WEBVTT - Crime Trends vs. Statistics – and Reality

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<v Speaker 1>Welcome to Crash Course, a podcast about business, political, and

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<v Speaker 1>social disruption and what we can learn from it. I'm

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<v Speaker 1>Tim O'Brien. Today's crash Course crime trends versus statistics and reality.

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<v Speaker 1>After many years of reassuring declines, some crime rates soared

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<v Speaker 1>nationwide during the COVID nineteen pandemic. Homicides jumped about thirty

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<v Speaker 1>percent in twenty twenty compared to the prior year, and

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<v Speaker 1>violent assaults rose by more than ten percent. According to

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<v Speaker 1>a number of different groups that track the data, these

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<v Speaker 1>trends weren't geographically or politically specific. Residents in cities, suburbs,

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<v Speaker 1>and rural areas all suffered through that shift, and it

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<v Speaker 1>didn't matter if they lived in a city run by

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<v Speaker 1>a Democrat or a Republican. More murders, the data showed,

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<v Speaker 1>plagued every urban area. On the other hand, robberies, burglaries,

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<v Speaker 1>and larcenies dropped during the pandemics onset. As the pandemic,

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<v Speaker 1>war on murder rates andolent crime rates overall settled down,

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<v Speaker 1>the numbers rose, but not nearly as sharply as they

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<v Speaker 1>did early on. Another wrinkle, crime statistics are subject to

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<v Speaker 1>spotty methodology and reporting gaps, making it hard to rely

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<v Speaker 1>on the data with absolute certainty. Public safety isn't a

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<v Speaker 1>trivial topic, and there's no question that many Americans say

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<v Speaker 1>they feel less safe on some streets than they once did,

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<v Speaker 1>despite the fact that violent crime rates are well below

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<v Speaker 1>where they were during the nineteen nineties. So what was

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<v Speaker 1>behind the pandemic surge and murders and assaults and what

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<v Speaker 1>lessons can residents and public officials draw from what happened.

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<v Speaker 1>Joining us today to chat about all of this is

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<v Speaker 1>Ames Growert, a lawyer and expert on crime statistics at

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<v Speaker 1>the Brennan Center for Justice at the NYU Law School.

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<v Speaker 1>The Brennan Center is a nonprofit focused on a number

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<v Speaker 1>of legal and public policy issues, including research into the

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<v Speaker 1>sources of violent crime. Welcome, Ames, Thank.

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<v Speaker 2>You so much for having me. It's a pleasure to

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<v Speaker 2>be here.

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<v Speaker 1>So set the stage alone a little bit for us. First,

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<v Speaker 1>tell us a little bit about the work you do

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<v Speaker 1>at the Brennan Center and how the Brennan Center intersects

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<v Speaker 1>with crime research and crime statistics.

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<v Speaker 2>Absolutely so. Our theory of criminal justice reform is that

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<v Speaker 2>we can have a country that is both safer and fairer,

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<v Speaker 2>that we can has common sense criminal justice reform policies

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<v Speaker 2>that lead to a justice system that is fairer to

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<v Speaker 2>all who are impacted by it. That's including people who

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<v Speaker 2>are victims of crime as well as people accused of crime,

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<v Speaker 2>and that while doing so, we can also have a

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<v Speaker 2>safer country. As a whole. Part and parcel of that

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<v Speaker 2>research is trying to understand what's actually happening when it

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<v Speaker 2>comes to crime trends around the country. So around eight

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<v Speaker 2>years ago, some colleagues before I joined the Brendan Center

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<v Speaker 2>actually released a report called What Caused the Crime de Client.

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<v Speaker 2>This is sort of the origin of this work, but

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<v Speaker 2>it's also very much still relevant to the work we

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<v Speaker 2>do today. They're thinking was, we need to understand the

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<v Speaker 2>huge drop off and crime rates that happened between nineteen

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<v Speaker 2>ninety one and roughly twenty fourteen. Over that course of time,

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<v Speaker 2>murder rates in the United States the drops of half.

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<v Speaker 2>Some sociologists call this the Great Crime Decline. It's a

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<v Speaker 2>rarely remarked upon but incredibly important social phenomenon. So they

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<v Speaker 2>set out to figure out, you know, why what happened.

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<v Speaker 2>They came to a couple conclusions, one of which is

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<v Speaker 2>it's very difficult to untact something that complicated, but a

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<v Speaker 2>couple of their findings were that improving economic conditions partially

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<v Speaker 2>helped explain drops in crime nationwide, and that incarceration was

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<v Speaker 2>not as powerful an explanation as some had expected. So

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<v Speaker 2>that was the genesis of this work, an idea that

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<v Speaker 2>we need to you know, understand what's really happening with

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<v Speaker 2>crime trends across the country, and that you know, we

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<v Speaker 2>continue to this day to monitor what's happening around the country,

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<v Speaker 2>keep abreast of the very best research, and contribute our

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<v Speaker 2>own where we can well.

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<v Speaker 1>And socioeconomic factors play into our understanding what happened during

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<v Speaker 1>the pandemic too, So let's get into that a little bit.

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<v Speaker 1>What happened in the early stages of the pandemic, particularly

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<v Speaker 1>twenty twenty, that caused homicides and violent crimes to spike.

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<v Speaker 2>Yeah, just to give you a bit of context, I

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<v Speaker 2>know you touched on at the top of the show,

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<v Speaker 2>but the key statistics are we saw the national murder

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<v Speaker 2>rate increase by about thirty percent year every year from

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<v Speaker 2>twenty nineteen to twenty twenty. We saw assault increase by

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<v Speaker 2>around ten percent or so, you know, that's a significant

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<v Speaker 2>increase in violence. And I think, much like we don't

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<v Speaker 2>have a complete answer as to, you know, why crime

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<v Speaker 2>dropped so precipitously between you know, the early nineteen nineties

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<v Speaker 2>and today. We don't yet have and may not have

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<v Speaker 2>for a long time, a full accounting of what happened

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<v Speaker 2>during the COVID nineteen pandemic. When my colleagues and I

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<v Speaker 2>investigated this to try to figure out, you know, what

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<v Speaker 2>could explain such a dramatic increase in violence concentrated in

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<v Speaker 2>such a short period of time. We can do a

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<v Speaker 2>couple explanations, but we've always been careful, and I just

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<v Speaker 2>want to re emphasize to your listeners too, that this

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<v Speaker 2>isn't the full accounting. We're not saying, you know, these

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<v Speaker 2>are the factors that one hundred percent explained everything that

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<v Speaker 2>happened since twenty nineteen. I don't know who'll ever get there,

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<v Speaker 2>but a couple of those factors were Number one, increasing

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<v Speaker 2>access to firearms and increasing carrying and use of them.

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<v Speaker 2>And I can go into that at greater length. It's

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<v Speaker 2>really interesting.

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<v Speaker 1>So, surprise, surprise, more guns on the street produce more

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<v Speaker 1>violence against other people. That's about right, I'm shocked to

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<v Speaker 1>discover that.

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<v Speaker 2>You know, so often we look for counterintuitive findings, but

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<v Speaker 2>this just feels very intuitive. It's sometimes these sort of

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<v Speaker 2>explanations that resonate with us. It's just common sense. There

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<v Speaker 2>actually is research back into it, and people can push

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<v Speaker 2>back and say, you know, well, it's true that more

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<v Speaker 2>guns is an mulos equal more crime. A lot of

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<v Speaker 2>second and third guns are bought by collectors, but in

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<v Speaker 2>the pandemic, we actually did see a sort of closer

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<v Speaker 2>link at least between more guns more crime.

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<v Speaker 1>There had been years of a surge on guns on

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<v Speaker 1>the streets that also corresponded with a drop in homicides

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<v Speaker 1>and violent crimes. So even there, the link is not

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<v Speaker 1>entirely direct, right, It's.

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<v Speaker 2>Very complicated yet. So one of the pandemic ara statistics

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<v Speaker 2>we look at is something that the ATF refers to

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<v Speaker 2>as time to crime. What that means is when a

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<v Speaker 2>gun is recovered from a crime scene, how long ago

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<v Speaker 2>was it lawfully purchased. So it's sort of the time

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<v Speaker 2>between when a gun enters the market legally and when

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<v Speaker 2>it turns up at a crime scene. Time to crime

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<v Speaker 2>actually dropped during the first two years of the COVID

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<v Speaker 2>nineteen pandemic that suggests there's sort of a closer link

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<v Speaker 2>between gun purchases and guns being used unlawfully. But frankly,

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<v Speaker 2>this is an area where we need more research to

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<v Speaker 2>understand better the link between gun purchases and gun violence.

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<v Speaker 1>Were there other factors in addition to availability to firearms?

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<v Speaker 1>Access to firearms?

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<v Speaker 2>Yes, So this is a tough one. I think. You know,

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<v Speaker 2>when you talk to some people, they will give you

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<v Speaker 2>a very strong case of this argument, and I'm going

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<v Speaker 2>to give you the sort of middle way case of

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<v Speaker 2>the argument, that is that the social disruption caused by

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<v Speaker 2>the COVID nineteen pandemic had some effect on crime trends,

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<v Speaker 2>and especially violent crime. This is a tough one because

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<v Speaker 2>I don't know if we'll ever be able to fully

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<v Speaker 2>quantify exactly how this relationship played out, What happened, What's

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<v Speaker 2>the mechanism that explains the link between the onset of

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<v Speaker 2>the pandemic and violent crime. We might not ever have

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<v Speaker 2>a full understanding of that, but a couple of mechanisms

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<v Speaker 2>that we're sort of thinking through are this. When we

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<v Speaker 2>saw the pandemic begin, the government response was not immediately

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<v Speaker 2>adequate and not immediately encouraging. So a lot of people

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<v Speaker 2>and people that we talked to in communities affected by

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<v Speaker 2>violence said that members of their community lost faith in

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<v Speaker 2>the government, didn't believe that their institutions were there to

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<v Speaker 2>keep them safe. At the same time, a lot of

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<v Speaker 2>basic parts of the community fabric, like libraries, third places

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<v Speaker 2>so called where people can congregate after work or on

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<v Speaker 2>the weekends, those shut down or inaccessible programs like community

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<v Speaker 2>violence intervention initiatives, which are programs run by people at

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<v Speaker 2>street level to help stop violence, support starts. Those sor

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<v Speaker 2>programs often have to be run face to face, and

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<v Speaker 2>you can't do that during a respiratory pandemic. That's just

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<v Speaker 2>not how it works. So all these factors that sort

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<v Speaker 2>of work together in the background almost to keep communities safe,

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<v Speaker 2>all of them sort of fell apart at once, And

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<v Speaker 2>it would almost be surprising if that had no effects.

