
The Ticket Trap: Front to Back - danso
https://www.propublica.org/nerds/the-ticket-trap-news-app-front-to-back-david-eads-propublica-illinois
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_Codemonkeyism
"We decided against showing trends over time on ward pages because the overall
trend in the number of tickets issued is too big and complex [...] it would
have been outside the journalistic goals of highlighting systemic injustices."

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arcticfox
I appreciate the goals of this project, but IMO they aren't being very
rigorous about it, and really only arrive at the conclusion that "more blacks
are poor, and tickets hit poor people very hard", which I think anyone would
already agree with before this study. I don't really understand what the ward
breakdown adds.

"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.

~~~
IOT_Apprentice
Perhaps to call out the politicians who could do something about the preying
on the poorer areas?

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everybodyknows
The project would smell sweeter if the top page of the app weren't hitting
facebook.net --

[https://projects.propublica.org/chicago-
tickets/](https://projects.propublica.org/chicago-tickets/)

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Simulacra
It’s interesting that Low income people are the ones disproportionally hit by
the number of tickets, but I guess the question that needs answering is: are
they in fact breaking the law?

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?

~~~
4werfaw34r
I don't think that's what they are trying to say at all:

[https://projects.propublica.org/chicago-
tickets/](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.

~~~
c22
Tickets should be adjusted for income. If someone making $200,000 a year has
to pay $50 for parking in the wrong place then someone who makes $20,000
should have to pay $5.

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mlthoughts2018
Microservices and using Make to wrap their chosen build tooling - I love it!

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.

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dstroot
I have always enjoyed articles like this that clearly explain the problem they
are trying to solve, why they are solving it, and how they are solving it all
the way down to the tech stack (which is the most interesting bits along with
UI design for me). Worth the read time.

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everybodyknows
Propublica list of data sets, some offering free download:

[https://www.propublica.org/datastore/datasets](https://www.propublica.org/datastore/datasets)

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_Codemonkeyism
What made me wonder: Single developer setting up app with a bunch of
microservices in the backend claiming low maintenance, would really be
interested in an evaluation 2y in the future.

