the data presentation actually makes it quite hard to interpret what’s “real” and what might just be an artifact of cherry picking, not to mention what slices of the data could be exhibiting something like Simpson’s paradox, etc.
I don’t think I’ve ever gotten a parking ticket for something I haven’t legitimately done wrong, they suck, but if you break the law you get a ticket. So I’m just curious is the map supposed to help us understand that the police are disproportionately ticketing in low income areas, and by that reasoning less in higher income areas ?
Just trying to understand what’s the lesson we should take away from this. Should we forgive tickets to people who are low income?
https://projects.propublica.org/chicago-tickets/
Some of the insights they pull from this data: Most tickets are issues in majority-black wards, in places with high poverty rates. Motorists in these wards were found more at risk of losing a vehicle or declaring bankruptcy. Most tickets that are contested are in more well-to-do, majority-white wards, and contested tickets have more than a 50% chance of the driver being found not liable.
Here's what I draw from this: Parking tickets frequently trap the poor into a cycle of debt. People who have money and free time have more resources available to challenge the ticket and not have to pay.
That doesn't say to me "we should forgive tickets for low income residents" but it says to me we need to find other ways to enforce the parking laws that don't just make the poor even poorer.
This is similar to what my team does with a set of about 20 computer vision and NLP web services, in an environment with fairly high web traffic (Alexa top 300 site), with a large and distributed team of engineers.
In our case several parts also involve Docker & CI such that common Makefiles are used by all parties and all config is externalized to the build and/or runtime environment.
It has worked extremely well for many years now.