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<v Speaker 2>The question that we ask, and I think researchers need

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<v Speaker 2>to continue to ask, is what sort of effect did

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<v Speaker 2>it have? What was the magnitude of that effect?

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<v Speaker 1>So it would all be under the umbrella of people

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<v Speaker 1>freaked out, it.

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<v Speaker 2>Would be more into the umbrella of once in a

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<v Speaker 2>generation pandemic having untold, difficult to quantify, difficult to really

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<v Speaker 2>fully appreciate, effects on the social fabric and the sort

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<v Speaker 2>of informal ties that keep the communities safe.

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<v Speaker 1>Yeah, people certainly had existential dread. People were reaching out

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<v Speaker 1>to connect to one another more, and it was uncertain

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<v Speaker 1>what the pandemic's effects would be. It's interesting to me

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<v Speaker 1>to contemplate that. Then another stage and thinking was lashing

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<v Speaker 1>out against other people, you know, either with guns or hands.

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<v Speaker 1>Yet another statistic in all of that, though, is interesting

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<v Speaker 1>to me, is that auto thefts also jumped. So in

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<v Speaker 1>addition to, you know, you had certain kinds of crime

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<v Speaker 1>to decline, and then you had homicides and assaults jump,

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<v Speaker 1>but auto thefts jumped too. What are you thinking about that?

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<v Speaker 1>That's a category to me that's sort of intriguing.

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<v Speaker 2>Yeah, this is a really interesting one. One way to

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<v Speaker 2>think about what happened during the COVID nineteen pandemic is

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<v Speaker 2>how does the onset of a major respiratory virus affect

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<v Speaker 2>someone's opportunity to commit a type of crime. So retail

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<v Speaker 2>thefts tended to drop during the COVID nineteen pandemics. People

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<v Speaker 2>simply weren't going to stores but at the same time,

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<v Speaker 2>you know, you might not have eyes on your car

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<v Speaker 2>that you parked up the street a couple of weeks

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<v Speaker 2>ago because you haven't left your house. That's one factor

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<v Speaker 2>that might partially explain increasing motor vehicle thefts. But there

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<v Speaker 2>are a couple others too. One and this comes from

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<v Speaker 2>a conversation I had with Jeff Asher, who's a fantastic

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<v Speaker 2>analyst of crime trends. He pointed out that motor vehicle

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<v Speaker 2>thefts tend to go hand in hand with more serious

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<v Speaker 2>forms of violence. So, you know, a car is stolen

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<v Speaker 2>and then used in a drive by shooting, so it's

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<v Speaker 2>possible that, you know, you would see that type of

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<v Speaker 2>offense increase alongside murder, which is what we in fact

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<v Speaker 2>saw during the COVID nineteen pandemic. More recently, there have

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<v Speaker 2>been security vulnerabilities discovered and a couple of vehicle brands,

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<v Speaker 2>and there have been videos and stuff.

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<v Speaker 1>So glad you're bringing this up. You're getting to the

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<v Speaker 1>TikTok video. Yeah, part of the argument. Excellent.

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<v Speaker 2>Yeah, there's a social media video explaining how easy it

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<v Speaker 2>is to short circuit the security defenses of some vehicles.

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<v Speaker 1>And specifically kias and Hyundais.

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<v Speaker 2>I believe, Yeah, I believe that's right. And I can't

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<v Speaker 2>tell you that that explains, you know, fifty percent or

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<v Speaker 2>whatever percent of the increase in motor vehicle thefts, but

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<v Speaker 2>it's not trivial. I think that that sort of effect

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<v Speaker 2>of not just opportunity but means becoming more available might

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<v Speaker 2>help explain the increase in those offenses as well.

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<v Speaker 1>So all of the reasons you're giving for why the

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<v Speaker 1>numbers jumped, both in these separate categories which can be

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<v Speaker 1>caused by unrelated factors, and then some of the ones

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<v Speaker 1>that are caused by related factors, none of these are

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<v Speaker 1>necessarily the reasons that captured the public's imagination as to

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<v Speaker 1>why homicides and violent crime were rising in year one

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<v Speaker 1>of COVID nineteen. Tell me about that. What were the

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<v Speaker 1>reasons that many people latched onto for why this was happening.

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<v Speaker 2>Yeah, that's the key question. One of the frustrating things

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<v Speaker 2>about working on crime research and trying to understand the

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<v Speaker 2>way the criminal justice system works is it's easier to

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<v Speaker 2>disprove some theories than it is to proved them. That's

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<v Speaker 2>because the data are very hard to come by sometimes,

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<v Speaker 2>But when you have a concrete idea. Sometimes you can

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<v Speaker 2>gather the data you need to actually test the theory,

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<v Speaker 2>and that's what my colleagues and I have done in

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<v Speaker 2>some cases, and researchers around the country have done in others.

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<v Speaker 2>And I'll get to exactly what the data show in

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<v Speaker 2>a minute. But one of the most popular theories about,

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<v Speaker 2>you know, why crime rose, especially in New York City,

0:11:01.200 --> 0:11:04.840
<v Speaker 2>was bail reform. This was a major initiative enacted in

0:11:04.880 --> 0:11:07.439
<v Speaker 2>twenty twenty that changed the way the state's pre trailer

0:11:07.440 --> 0:11:11.200
<v Speaker 2>released laws worked, so detension bail were largely taken off

0:11:11.240 --> 0:11:13.880
<v Speaker 2>the table for our misdemeanors in some lower level felonies.

0:11:14.240 --> 0:11:17.160
<v Speaker 2>People jumped to the conclusion very quickly that bail reform

0:11:17.240 --> 0:11:19.880
<v Speaker 2>might explain rising crime in New York City. But when

0:11:19.920 --> 0:11:21.960
<v Speaker 2>you really kick the tires of that data, it just

0:11:22.160 --> 0:11:24.480
<v Speaker 2>doesn't add up. For one, as you know, as we've

0:11:24.520 --> 0:11:27.360
<v Speaker 2>been discussing folent crime and murders rose around the country,

0:11:27.400 --> 0:11:29.480
<v Speaker 2>it would be very odd, indeed, if bail reform in

0:11:29.520 --> 0:11:32.720
<v Speaker 2>New York somehow powered a nationwide increase in violent crime.

0:11:32.760 --> 0:11:36.120
<v Speaker 2>It just doesn't compute. Really. Subsequent researchers backed that up

0:11:36.120 --> 0:11:37.960
<v Speaker 2>as well, and I'm happy to go into that too.

0:11:38.400 --> 0:11:41.880
<v Speaker 2>Another point that people argued was that this might be

0:11:42.040 --> 0:11:45.960
<v Speaker 2>a quote city phenomenon, that this is something that originates

0:11:45.960 --> 0:11:49.800
<v Speaker 2>in nebulously defined, quote blue city governance. I think this

0:11:49.920 --> 0:11:52.920
<v Speaker 2>idea is sort of a holdover of the way crime

0:11:53.040 --> 0:11:54.559
<v Speaker 2>used to look in this country. You know, if you

0:11:54.600 --> 0:11:58.120
<v Speaker 2>go back to the nineteen nineties, there were multiple thousands

0:11:58.120 --> 0:12:00.679
<v Speaker 2>of murders in New York every year. Amasite raid in

0:12:00.679 --> 0:12:03.280
<v Speaker 2>a city like New York was well about the national average,

0:12:03.320 --> 0:12:05.440
<v Speaker 2>And I think people sort of came to expect that

0:12:05.760 --> 0:12:08.960
<v Speaker 2>violent crime is a city problem. But fast forward thirty

0:12:09.000 --> 0:12:11.360
<v Speaker 2>years down the line, that's not quite so true. New

0:12:11.440 --> 0:12:13.080
<v Speaker 2>York City is one of the safest big cities in

0:12:13.080 --> 0:12:15.840
<v Speaker 2>the country. It's murder rate is below the national average.

0:12:16.200 --> 0:12:19.520
<v Speaker 2>So this idea that violent crime was caused by and

0:12:20.280 --> 0:12:23.320
<v Speaker 2>primarily a problem of cities, it's also simply not true,

0:12:23.360 --> 0:12:26.040
<v Speaker 2>but became a very prevalent narrative, especially during the early

0:12:26.120 --> 0:12:28.760
<v Speaker 2>days of the COVID nineteen pandemic. One of the other

0:12:28.800 --> 0:12:31.600
<v Speaker 2>theories that we've looked into, and others have really taken

0:12:31.800 --> 0:12:35.040
<v Speaker 2>a lot of time to try to research, is whether

0:12:35.200 --> 0:12:39.120
<v Speaker 2>the inauguration of district attorneys who believe in criminal justice

0:12:39.160 --> 0:12:42.359
<v Speaker 2>reform policies. The label you here as quote progressive prosecutors,

0:12:42.400 --> 0:12:44.960
<v Speaker 2>But I've talked to these people. They don't all subscribe

0:12:44.960 --> 0:12:47.320
<v Speaker 2>to that label. They subscribe to the idea that they

0:12:47.360 --> 0:12:51.280
<v Speaker 2>are elected district attorneys who believe in criminal justice reform policies.

0:12:51.720 --> 0:12:53.560
<v Speaker 2>But one of the arguments against them has been that.

0:12:53.640 --> 0:12:55.320
<v Speaker 1>We'll still wanting to enforce the law.

