Last summer, we set out to find out how much cities spend on settlements for police misconduct -- bills often footed by taxpayers.

We got data from 31 cities. We also found that the data is basically impossible to compare across time or city.
Cities don't track this money in a straightforward, comparable way. Indeed, some don't seem to track it at all.
The data is in no way standardized. Some cities provided no description of what each settlement was for. Other provided categories -- but those categories differed wildly. Even when they had the same name ('civil rights'), we couldn't assume it meant the same thing.
Cities also differed wildly in the number of settlements and how costly each settlement was. But again, it was hard to know what to make of those differences.
Fundamentally, so many factors affect whether lawsuits are even filed -- and whether cities decide to settle -- that it's unclear whether high totals are a bad thing (more police misconduct) or a good thing (victims being more likely to get compensated).
The bottom line: Unless cities do a better job collecting this kind of data -- in some cases, any kind of job, frankly -- it's incredibly hard to hold departments accountable for the misconduct that they perpetrate.
So grateful to @ameliatd, @sharmad23, @mayasweedler, @jazzmyth, @LikhithaBu, @eads and many others at @FiveThirtyEight and @MarshallProj for the months and months of data munging, head scratching, and cryptic conversations with city officials that went into this!
We made a conscious decision *not* to adjust for the size of the city or the police force because we didn't want to make the data seem more comparable than it is. There are many reasons this isn't an apples-to-apples comparison!

And with a fashionably late arrival, here's all the data!

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More from @laurabronner

22 Feb
All the data behind our article on police misconduct settlements ( is now public on Github! Our main aim here was to make everything we received in response to our FOIAs available to others:… ImageImage
But we want to encourage responsible use of this data! It's *not* comparable across cities, which is why we're not providing it as an easy-to-use, pre-compiled data set. We want you to use it -- but we want you to read about its idiosyncrasies first! Image
We're making public all the original data the cities gave us, as well as all the cleaning/munging/filtering we did to make it as usable as we could. ImageImageImage
Read 6 tweets
16 Dec 20
The suburbs shifted to the Democrats, and they also got more diverse. Is the story that simple? @geoffreyvs, @elena___mejia, @ameliatd and I find that education makes the story more complicated.
The biggest shift towards Biden was in suburban counties that became *both* more diverse *and* more educated over the past decade -- a lot of the GA suburbs fall into this category.
But for counties where increased diversity and education *didn't* go together, the Democratic swing was bigger in places that became more educated but not more diverse, than in places that became more diverse but not more educated.
Read 5 tweets
12 Nov 20
Where we saw red and blue mirages -- or, as I wanted to headline it, "Election Night was a marshmallow test for the country, and we failed".

@wiederkehra, @baseballot and I look at vote counts 1.5, 12 and 72 hours after polls closed in each state:
In some states, generally those where absentee votes were processed before Election Day, the race looked competitive after 90 minutes, only for Election Day ballots to conclusively put Trump in the lead. (Missouri and Montana are also in this category.)
In other states, generally those where absentee ballots were counted after the election, what appeared like an early lead for Trump disappeared as more ballots were counted, like in Michigan, which was unable to process ballots before election week.
Read 5 tweets
31 Oct 20
Four reasons Biden has a better shot than Clinton did in 2016 -- and 2 reasons there's still uncertainty.
A summary 🧵:

1. Biden's lead is bigger and more stable than Clinton's was.

Clinton's lead was smaller throughout, and more unstable. Biden's has never been < 6.6 points.
2. There are fewer undecideds than 2016.

A week before the 2016 election, around 14% of respondents said they were undecided or intended to vote third party -- and the vast majority of late deciders voted for Trump:

This year, there are much fewer.
3. State polls have improved.

In 2016, it was state polls that had polling errors, in part because they hadn't needed to weight by education before (…). But polls have improved (, and there are more state polls now.
Read 8 tweets
31 Oct 20
Vier Gründe, wieso es 2020 um Biden besser steht als 2016 um Clinton -- und zwei Gründe, wieso es trotzdem noch viel Unsicherheit gibt, heute im @derStandardat:…
1. Bidens Vorsprung ist größer und stabiler als jener Clintons.

Clintons Vorsprung war durchgehend kleiner und schrumpfte zeitweise auf einen Prozentpunkt; Bidens lag nie unter 6.6 Punkten.
2. Es gibt weniger unentschlossene Wähler als 2016.

Eine Woche vor der Wahl 2016 gab es rund 14% Unentschlossene/Kleinparteienwähler -- und Trump konnte bei genau bei Wählern, die sich spät entschieden, punkten:…

Diesmal gibt es nur 5% Unentschlossene.
Read 9 tweets
30 Oct 20
Why is turnout among young Americans so low? @ameliatd, @jazzmyth and I find that while people under 35 *are* more skeptical of the system, they're not apathetic. Instead, they're more likely to face structural barriers like not being able to get off work
(+ bonus charts!) How do we know young people aren't more apathetic? Well, they're not significantly more likely to say they don't vote because the system is too broken, or because they don't believe in voting. But they *are* more likely to say they wanted to vote, but couldn't.
In fact, if anything, young people are *less* likely to say that they don't vote because nothing will change for people like them no matter who wins!
Read 7 tweets

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