0:12:55.480 --> 0:12:58.600
<v Speaker 2>Indeed, yes, they're elected district attorneys who believe in criminal

0:12:58.640 --> 0:13:01.400
<v Speaker 2>justice reform as a means of making their community safer,

0:13:01.559 --> 0:13:05.080
<v Speaker 2>not as a political point. So one of the arguments

0:13:05.120 --> 0:13:08.160
<v Speaker 2>has done that these so called progressive prosecutors have presided

0:13:08.160 --> 0:13:10.160
<v Speaker 2>over a rise at crime and helped kick it off

0:13:10.160 --> 0:13:12.559
<v Speaker 2>in their cities, and the data just don't support that.

0:13:12.600 --> 0:13:15.160
<v Speaker 2>There's a really good study that was co authored by

0:13:15.280 --> 0:13:18.679
<v Speaker 2>Anna Harvey at NYU's Public Safety Lab that tried to

0:13:18.679 --> 0:13:21.480
<v Speaker 2>revide a relationship between progressive prosecuters and rise and crime,

0:13:21.520 --> 0:13:23.319
<v Speaker 2>and she couldn't do it. She just couldn't find any

0:13:23.320 --> 0:13:26.360
<v Speaker 2>sort of relationship. More researchers coming out on this. Now,

0:13:26.720 --> 0:13:28.800
<v Speaker 2>that was a popular narrative, but it just hasn't held up.

0:13:29.400 --> 0:13:32.160
<v Speaker 1>And then moreover in successive years, in twenty twenty one

0:13:32.200 --> 0:13:35.800
<v Speaker 1>and twenty twenty two, the homicide rate drop, the rate

0:13:35.840 --> 0:13:38.760
<v Speaker 1>of violent crimes dropped. What changed? Do you have a

0:13:38.800 --> 0:13:41.240
<v Speaker 1>handle on what was behind that phenomenon.

0:13:41.840 --> 0:13:44.079
<v Speaker 2>That's a question we're sitting with too. I actually think

0:13:44.120 --> 0:13:47.680
<v Speaker 2>it does suggest one point. So if you were as

0:13:47.760 --> 0:13:49.880
<v Speaker 2>we were sitting in the beginning of the COVID nineteen

0:13:49.920 --> 0:13:52.240
<v Speaker 2>pandemic and wondering, you know, what's happening in the country,

0:13:52.280 --> 0:13:55.439
<v Speaker 2>why are we seeing crime rates increase so much? If

0:13:55.480 --> 0:13:58.560
<v Speaker 2>you had a theory that part of this might be

0:13:58.720 --> 0:14:02.520
<v Speaker 2>due to factors related to the COVID nineteen pandemic, like

0:14:02.840 --> 0:14:06.840
<v Speaker 2>social disorder, like the shuddering of key institutions that help

0:14:06.920 --> 0:14:11.520
<v Speaker 2>keep communities safe, you might hypothesize that as the pandemic recedes,

0:14:11.960 --> 0:14:14.600
<v Speaker 2>we might start to see murder rates go down, and

0:14:14.640 --> 0:14:16.599
<v Speaker 2>that is in fact what we're now seeing. So I

0:14:16.640 --> 0:14:19.320
<v Speaker 2>think it's a point of evidence that suggests, but doesn't

0:14:19.320 --> 0:14:22.040
<v Speaker 2>conclusively prove, that much of the reason that we sew

0:14:22.160 --> 0:14:24.600
<v Speaker 2>violence spike so much in the early years of the

0:14:24.600 --> 0:14:28.400
<v Speaker 2>pandemic might be due to these factors related to the pandemic,

0:14:28.440 --> 0:14:30.520
<v Speaker 2>And as the world sort of returns to normal, as

0:14:30.560 --> 0:14:33.240
<v Speaker 2>businesses reopen, as people get back to their daily life.

0:14:33.360 --> 0:14:36.680
<v Speaker 2>As community rhythm's return, that sort of network of safety

0:14:36.680 --> 0:14:38.880
<v Speaker 2>and invisible bonds that keep us safe sort of re

0:14:39.000 --> 0:14:42.480
<v Speaker 2>establishes itself. I don't have a complete answer for this question,

0:14:42.560 --> 0:14:44.880
<v Speaker 2>but I think that's at least one theory worth thinking over.

0:14:45.480 --> 0:14:47.240
<v Speaker 1>So the lesson to be drawn from that is state

0:14:47.400 --> 0:14:50.160
<v Speaker 1>away from guns during year one of any lockdown, because

0:14:50.160 --> 0:14:52.080
<v Speaker 1>that's when people are most likely to fire them.

0:14:52.440 --> 0:14:54.200
<v Speaker 2>A question we think about too is sort of how

0:14:54.280 --> 0:14:57.120
<v Speaker 2>to build resilience into communities and how do you build

0:14:57.120 --> 0:15:00.720
<v Speaker 2>resilience into society as a whole? And trust absolutely and

0:15:00.760 --> 0:15:02.600
<v Speaker 2>trust I think that's a really good way of putting it.

0:15:02.960 --> 0:15:05.080
<v Speaker 2>There were some surprising things that we found when we

0:15:05.120 --> 0:15:08.280
<v Speaker 2>looked into, you know, not just what caused crime to

0:15:08.320 --> 0:15:10.880
<v Speaker 2>increase in twenty twenty, but you know what solutions people

0:15:10.880 --> 0:15:13.800
<v Speaker 2>were talking about. There's actually some research these days that

0:15:13.920 --> 0:15:16.280
<v Speaker 2>medicaid expansion, which we just saw go into place, and

0:15:16.320 --> 0:15:19.000
<v Speaker 2>I believe it was North Carolina, is actually associated with

0:15:19.200 --> 0:15:22.720
<v Speaker 2>lower arrest rates and lower rates of priscidivism in some cases.

0:15:23.240 --> 0:15:25.400
<v Speaker 2>This suggests to me that as you build a society

0:15:25.440 --> 0:15:28.160
<v Speaker 2>that has a stronger safety net and is more focused

0:15:28.200 --> 0:15:31.680
<v Speaker 2>on taking care of people. You might help firm up

0:15:31.720 --> 0:15:34.240
<v Speaker 2>that sort of invisible network that keeps us all safer.

0:15:35.680 --> 0:15:37.360
<v Speaker 1>On that note, Ames, I'm going to take a quick

0:15:37.440 --> 0:15:39.440
<v Speaker 1>break so we can hear from a sponsor, and then

0:15:39.440 --> 0:15:41.760
<v Speaker 1>we will come back in to chat further about all

0:15:41.760 --> 0:15:49.880
<v Speaker 1>of this. We're back with Ames GROWERDT and we're discussing

0:15:49.960 --> 0:15:54.000
<v Speaker 1>murder and other crimes during the pandemic and after Ames

0:15:54.000 --> 0:15:56.680
<v Speaker 1>we talked a little bit earlier about people citing the

0:15:56.720 --> 0:16:00.120
<v Speaker 1>wrong factors for this spike and murder and viol and

0:16:00.160 --> 0:16:02.920
<v Speaker 1>assaults during the pandemic and what some of the real

0:16:02.960 --> 0:16:05.440
<v Speaker 1>factors might have been. You know, we're having this conversation

0:16:05.520 --> 0:16:08.240
<v Speaker 1>and the context of the data is still recently fresh.

0:16:08.320 --> 0:16:11.480
<v Speaker 1>The events are still relatively recent, and no one knows

0:16:11.520 --> 0:16:13.920
<v Speaker 1>for certain, but our goal is to try to really

0:16:13.920 --> 0:16:15.720
<v Speaker 1>get it real cause and effect so we can get

0:16:15.720 --> 0:16:20.560
<v Speaker 1>better solutions. How was the narrative around the crime spike

0:16:20.760 --> 0:16:26.080
<v Speaker 1>during the COVID pandemic and after construct it. I'm interested

0:16:26.080 --> 0:16:29.120
<v Speaker 1>in that from your perspective. How did that narrative come

0:16:29.120 --> 0:16:32.200
<v Speaker 1>into the public consciousness, because it's certainly different than some

0:16:32.280 --> 0:16:34.600
<v Speaker 1>of what we just talked about earlier in terms of

0:16:35.080 --> 0:16:37.240
<v Speaker 1>the factors that actually informed the spike.

0:16:37.920 --> 0:16:40.480
<v Speaker 2>Yeah, that's a really good question and something I spend

0:16:40.520 --> 0:16:42.800
<v Speaker 2>a lot of time thinking about. I'll do my best

0:16:42.840 --> 0:16:44.760
<v Speaker 2>to give you as clear of an answer as I can,

0:16:44.840 --> 0:16:47.280
<v Speaker 2>but it's a complicated subject. On the one hand. You know,

0:16:47.360 --> 0:16:51.440
<v Speaker 2>I think when people see something like the covidanteen pandemic

0:16:51.520 --> 0:16:53.600
<v Speaker 2>and they see, you know, hard data showing what they're

0:16:53.600 --> 0:16:58.360
<v Speaker 2>feeling that violence is increasing, people naturally feel afraid and

0:16:58.400 --> 0:17:00.800
<v Speaker 2>feel concerned for their states, see in the safety their

0:17:00.840 --> 0:17:03.400
<v Speaker 2>loved ones, and those feelings are valid and important, and

0:17:03.400 --> 0:17:06.720
<v Speaker 2>we should respect that. Number one one temptation when these

0:17:06.800 --> 0:17:09.280
<v Speaker 2>very reasonable fears arise, I think it's tempting for some

0:17:09.440 --> 0:17:12.399
<v Speaker 2>to look for sort of easy explanations. It's tempting to

0:17:12.440 --> 0:17:15.359
<v Speaker 2>say this is a problem, and here's the solution, and

0:17:15.359 --> 0:17:19.200
<v Speaker 2>that solution will work tomorrow. When people gravitate to those

0:17:19.240 --> 0:17:23.200
<v Speaker 2>easy answers, those answers feel good, they might sound attractive,

0:17:23.720 --> 0:17:25.800
<v Speaker 2>but they might be wrong, and more than that, they

0:17:25.880 --> 0:17:28.800
<v Speaker 2>might actually end up doing more harm than good. So

0:17:28.840 --> 0:17:31.800
<v Speaker 2>I think that's one factor, and telling the narrative onward

0:17:32.000 --> 0:17:34.960
<v Speaker 2>is know, when crime rose, people looked for sort of

0:17:35.000 --> 0:17:37.760
<v Speaker 2>a single factor answer, you know, crime rose by thirty

0:17:37.800 --> 0:17:42.399
<v Speaker 2>percent in twenty twenty because of X, and insert into X,

0:17:42.480 --> 0:17:45.760
<v Speaker 2>you know, bail reform, quote, blue city, something like that.

0:17:45.760 --> 0:17:48.359
<v Speaker 2>That answer might have a certain narrative and intuitive appeal,

0:17:48.440 --> 0:17:51.320
<v Speaker 2>it just happens to be wrong. Another factor I think

0:17:51.320 --> 0:17:53.320
<v Speaker 2>we've seen, and I touched on this a little bit earlier,

0:17:53.800 --> 0:17:55.720
<v Speaker 2>is I think because of the way that crime trends

0:17:55.760 --> 0:17:57.879
<v Speaker 2>in the country used to look, people are sort of

0:17:57.920 --> 0:18:00.280
<v Speaker 2>primed to think of crime as a city issue rather

0:18:00.320 --> 0:18:03.240
<v Speaker 2>than an American issue, and people are primed to believe

0:18:03.280 --> 0:18:06.480
<v Speaker 2>that cities like New York are uniquely dangerous, when actually

0:18:06.600 --> 0:18:10.440
<v Speaker 2>almost the opposite is true. Representative Jim Jordan hosted a

0:18:10.480 --> 0:18:13.200
<v Speaker 2>field hearing in New York City designed to highlight how

0:18:13.280 --> 0:18:15.879
<v Speaker 2>crime in the city was increasing. It just happened to

0:18:15.920 --> 0:18:18.080
<v Speaker 2>be at a time when murder trends in the city

0:18:18.080 --> 0:18:21.680
<v Speaker 2>were actually declining sharply, and the evidence for rising crime

0:18:21.680 --> 0:18:23.520
<v Speaker 2>in New York City was simply nowhere to be found.

0:18:23.560 --> 0:18:25.399
<v Speaker 2>You know, the city, like other places in the country,

0:18:25.440 --> 0:18:28.040
<v Speaker 2>had experience of crime spike during the pandemic, but by

0:18:28.080 --> 0:18:30.480
<v Speaker 2>all accounts that spike was in the process of reversing.

0:18:31.280 --> 0:18:33.840
<v Speaker 2>These narratives, they have an intuitive appeal. It's up to

0:18:33.960 --> 0:18:37.399
<v Speaker 2>you know, policymakers and other opinion leaders like us in fact,

0:18:37.480 --> 0:18:41.199
<v Speaker 2>to talk through why those narratives might not actually be

0:18:41.320 --> 0:18:43.800
<v Speaker 2>true and why there might be other solutions that can

0:18:43.840 --> 0:18:46.399
<v Speaker 2>make us safer. A colleague of mine who I do

0:18:46.480 --> 0:18:48.840
<v Speaker 2>some work with, in Hirahman at the Beer Institute. She

0:18:48.880 --> 0:18:51.800
<v Speaker 2>has a really interesting saying, I think in something that

0:18:51.840 --> 0:18:54.159
<v Speaker 2>I think about daily. She says, you know, if we

0:18:54.240 --> 0:18:57.199
<v Speaker 2>focus on the wrong problems, we also focus on the

0:18:57.200 --> 0:19:01.400
<v Speaker 2>wrong solutions. So if you yourself in a narrative where

0:19:01.400 --> 0:19:04.280
<v Speaker 2>you think the reason that crime is up is because

0:19:04.280 --> 0:19:06.960
<v Speaker 2>cities are doing something wrong and bail reform or progressive

0:19:07.000 --> 0:19:09.320
<v Speaker 2>prosecutor or something like that, you might miss some other

0:19:09.400 --> 0:19:12.320
<v Speaker 2>solution that has nothing to do with those quote problems

0:19:12.359 --> 0:19:15.440
<v Speaker 2>and that could actually lead to safer communities down the line.

0:19:15.760 --> 0:19:17.399
<v Speaker 1>And as I noted at the top of the show,

0:19:17.720 --> 0:19:21.359
<v Speaker 1>suburbs and rural areas saw a very similar spike to

0:19:21.440 --> 0:19:24.919
<v Speaker 1>what cities saw. So the idea again that cities themselves

0:19:24.920 --> 0:19:28.440
<v Speaker 1>are unique kind of breeding grounds or Petrie dishes for

0:19:29.440 --> 0:19:32.760
<v Speaker 1>violent crime is belied by reality in the data.

0:19:33.080 --> 0:19:33.960
<v Speaker 2>That's exactly right.

0:19:34.560 --> 0:19:38.919
<v Speaker 1>Having said that, aims about the similarities of suburbs and

0:19:39.000 --> 0:19:43.040
<v Speaker 1>rural areas and cities. There is also reality at work here. However,

0:19:43.080 --> 0:19:47.040
<v Speaker 1>there is no denying that city streets do for a

0:19:47.040 --> 0:19:50.240
<v Speaker 1>lot of people feel less safe. A lot of small

0:19:50.280 --> 0:19:53.879
<v Speaker 1>businesses have boarded up, there's less people walking around in

0:19:53.920 --> 0:19:57.439
<v Speaker 1>the streets, particularly late at night. Homelessness has been on

0:19:57.480 --> 0:20:00.320
<v Speaker 1>the rise in every big city I think, or at

0:20:00.359 --> 0:20:02.520
<v Speaker 1>least most of the big ones, and I've visited a

0:20:02.600 --> 0:20:05.199
<v Speaker 1>number of them since COVID began, and you just notice

0:20:05.200 --> 0:20:09.600
<v Speaker 1>homeless people wandering in greater numbers in the past, and

0:20:09.920 --> 0:20:13.840
<v Speaker 1>there is this perception that the streets aren't as safe,

0:20:13.880 --> 0:20:16.800
<v Speaker 1>even if the data doesn't show us that. Let's talk

0:20:16.840 --> 0:20:19.200
<v Speaker 1>about that a little bit, because that is a reality

0:20:19.280 --> 0:20:21.520
<v Speaker 1>based conclusion for a lot of folks.

0:20:22.080 --> 0:20:25.320
<v Speaker 2>Absolutely it is, yes, And when people have that impression,

0:20:25.359 --> 0:20:27.359
<v Speaker 2>they were reacting to something real. I'm not one to

0:20:27.400 --> 0:20:31.320
<v Speaker 2>discount people's experiences and fears about their community. I think

0:20:31.359 --> 0:20:33.840
<v Speaker 2>one thing at work here is people see social disorder,

0:20:33.960 --> 0:20:36.959
<v Speaker 2>People see hardship in their lives, such as an increasing

0:20:37.000 --> 0:20:39.439
<v Speaker 2>number of people living on the streets, and they make

0:20:39.480 --> 0:20:42.560
<v Speaker 2>a sort of intuitive connection between bad and crime. But

0:20:42.600 --> 0:20:45.240
<v Speaker 2>social disorder and crime are not necessarily one of the same.

0:20:45.280 --> 0:20:47.439
<v Speaker 2>They might in some cases go hand in hand, but

0:20:47.520 --> 0:20:49.680
<v Speaker 2>that might be one reason why we see a sort

0:20:49.720 --> 0:20:52.760
<v Speaker 2>of a gap between the perceptions and realities around the trends,

0:20:52.880 --> 0:20:55.680
<v Speaker 2>especially in major offenses. These are real problems. They don't

0:20:55.680 --> 0:20:57.520
<v Speaker 2>want to downplay it. Like I've seen the data on

0:20:57.560 --> 0:21:00.119
<v Speaker 2>homelessness and Portland, I've seen the data on homelessness in

0:21:00.119 --> 0:21:02.359
<v Speaker 2>California and New York, and you're right, it is up.

0:21:02.440 --> 0:21:06.000
<v Speaker 2>But the solutions to those problems might lie outside the

0:21:06.000 --> 0:21:08.800
<v Speaker 2>criminal justice system, where they might lie in other policy

0:21:08.800 --> 0:21:12.040
<v Speaker 2>interventions disconnected from the problem of crime in the United.

0:21:11.800 --> 0:21:14.479
<v Speaker 1>States, and the sense of menace that some people might

0:21:14.520 --> 0:21:17.679
<v Speaker 1>feel from a homeless person doesn't necessarily translate into the

0:21:17.680 --> 0:21:20.800
<v Speaker 1>homeless person whipping out a gun and shooting you or

0:21:20.840 --> 0:21:21.439
<v Speaker 1>assaulting you.

0:21:21.600 --> 0:21:24.000
<v Speaker 2>Right, But you know people's fears about their safety and

0:21:24.040 --> 0:21:26.119
<v Speaker 2>about seeing disorder in their community. I want to make

0:21:26.160 --> 0:21:29.359
<v Speaker 2>sure that we take that seriously, and policymakers should. They

0:21:29.359 --> 0:21:31.680
<v Speaker 2>should just be careful about what solutions we can offer

0:21:31.800 --> 0:21:34.200
<v Speaker 2>to try to build healthier communities for everyone.

0:21:34.520 --> 0:21:36.879
<v Speaker 1>Two of the other sort of marquee incidents that have

0:21:37.160 --> 0:21:41.120
<v Speaker 1>I think also make people worried about cities are shoplifting waves.

0:21:41.720 --> 0:21:45.159
<v Speaker 1>As we know from the data, most shoplifting is carried

0:21:45.160 --> 0:21:48.639
<v Speaker 1>out by a small cohort, often acting in conjunction with

0:21:48.640 --> 0:21:52.639
<v Speaker 1>one another. They're repeat offenders. Again, that doesn't take away

0:21:52.640 --> 0:21:55.199
<v Speaker 1>from the fact that the shoplifting is occurring and it

0:21:55.240 --> 0:21:59.560
<v Speaker 1>appears to be unstopped. Storefronts are shattered, or people walk

0:21:59.560 --> 0:22:02.160
<v Speaker 1>into a retail store and just sweep stuff off the shelves.

0:22:02.720 --> 0:22:05.879
<v Speaker 1>Have you thought about shoplifting it's just a category of

0:22:06.280 --> 0:22:08.520
<v Speaker 1>sort of urban blight, or maybe the data there I

0:22:08.520 --> 0:22:11.399
<v Speaker 1>don't actually know. Is the data similar again across the

0:22:11.400 --> 0:22:14.600
<v Speaker 1>board of shoplifting a problem also in suburbs and in

0:22:14.680 --> 0:22:15.760
<v Speaker 1>rural areas as well.

0:22:15.960 --> 0:22:18.639
<v Speaker 2>This is a challenging question too, because there are a

0:22:18.720 --> 0:22:22.000
<v Speaker 2>number of things that can explain trends in shoplifting. Different

0:22:22.000 --> 0:22:26.439
<v Speaker 2>stores have different strategies or protocols for reporting shoplifting to

0:22:26.440 --> 0:22:29.520
<v Speaker 2>the police. For example, a colleague is a former prosecutor

0:22:29.520 --> 0:22:32.280
<v Speaker 2>mentioned this to me. You know, if I go into

0:22:32.640 --> 0:22:36.280
<v Speaker 2>a convenience store every day one week and steal you know,

0:22:36.320 --> 0:22:39.320
<v Speaker 2>ten dollars worth of property, is it the store policy

0:22:39.359 --> 0:22:41.680
<v Speaker 2>to report me the first time and every subsequent time?

0:22:41.840 --> 0:22:43.800
<v Speaker 2>Is it the store policy to call the police only

0:22:43.840 --> 0:22:46.680
<v Speaker 2>after the seventh and then report every incident. These sort

0:22:46.680 --> 0:22:50.560
<v Speaker 2>of differences in how stores and store owners report shoplifting

0:22:50.560 --> 0:22:53.480
<v Speaker 2>to police can sort of confound our understanding of the data,

0:22:53.520 --> 0:22:56.639
<v Speaker 2>and it makes it very hard to understand precise trends

0:22:56.680 --> 0:23:00.119
<v Speaker 2>in shoplifting around the country and individual cities. One thing

0:23:00.200 --> 0:23:02.359
<v Speaker 2>does seem to be clear, though, and most data that

0:23:02.359 --> 0:23:04.240
<v Speaker 2>we have does point to this, and that is that

0:23:04.280 --> 0:23:08.040
<v Speaker 2>shoplifting has increased in some major cities. In New York City,

0:23:08.040 --> 0:23:11.000
<v Speaker 2>the data seems very clear that shoplifting increased sharply in

0:23:11.000 --> 0:23:13.959
<v Speaker 2>twenty twenty two, and that it actually increased year over

0:23:14.080 --> 0:23:16.600
<v Speaker 2>year for I think going back more than a decade.

0:23:16.960 --> 0:23:19.200
<v Speaker 2>So the problem is very real, even if we need

0:23:19.240 --> 0:23:21.480
<v Speaker 2>better data to fully understand what's going on.

0:23:21.880 --> 0:23:24.080
<v Speaker 1>And tell me. As a last category before we move

0:23:24.119 --> 0:23:27.200
<v Speaker 1>on to other and grander things, or carjacking, that has

0:23:27.280 --> 0:23:29.760
<v Speaker 1>also seemed to have been on the rise in urban areas,

0:23:29.800 --> 0:23:33.040
<v Speaker 1>prekly in places like Chicago, in very stark ways. You know,

0:23:33.119 --> 0:23:36.080
<v Speaker 1>drivers are pulled over by another car, or is they're

0:23:36.080 --> 0:23:38.240
<v Speaker 1>getting out of a car or into a car, they're

0:23:38.400 --> 0:23:41.000
<v Speaker 1>essentially held up and their car is stolen. And that

0:23:41.200 --> 0:23:44.320
<v Speaker 1>seems to be a more frequent and visible crime than

0:23:44.320 --> 0:23:45.280
<v Speaker 1>it was a few years ago.

0:23:45.720 --> 0:23:48.159
<v Speaker 2>That's right, and this is actually a tough crime for

0:23:48.200 --> 0:23:49.800
<v Speaker 2>us to study as well. I feel like I'm saying

0:23:49.800 --> 0:23:51.800
<v Speaker 2>that a lot, but you can get an idea of

0:23:51.800 --> 0:23:54.760
<v Speaker 2>how challenging the data can be. Sometimes. The reason is that,

0:23:54.840 --> 0:23:56.960
<v Speaker 2>until very recently, and I know we'll talk about this

0:23:57.000 --> 0:23:59.520
<v Speaker 2>in more detail, car jacking was not broken out as

0:23:59.520 --> 0:24:02.000
<v Speaker 2>a separate fence studied by the FBI. It was sort

0:24:02.000 --> 0:24:04.560
<v Speaker 2>of rolled into robbery. So in many places we don't

0:24:04.560 --> 0:24:07.280
<v Speaker 2>really have an idea of year to year trends in carjacking.

0:24:07.359 --> 0:24:10.119
<v Speaker 2>The data that we do have does show that it

0:24:10.200 --> 0:24:13.160
<v Speaker 2>is increasing or increased in twenty twenty two. We also

0:24:13.359 --> 0:24:15.960
<v Speaker 2>know from city reports. I think you mentioned Chicago. I'm

0:24:15.960 --> 0:24:17.640
<v Speaker 2>not familiar with the data, but I'm sure you're right.

0:24:18.000 --> 0:24:21.120
<v Speaker 2>But we know in Washington, DC carjackings definitely have increased.

0:24:21.560 --> 0:24:24.000
<v Speaker 2>As to why it's a tough question, I go back

0:24:24.000 --> 0:24:27.159
<v Speaker 2>to something I mentioned earlier. There might be some correlation

0:24:27.280 --> 0:24:30.440
<v Speaker 2>between types of motor vehicle theft and other more serious crimes.

0:24:30.480 --> 0:24:32.840
<v Speaker 2>As you steal a car, you carjack a car to

0:24:32.880 --> 0:24:34.960
<v Speaker 2>be used in a more serious efense down the line.

0:24:35.119 --> 0:24:37.040
<v Speaker 2>It could be that those types of defenses go hand

0:24:37.040 --> 0:24:37.400
<v Speaker 2>in hand.

0:24:37.760 --> 0:24:40.720
<v Speaker 1>And is there like a psychology of crime that when

0:24:40.760 --> 0:24:44.920
<v Speaker 1>you see categories of crime as a resident spike, whether

0:24:44.960 --> 0:24:48.320
<v Speaker 1>it's murders or assaults, it leads you to believe that

0:24:48.359 --> 0:24:51.480
<v Speaker 1>every kind of crime that could take place might take

0:24:51.520 --> 0:24:54.760
<v Speaker 1>place and will also increase. And that sort of feeds

0:24:54.840 --> 0:24:57.720
<v Speaker 1>on itself, and people can get into that space without

0:24:57.880 --> 0:25:01.320
<v Speaker 1>necessarily finding easy ways to reverse the fears they're feeling.

0:25:01.760 --> 0:25:03.679
<v Speaker 2>I think that's true. It goes to a sort of

0:25:03.840 --> 0:25:06.280
<v Speaker 2>broader concept. I think people of all types like to

0:25:06.280 --> 0:25:09.560
<v Speaker 2>see accountability and like to see people, you know, face

0:25:09.600 --> 0:25:12.440
<v Speaker 2>consequences for their actions. So if they see people committing

0:25:12.480 --> 0:25:15.080
<v Speaker 2>crimes and facing no consequence for it, it leads them

0:25:15.080 --> 0:25:18.280
<v Speaker 2>to draw broader conclusions about the health of society and

0:25:18.320 --> 0:25:21.040
<v Speaker 2>the moral fabric of their communities. That might be one

0:25:21.040 --> 0:25:23.040
<v Speaker 2>way that we see fears about one type of crime

0:25:23.119 --> 0:25:26.000
<v Speaker 2>bleed over into another. Sort of an interesting thing if

0:25:26.040 --> 0:25:28.560
<v Speaker 2>you ask people what types of crime they're most worried about,

0:25:28.920 --> 0:25:31.359
<v Speaker 2>it really depends on the community. Number One, when we

0:25:31.400 --> 0:25:34.200
<v Speaker 2>saw violence brise in twenty twenty, it was very very uneven.

0:25:34.400 --> 0:25:37.160
<v Speaker 2>The violence spiked more in New York city, for example,

0:25:37.520 --> 0:25:40.320
<v Speaker 2>in neighborhoods that have always been for have always struggled

0:25:40.359 --> 0:25:42.800
<v Speaker 2>with violence, so that increase might not have been as

0:25:42.880 --> 0:25:45.520
<v Speaker 2>visible to other people. But often you see people are

0:25:45.560 --> 0:25:48.280
<v Speaker 2>more worried in some cases about what we in the

0:25:48.320 --> 0:25:51.480
<v Speaker 2>policy field might call relatively lower level offenses, as in

0:25:52.000 --> 0:25:54.480
<v Speaker 2>not the most serious offenses known to law enforcement, but

0:25:54.560 --> 0:25:58.000
<v Speaker 2>crimes like shoplifting, crimes like turnstile jumping, things like that.

0:25:58.080 --> 0:26:01.400
<v Speaker 2>Those sort of crimes can definitely affect people's perception of safety.

0:26:02.080 --> 0:26:04.680
<v Speaker 1>And this is a good moment to point out that

0:26:04.720 --> 0:26:08.360
<v Speaker 1>it is our neighbors and fellow Americans at the lowest

0:26:08.920 --> 0:26:13.159
<v Speaker 1>part of the socioeconomic ladder who experience the brunt of

0:26:13.240 --> 0:26:17.280
<v Speaker 1>violent crime increases, particularly homicides and violent assaults. So within

0:26:17.320 --> 0:26:20.680
<v Speaker 1>those statistics, they don't apply in a blanket and uniform

0:26:20.720 --> 0:26:24.520
<v Speaker 1>way across our society. They really affect usually the most

0:26:24.600 --> 0:26:26.679
<v Speaker 1>vulnerable and disadvantaged people the hardest.

0:26:26.840 --> 0:26:30.200
<v Speaker 2>That's absolutely right. There's a complicated relationship between poverty and crime,

0:26:30.280 --> 0:26:32.720
<v Speaker 2>but if you look at cities around the country, you

0:26:32.800 --> 0:26:35.600
<v Speaker 2>tend to see violence and rising crime in twenty twenty

0:26:35.920 --> 0:26:38.920
<v Speaker 2>clustered in communities that have suffered from other disadvantages. Those

0:26:38.920 --> 0:26:41.439
<v Speaker 2>sort of inequalities have always existed, you know, you go

0:26:41.560 --> 0:26:44.000
<v Speaker 2>back years, you'll see the same sort of prends. They

0:26:44.000 --> 0:26:47.120
<v Speaker 2>simply became more exaggerated or pronounced during the COVID nineteen ten.

0:26:47.040 --> 0:26:50.280
<v Speaker 1>Dem let's take another break, games, then we'll come right back.

0:26:55.480 --> 0:26:58.000
<v Speaker 1>We're back, and I'm having a conversation about crime and

0:26:58.040 --> 0:27:02.359
<v Speaker 1>the COVID nineteen pandemic with Aames Groward. Ames, I think

0:27:02.400 --> 0:27:05.480
<v Speaker 1>we have a data collection and data analysis problem around

0:27:05.560 --> 0:27:09.760
<v Speaker 1>crime statistics that transcends politics and disagreements, and maybe it

0:27:09.800 --> 0:27:13.080
<v Speaker 1>even makes them worse from my perspective, But I was

0:27:13.119 --> 0:27:14.480
<v Speaker 1>wondering what you thought of that.

0:27:14.480 --> 0:27:17.119
<v Speaker 2>That's absolutely right. Someone we've worked with before, a law

0:27:17.160 --> 0:27:19.680
<v Speaker 2>professor John faff I'm going to borrow point that he makes,

0:27:19.720 --> 0:27:22.000
<v Speaker 2>and that is we have up to the minute data

0:27:22.040 --> 0:27:25.800
<v Speaker 2>on the economy, unemployment data, jobs created, et cetera. But

0:27:25.840 --> 0:27:29.080
<v Speaker 2>when it comes to our data on crime, until very recently,

0:27:29.200 --> 0:27:31.400
<v Speaker 2>we had to wait almost a year, nine to ten

0:27:31.480 --> 0:27:34.560
<v Speaker 2>full months between the end of a year and the

0:27:34.760 --> 0:27:38.600
<v Speaker 2>release of national crime data by the Federal Bureau of Investigation.

0:27:38.800 --> 0:27:40.720
<v Speaker 2>So be give you an example. If you wanted to

0:27:40.720 --> 0:27:44.199
<v Speaker 2>see national crime data on twenty nineteen. You had to

0:27:44.200 --> 0:27:46.919
<v Speaker 2>wait until late September twenty twenty for that data to

0:27:46.960 --> 0:27:50.960
<v Speaker 2>come out. That's nowhere close to the real time data

0:27:50.960 --> 0:27:54.920
<v Speaker 2>that policymakers need to actually craft interventions and understand what's

0:27:54.960 --> 0:27:59.560
<v Speaker 2>happening in their community relative to communities around the country now.

0:27:59.600 --> 0:28:01.640
<v Speaker 2>To be sure, local data is much more up to date.

0:28:01.680 --> 0:28:04.680
<v Speaker 2>I could pull up New York City's constant portal right

0:28:04.720 --> 0:28:06.600
<v Speaker 2>now and it would have data that's probably less than

0:28:06.640 --> 0:28:08.920
<v Speaker 2>a week old. Depending on the day of the week,

0:28:08.960 --> 0:28:11.679
<v Speaker 2>it might be, you know, yesterday. But when we don't

0:28:11.720 --> 0:28:14.440
<v Speaker 2>have national data, or when we have delayed national data,

0:28:14.480 --> 0:28:16.520
<v Speaker 2>it also has an effect on the narrative. So to

0:28:16.560 --> 0:28:19.639
<v Speaker 2>give you an example, you know you will hear policymakers

0:28:19.680 --> 0:28:23.480
<v Speaker 2>talk about rising crime in major cities. Over the past month,

0:28:23.480 --> 0:28:26.440
<v Speaker 2>I've heard many policymakers on the federal level talk about

0:28:26.480 --> 0:28:28.840
<v Speaker 2>rising crime in major cities. In every case, they're citing

0:28:28.920 --> 0:28:31.400
<v Speaker 2>data from twenty twenty. You know, that's three years ago.

0:28:31.600 --> 0:28:34.240
<v Speaker 2>Why aren't they using more recent data? Why aren't they

0:28:34.280 --> 0:28:36.679
<v Speaker 2>aware of more recent data? And the answer is not

0:28:36.720 --> 0:28:39.680
<v Speaker 2>necessarily bad faith. The answer might be in part that

0:28:39.840 --> 0:28:42.400
<v Speaker 2>we have such a delay between the year that we're

0:28:42.400 --> 0:28:45.000
<v Speaker 2>interested in studying and when crime data actually come out

0:28:45.240 --> 0:28:47.080
<v Speaker 2>that it sort of takes a while for the public

0:28:47.120 --> 0:28:50.360
<v Speaker 2>to understand and adjust to what those data show. There's

0:28:50.360 --> 0:28:54.000
<v Speaker 2>sort of a lag time between our reality of national

0:28:54.040 --> 0:28:57.080
<v Speaker 2>crime trends and our perception of what those trends actually

0:28:57.080 --> 0:28:59.560
<v Speaker 2>look like. And it's actually gotten worse in the past

0:28:59.560 --> 0:29:02.239
<v Speaker 2>couple of years due to transition of the way the

0:29:02.280 --> 0:29:04.760
<v Speaker 2>FBI calculates crime data, which I could talk to you

0:29:04.800 --> 0:29:05.960
<v Speaker 2>about as well well.

0:29:06.000 --> 0:29:09.600
<v Speaker 1>Since you mentioned the FBI, My Bloomberg Opinion colleague Justin Fox,

0:29:09.920 --> 0:29:12.560
<v Speaker 1>who loves to crunch and examine numbers around all sorts

0:29:12.560 --> 0:29:16.640
<v Speaker 1>of things, has been particularly frustrated by the FBI's methodology.

0:29:17.200 --> 0:29:20.120
<v Speaker 1>He recently wrote this about how the FBI colates data

0:29:20.160 --> 0:29:23.760
<v Speaker 1>around four major crimes to analyze violent crime rates, and

0:29:23.800 --> 0:29:27.200
<v Speaker 1>I'm quoting Justin here. To calculate violent crime rates, the

0:29:27.280 --> 0:29:30.840
<v Speaker 1>FBI simply adds together the incidents of the four violent crimes,

0:29:31.240 --> 0:29:33.560
<v Speaker 1>meaning the rate ends up being determined by the most

0:29:33.560 --> 0:29:39.000
<v Speaker 1>common ones, robbery and especially aggravated assault. That's not great.

0:29:39.440 --> 0:29:41.560
<v Speaker 1>What do you think of Justin's thoughts on that?

0:29:41.800 --> 0:29:44.280
<v Speaker 2>Your colleague is absolutely right to make the problem even

0:29:44.320 --> 0:29:47.120
<v Speaker 2>more stark when people talk about the overall crime rate,

0:29:47.280 --> 0:29:49.800
<v Speaker 2>what they tend to be referring to is the incidences

0:29:49.800 --> 0:29:52.800
<v Speaker 2>of the four violent offenses that Justin referred to, plus

0:29:52.880 --> 0:29:55.600
<v Speaker 2>the three property crime offenses historically tracked by the FBI,

0:29:55.760 --> 0:29:59.440
<v Speaker 2>so burglary, larceny, motor vehicle theft. But when you add

0:29:59.440 --> 0:30:02.640
<v Speaker 2>all those together, larceny is far and away the most

0:30:02.680 --> 0:30:06.240
<v Speaker 2>common offense, overwhelming all of them. So when people talk

0:30:06.280 --> 0:30:08.400
<v Speaker 2>about the quote crime rate, there's often a risk that

0:30:08.440 --> 0:30:10.920
<v Speaker 2>you're really talking about the larceny rate with some other

0:30:11.000 --> 0:30:13.720
<v Speaker 2>crimes thrown in there. It's a very sort of blunt

0:30:13.800 --> 0:30:15.880
<v Speaker 2>way of looking at crime trends.

0:30:15.640 --> 0:30:18.040
<v Speaker 1>And skewed statistically skewed.

0:30:17.920 --> 0:30:20.800
<v Speaker 2>Yes, especially because we actually saw this phenomenon in the

0:30:20.800 --> 0:30:25.760
<v Speaker 2>COVID nineteen pandemic. Larcenies have fallen for starting in nineteen ninety,

0:30:25.760 --> 0:30:28.520
<v Speaker 2>they fill every year until I think twenty twenty two.

0:30:28.760 --> 0:30:31.400
<v Speaker 2>So you could look at quote overall crime data in

0:30:31.440 --> 0:30:34.560
<v Speaker 2>twenty twenty and see a decline in crime rates twenty

0:30:34.640 --> 0:30:37.560
<v Speaker 2>nineteen to twenty twenty. So you could hear people say, well,

0:30:37.600 --> 0:30:40.200
<v Speaker 2>the murder rate is up and respond with well crime

0:30:40.280 --> 0:30:44.560
<v Speaker 2>is down, and you're both right. But if you're discounting

0:30:44.560 --> 0:30:47.480
<v Speaker 2>a thirty percent spike in murder. By looking at larceny data,

0:30:48.160 --> 0:30:48.760
<v Speaker 2>you're just not.

0:30:49.280 --> 0:30:50.560
<v Speaker 1>Doing apples and oranges.

0:30:50.680 --> 0:30:53.440
<v Speaker 2>Yes, as oranges. You're not doing the real analysis the

0:30:53.440 --> 0:30:55.200
<v Speaker 2>public needs. That's part of the challenge of it.

0:30:55.800 --> 0:30:57.880
<v Speaker 1>So how do we get better data so we all

0:30:57.920 --> 0:30:59.960
<v Speaker 1>have better confidence in what we're talking about?

0:31:00.280 --> 0:31:01.920
<v Speaker 2>So here I actually have some good news for you,

0:31:01.960 --> 0:31:03.960
<v Speaker 2>which I think we're all eager for. At this time,

0:31:04.320 --> 0:31:06.640
<v Speaker 2>the FBI is in the process of a transition to

0:31:06.800 --> 0:31:10.880
<v Speaker 2>something called the National Incident Based Reporting System. So when

0:31:10.960 --> 0:31:14.840
<v Speaker 2>that transition is done, we will have two things. Number One,

0:31:15.040 --> 0:31:18.480
<v Speaker 2>we'll have a system that tracks a much wider array

0:31:18.480 --> 0:31:22.240
<v Speaker 2>of offenses in much greater detail. So we won't just have

0:31:22.360 --> 0:31:26.520
<v Speaker 2>data on larsenies. We'll have data on larceny dash, shoplifting,

0:31:26.920 --> 0:31:30.320
<v Speaker 2>larceny dash, by fraud, larceny dash, you know, every variety

0:31:30.360 --> 0:31:33.000
<v Speaker 2>of every variety of crime. That's going to allow for

0:31:33.920 --> 0:31:38.120
<v Speaker 2>much richer, more thoughtful analysis of crime trends year over year.

0:31:38.240 --> 0:31:40.440
<v Speaker 2>And you can actually see that in some work already,

0:31:40.520 --> 0:31:43.040
<v Speaker 2>because many cities have already adopted this new system. You

0:31:43.120 --> 0:31:44.880
<v Speaker 2>can see that in some work by the Council and

0:31:44.960 --> 0:31:48.720
<v Speaker 2>Criminal Justice A great nonprofit organization. They put together an

0:31:48.760 --> 0:31:52.440
<v Speaker 2>analysis of shoplifting trends across the country using NYBERS data,

0:31:52.480 --> 0:31:54.600
<v Speaker 2>which is how people in my field refer to the

0:31:54.680 --> 0:31:57.640
<v Speaker 2>National Incident based Crime Reporting System, and they had a

0:31:57.680 --> 0:32:01.000
<v Speaker 2>much richer look at what's actually happening shoplifting around the country.

0:32:01.000 --> 0:32:04.040
<v Speaker 2>It was really interesting. Their finding was, as we discussed,

0:32:04.040 --> 0:32:05.720
<v Speaker 2>that it's a real problem in New York. But so

0:32:05.800 --> 0:32:09.080
<v Speaker 2>number one, we'll have a richer analysis of what the

0:32:09.160 --> 0:32:12.000
<v Speaker 2>data actually look like. Number two will actually have more

0:32:12.000 --> 0:32:15.000
<v Speaker 2>timely data. The FBI is in the process of rolling

0:32:15.000 --> 0:32:18.000
<v Speaker 2>out quarterly reports, so rather than have to wait for

0:32:18.320 --> 0:32:21.480
<v Speaker 2>September October every year for your dose of national crime data,

0:32:21.840 --> 0:32:24.960
<v Speaker 2>every quarter you should get a little more data on

0:32:25.000 --> 0:32:27.720
<v Speaker 2>the national picture. That data will still have a lag time,

0:32:27.800 --> 0:32:30.120
<v Speaker 2>it will still be fairly stale by the time you

0:32:30.160 --> 0:32:31.880
<v Speaker 2>read it, but you won't have to wait a year.

0:32:32.040 --> 0:32:34.080
<v Speaker 2>And I think that's the real improvement and should help

0:32:34.160 --> 0:32:37.440
<v Speaker 2>policymakers come to better and more thoughtful and more timely

0:32:37.480 --> 0:32:41.000
<v Speaker 2>conclusions about crime data. I can't give you unallied good

0:32:41.040 --> 0:32:44.760
<v Speaker 2>news here though, because although this new system is going

0:32:44.760 --> 0:32:48.840
<v Speaker 2>to be fantastic when it's fully implemented, implementation is going

0:32:49.000 --> 0:32:50.680
<v Speaker 2>better than it was a year ago, but it's not

0:32:50.760 --> 0:32:54.600
<v Speaker 2>going great. That's because to switch over to the system,

0:32:54.920 --> 0:32:58.040
<v Speaker 2>police departments, that is, the agencies that report crime data

0:32:58.200 --> 0:33:01.080
<v Speaker 2>up through their state to the federal government, have to

0:33:01.320 --> 0:33:04.360
<v Speaker 2>rework their computer systems and their way of tracking crime data.

0:33:04.480 --> 0:33:07.239
<v Speaker 2>That takes time, that takes money, it's difficult to do,

0:33:07.440 --> 0:33:10.280
<v Speaker 2>take staff, and many departments, through no fault of their own,

0:33:10.400 --> 0:33:12.000
<v Speaker 2>don't have the ability to do that and.

0:33:11.960 --> 0:33:14.320
<v Speaker 1>Happen, including some pretty big ones, some.

0:33:14.400 --> 0:33:17.120
<v Speaker 2>Very big ones in fact, so Florida and Pennsylvania remain

0:33:17.200 --> 0:33:20.600
<v Speaker 2>big blind spots and the incident based reporting system, as

0:33:20.640 --> 0:33:21.520
<v Speaker 2>does New York City.

0:33:21.760 --> 0:33:25.560
<v Speaker 1>Right, and you've mentioned now two different states in a city.

0:33:25.920 --> 0:33:29.800
<v Speaker 1>How reliable is data comparing one state to another or

0:33:29.840 --> 0:33:32.640
<v Speaker 1>one city to another when when you see these sort

0:33:32.680 --> 0:33:35.600
<v Speaker 1>of comparisons about what's safe and what isn't, what's a

0:33:35.680 --> 0:33:37.120
<v Speaker 1>crime written place and what isn't.

0:33:37.520 --> 0:33:39.760
<v Speaker 2>Yeah, let me put it this way. You know, the

0:33:39.840 --> 0:33:42.479
<v Speaker 2>FBI's role is they seek to standardize the data to

0:33:42.520 --> 0:33:45.280
<v Speaker 2>the extent possible between cities so that you can make

0:33:45.400 --> 0:33:48.560
<v Speaker 2>these comparisons insofar as they're possible to be made at all.

0:33:49.000 --> 0:33:51.760
<v Speaker 2>But that can definitely be a little challenging. Even with

0:33:51.920 --> 0:33:55.920
<v Speaker 2>that standardization. The one data point that we sort of

0:33:56.120 --> 0:33:58.920
<v Speaker 2>know is accurate and reflects, you know, what is actually

0:33:58.920 --> 0:34:01.880
<v Speaker 2>happening on the ground is murder. Because of the tragic

0:34:01.960 --> 0:34:04.320
<v Speaker 2>nature of defense. At the end of it, someone has

0:34:04.360 --> 0:34:06.560
<v Speaker 2>lost their life, and that tends to be reported to

0:34:07.000 --> 0:34:10.680
<v Speaker 2>many different authorities. So murder counts, murder rates tend to

0:34:10.680 --> 0:34:13.920
<v Speaker 2>reflect the actual number of those offenses committed in a community.

0:34:14.040 --> 0:34:16.520
<v Speaker 2>But the same might not be true of larceny. The

0:34:16.560 --> 0:34:18.960
<v Speaker 2>same might not be true of burglary in all cases,

0:34:19.000 --> 0:34:20.279
<v Speaker 2>you know I'm thinking of You know, I had my

0:34:20.360 --> 0:34:22.600
<v Speaker 2>bike stolen in Brooklyn, and I certainly never told the

0:34:22.640 --> 0:34:26.240
<v Speaker 2>police that bike was gone. So those sort of challenges

0:34:26.280 --> 0:34:28.839
<v Speaker 2>and reporting rate also might have an issue a way

0:34:28.880 --> 0:34:33.279
<v Speaker 2>of confounding comparisons between jurisdictions, It's not impossible. Those comparisons

0:34:33.320 --> 0:34:37.240
<v Speaker 2>are certainly meaningful, but they might not fully reflect facts

0:34:37.280 --> 0:34:39.160
<v Speaker 2>on the ground. They might come close to it. More.

0:34:39.760 --> 0:34:42.480
<v Speaker 1>You mentioned murder again, and we started talking about murder

0:34:42.520 --> 0:34:45.560
<v Speaker 1>in this happy episode we're having, and I wanted to

0:34:45.600 --> 0:34:48.680
<v Speaker 1>ask you, given this spike in the homicide rate in

0:34:48.760 --> 0:34:52.000
<v Speaker 1>twenty twenty, and it's cooled down subsequently, but it's still

0:34:52.080 --> 0:34:55.880
<v Speaker 1>higher than it had been. What aren't we doing about

0:34:56.200 --> 0:35:00.560
<v Speaker 1>homicide and violent crimes that could address that more directly?

0:35:01.440 --> 0:35:04.480
<v Speaker 2>That is the question. Two metrics that I've been thinking about,

0:35:04.520 --> 0:35:05.719
<v Speaker 2>and I'm going to refer to the work of some

0:35:05.719 --> 0:35:09.320
<v Speaker 2>other scholars in the process, are clearance rates and response times.

0:35:09.440 --> 0:35:12.279
<v Speaker 2>So the clearance rate is you can think of it

0:35:12.440 --> 0:35:15.360
<v Speaker 2>very roughly as the rate at which police solve an offense.

0:35:15.680 --> 0:35:18.560
<v Speaker 2>So it's the ratio of crimes in which an arrest

0:35:18.640 --> 0:35:20.799
<v Speaker 2>has been made or in which an arrest is impossible

0:35:21.200 --> 0:35:23.520
<v Speaker 2>to the number of crimes that are actually reported to them.

0:35:23.520 --> 0:35:25.480
<v Speaker 2>So if you have four murders in a given year,

0:35:25.520 --> 0:35:26.920
<v Speaker 2>and you make an arrest in three of them, your

0:35:26.920 --> 0:35:30.520
<v Speaker 2>clearance rate is seventy five percent. Unfortunately, seventy five percent

0:35:30.640 --> 0:35:33.279
<v Speaker 2>would be an outlier clearance rate in many cities in

0:35:33.280 --> 0:35:36.120
<v Speaker 2>this country. We've seen clearance rates below fifty percent in

0:35:36.160 --> 0:35:38.520
<v Speaker 2>some major cities, and in Chicago one year I think

0:35:38.520 --> 0:35:41.080
<v Speaker 2>it was below thirty percent. That suggests that, you know,

0:35:41.120 --> 0:35:43.520
<v Speaker 2>quite literally, people can get away with murder, and that's

0:35:43.680 --> 0:35:46.360
<v Speaker 2>very dispiriting, that's horrifying. I think we need to figure

0:35:46.360 --> 0:35:48.680
<v Speaker 2>out exactly what's happening and see if we can figure

0:35:48.680 --> 0:35:51.319
<v Speaker 2>out a way to increase clearance rates so people who

0:35:51.320 --> 0:35:55.360
<v Speaker 2>commit these most serious of offenses are actually brought to justice.

0:35:55.760 --> 0:35:58.920
<v Speaker 2>That's one factor. Anna Harvey, a researcher who I mentioned before,

0:35:59.000 --> 0:36:02.279
<v Speaker 2>is also some thought into studying police response times, which

0:36:02.320 --> 0:36:05.040
<v Speaker 2>in some jurisdictions can be quite high, and that also

0:36:05.040 --> 0:36:06.920
<v Speaker 2>can lead you a feeling of impunity. You know, if

0:36:06.920 --> 0:36:08.799
<v Speaker 2>by the time police show up it's an hour later,

0:36:09.080 --> 0:36:11.080
<v Speaker 2>it's much more difficult to solve that crime. So these

0:36:11.080 --> 0:36:13.560
<v Speaker 2>are two statistics that feed into each other, but I

0:36:13.600 --> 0:36:16.720
<v Speaker 2>don't want to talk exclusively about those two metrics. Another

0:36:16.760 --> 0:36:19.680
<v Speaker 2>promising intervention we've seen is something called the community violence

0:36:19.680 --> 0:36:23.600
<v Speaker 2>intervention programs. These are models where people from the community

0:36:23.800 --> 0:36:27.640
<v Speaker 2>build nonprofit organizations and employ people from the community to

0:36:27.719 --> 0:36:30.880
<v Speaker 2>help stop violence before it starts. So a model that

0:36:30.880 --> 0:36:33.279
<v Speaker 2>I've seen in Newark, New Jersey, which is quite near

0:36:33.320 --> 0:36:35.719
<v Speaker 2>to me, you will see people who have experienced in

0:36:35.719 --> 0:36:39.680
<v Speaker 2>the criminal justice system spend time in their communities, hear

0:36:39.719 --> 0:36:43.280
<v Speaker 2>what's happening here about nascent fights that might be brewing,

0:36:43.360 --> 0:36:45.839
<v Speaker 2>hear about conflicts that might be brewing, and then find

0:36:45.840 --> 0:36:48.920
<v Speaker 2>the people affected by those conflicts and try to put

0:36:48.920 --> 0:36:50.480
<v Speaker 2>a stop to it. Try to say, you know, I

0:36:50.560 --> 0:36:52.440
<v Speaker 2>understand what you're going through, but violence is not the

0:36:52.480 --> 0:36:55.920
<v Speaker 2>solution here. These sort of programs, when they work, they

0:36:55.920 --> 0:36:58.120
<v Speaker 2>are very effective. New York is one of very few

0:36:58.160 --> 0:37:00.920
<v Speaker 2>cities that didn't see homicide rates in create appreciably in

0:37:00.920 --> 0:37:03.879
<v Speaker 2>twenty twenty, for example. But they're very hard to get right,

0:37:03.960 --> 0:37:07.719
<v Speaker 2>and they typically require more money and more professionalization and

0:37:07.760 --> 0:37:10.360
<v Speaker 2>more staff than they're ever given. So this is a

0:37:10.400 --> 0:37:13.040
<v Speaker 2>promising option that I'm glad to say. Here's another piece

0:37:13.040 --> 0:37:15.600
<v Speaker 2>of good news. The Biden administration has actually taking a

0:37:15.640 --> 0:37:18.720
<v Speaker 2>serious interest and promoting and investing in ames.

0:37:18.760 --> 0:37:21.200
<v Speaker 1>I always like to ask guess what they've learned that

0:37:21.360 --> 0:37:23.399
<v Speaker 1>is an aha or a new thing to them about

0:37:23.440 --> 0:37:26.920
<v Speaker 1>the subject we're discussing. In your longtime observer of crime trends,

0:37:27.880 --> 0:37:31.680
<v Speaker 1>what did you learn watching the way that crime statistics

0:37:31.680 --> 0:37:33.960
<v Speaker 1>took shape in the early parts of the pandemic and

0:37:34.040 --> 0:37:36.600
<v Speaker 1>where they are now and the kind of public debate

0:37:36.640 --> 0:37:38.280
<v Speaker 1>we had around all of that.

0:37:38.280 --> 0:37:40.560
<v Speaker 2>That's a great question to think through. One thing I've

0:37:40.640 --> 0:37:44.920
<v Speaker 2>learned is statistics don't always reflect people's experience. We actually

0:37:44.960 --> 0:37:46.719
<v Speaker 2>see this in the economy as well. To bring it

0:37:46.840 --> 0:37:49.319
<v Speaker 2>near to a topic that always care about. The data

0:37:49.360 --> 0:37:51.680
<v Speaker 2>may show one thing, but people may feel another thing.

0:37:51.800 --> 0:37:54.799
<v Speaker 2>So there's a real gap often between people's perceptions of

0:37:54.840 --> 0:37:57.920
<v Speaker 2>safety and the actual data. And the reasons for that

0:37:57.960 --> 0:38:00.760
<v Speaker 2>may be really complicated. They may be because we've discussed

0:38:00.800 --> 0:38:04.239
<v Speaker 2>the data don't quantify the offenses that people are actually

0:38:04.280 --> 0:38:06.879
<v Speaker 2>worried about. But whatever the reason for that gap, we've

0:38:06.920 --> 0:38:09.239
<v Speaker 2>just got to take people's perceptions seriously. And it is

0:38:09.280 --> 0:38:12.239
<v Speaker 2>no answer to someone who's worried about their safety to say, well,

0:38:12.239 --> 0:38:14.920
<v Speaker 2>technically crime is down. That's non answer. That's not an

0:38:14.920 --> 0:38:17.800
<v Speaker 2>answer that helps bring us to a safer and more

0:38:17.840 --> 0:38:20.040
<v Speaker 2>just place. Games.

0:38:20.080 --> 0:38:22.360
<v Speaker 1>We're out of time. Thank you for coming on today.

0:38:22.640 --> 0:38:23.000
<v Speaker 2>Thank you.

0:38:24.160 --> 0:38:27.240
<v Speaker 1>Ames Groward is an expert on crime statistics and Senior

0:38:27.280 --> 0:38:29.960
<v Speaker 1>counsel at the Brennan Center for Justice at the NYU

0:38:30.160 --> 0:38:33.960
<v Speaker 1>Law School. Here at Crash Course, we believe that collisions

0:38:34.000 --> 0:38:39.120
<v Speaker 1>can be messy, impressive, challenging, surprising, and always instructive. In

0:38:39.160 --> 0:38:42.040
<v Speaker 1>today's Crash Course, I learned that the perception of crime

0:38:42.440 --> 0:38:45.840
<v Speaker 1>can almost be as influential for people as the reality

0:38:45.840 --> 0:38:48.960
<v Speaker 1>of crime itself and has to be taken into consideration

0:38:49.239 --> 0:38:53.000
<v Speaker 1>when we're coming up with policies to address crime. What

0:38:53.080 --> 0:38:55.319
<v Speaker 1>did you learn? We'd love to hear from you. You

0:38:55.320 --> 0:38:58.400
<v Speaker 1>can tweak at the Bloomberg Opinion, handle at Opinion or

0:38:58.480 --> 0:39:02.120
<v Speaker 1>me at Tim O'Brien using the hashtag Bloomberg Crash Course.

0:39:02.640 --> 0:39:05.480
<v Speaker 1>You can also subscribe to our show wherever you're listening

0:39:05.560 --> 0:39:08.160
<v Speaker 1>right now and leave us a review. It helps more

0:39:08.160 --> 0:39:11.200
<v Speaker 1>people find the show. This episode was produced by the

0:39:11.239 --> 0:39:15.680
<v Speaker 1>Indispensable and always Lawful Anna Maazarakis and me. Our supervising

0:39:15.719 --> 0:39:19.400
<v Speaker 1>producer is Magnus Hendrickson, and we had editing help from Sagebauman,

0:39:19.560 --> 0:39:24.080
<v Speaker 1>Jeff Grocott, Mike Nize and Christine Vanden Bilart. Blake Maples

0:39:24.080 --> 0:39:27.000
<v Speaker 1>does our sound engineering, and our original theme song was

0:39:27.040 --> 0:39:30.759
<v Speaker 1>composed by Luis Gara. I'm Tim O'Brien. We'll be back

0:39:30.840 --> 0:39:32.560
<v Speaker 1>next week with another Crash Course