1 00:00:15,356 --> 00:00:24,276 Speaker 1: Pushkin from Pushkin Industries. This is Deep Background, the show 2 00:00:24,316 --> 00:00:27,796 Speaker 1: where we explore the stories behind the stories in the news. 3 00:00:28,356 --> 00:00:32,996 Speaker 1: I'm Noah Feldman. Several weeks ago, the nation was shocked 4 00:00:33,196 --> 00:00:37,036 Speaker 1: and horrified to hear about shootings in Atlanta, Georgia, where 5 00:00:37,156 --> 00:00:40,396 Speaker 1: twenty one year old man went to three day spas 6 00:00:40,516 --> 00:00:44,516 Speaker 1: or massage parlors and killed eight people. Six of the 7 00:00:44,596 --> 00:00:48,676 Speaker 1: victims were of Asian origin, and many people are wondering 8 00:00:49,156 --> 00:00:52,036 Speaker 1: if and whether the gunmen will be charged with committing 9 00:00:52,036 --> 00:00:56,476 Speaker 1: a hate crime alongside charges of murder and aggravated assault. 10 00:00:57,276 --> 00:01:01,276 Speaker 1: But hate crime charges are relatively rare and they can 11 00:01:01,316 --> 00:01:05,636 Speaker 1: be challenging to prove in court. In twenty twenty, Georgia 12 00:01:05,676 --> 00:01:07,876 Speaker 1: became one of the last states in the country to 13 00:01:07,996 --> 00:01:11,756 Speaker 1: enact an anti hate crime That in turn raises some 14 00:01:11,876 --> 00:01:17,396 Speaker 1: core questions. Why are hate crimes charges so rare? How 15 00:01:17,556 --> 00:01:22,476 Speaker 1: should and do the police actually investigate and prosecute hate crime? 16 00:01:23,516 --> 00:01:26,036 Speaker 1: What should we do when there are many hate crimes 17 00:01:26,036 --> 00:01:29,956 Speaker 1: that may evade the legal criteria despite appearing on the 18 00:01:29,996 --> 00:01:34,516 Speaker 1: surface and maybe beneath to be racially motivated. All of 19 00:01:34,516 --> 00:01:37,236 Speaker 1: these are questions that connect to the theme of power, 20 00:01:37,636 --> 00:01:41,876 Speaker 1: which is our central theme this year On Deep Background, 21 00:01:42,356 --> 00:01:45,596 Speaker 1: they raise the question of the state's power to react 22 00:01:46,036 --> 00:01:49,276 Speaker 1: to racial and other forms of bias, and of the 23 00:01:49,316 --> 00:01:53,596 Speaker 1: capacity of our society more broadly, to exercise societal power 24 00:01:54,036 --> 00:01:58,276 Speaker 1: over and against the power of hate. Today's guest is 25 00:01:58,276 --> 00:02:03,116 Speaker 1: an expert on precisely these topics. Doctor Jeanine Bell is 26 00:02:03,156 --> 00:02:07,716 Speaker 1: professor of law at Indiana University. She's a nationally recognized 27 00:02:07,756 --> 00:02:11,356 Speaker 1: scholar in the area of pleasing and hate crime. She 28 00:02:11,396 --> 00:02:15,116 Speaker 1: wrote a book called Policing Hatred, Law Enforcement, Civil Rights 29 00:02:15,156 --> 00:02:18,836 Speaker 1: and Hate Crime, and ethnographic investigation of a big city 30 00:02:19,116 --> 00:02:23,396 Speaker 1: police hate crime unit. Today, on Deep Background, she's going 31 00:02:23,436 --> 00:02:26,436 Speaker 1: to talk to us about hate crimes laws, when and 32 00:02:26,476 --> 00:02:30,076 Speaker 1: how they came, about how they can and should be enforced, 33 00:02:30,676 --> 00:02:34,756 Speaker 1: and criticisms of those laws raised by some in the 34 00:02:34,796 --> 00:02:43,276 Speaker 1: advocacy community. Professor Bell, welcome to Deep Background. Ganine, thank 35 00:02:43,316 --> 00:02:48,156 Speaker 1: you so much for being here. Your topic is perennially significant, 36 00:02:48,876 --> 00:02:52,796 Speaker 1: and it's also very significant in the present moment. What 37 00:02:53,036 --> 00:02:58,116 Speaker 1: drew you to this particular subject of expertise and study. 38 00:02:58,116 --> 00:03:01,036 Speaker 1: It's it's importance is unquestioned, and it's more fortunate that 39 00:03:01,036 --> 00:03:03,836 Speaker 1: you are working on it. But what personally for you 40 00:03:03,876 --> 00:03:09,436 Speaker 1: made this your focus. It's interesting, you know, and this 41 00:03:09,796 --> 00:03:13,036 Speaker 1: has a lot to do with my current career as 42 00:03:13,036 --> 00:03:16,836 Speaker 1: a law professor. I was a political science graduate student. 43 00:03:17,196 --> 00:03:20,196 Speaker 1: It was early in nineteen nineties. I was in the 44 00:03:20,276 --> 00:03:24,316 Speaker 1: dentist's office and I picked up Time magazine and they 45 00:03:24,356 --> 00:03:30,236 Speaker 1: had a story about a black tourist visiting Disneyland, I believe, 46 00:03:30,516 --> 00:03:35,516 Speaker 1: who had been set on fire by some whites, and 47 00:03:35,676 --> 00:03:40,036 Speaker 1: they called it a hate crime. I was really surprised, 48 00:03:40,756 --> 00:03:44,676 Speaker 1: you know, I was familiar with acts of racist violence, 49 00:03:44,716 --> 00:03:48,196 Speaker 1: but I'd never heard any notion of hate crime. So 50 00:03:48,236 --> 00:03:50,876 Speaker 1: I decided to look into it, and I looked at 51 00:03:50,916 --> 00:03:54,476 Speaker 1: the literature, all of the literature about this term hate crime. 52 00:03:54,956 --> 00:04:01,596 Speaker 1: It was right between rav in Wisconsin versus Mitchell and 53 00:04:01,916 --> 00:04:08,876 Speaker 1: all of the legal literature. You know, law professor's writings said, Oh, 54 00:04:08,876 --> 00:04:12,676 Speaker 1: this silly. Nobody knows what a hate crime is. You 55 00:04:12,676 --> 00:04:15,556 Speaker 1: can never tell whether something is a hate crime or not. 56 00:04:15,916 --> 00:04:23,036 Speaker 1: And this is still twenty five years later, something that 57 00:04:23,236 --> 00:04:27,956 Speaker 1: is a huge portion of the First Amendment literature. We 58 00:04:28,036 --> 00:04:32,156 Speaker 1: can't figure out whether something is bias motivated. So that's 59 00:04:32,236 --> 00:04:35,556 Speaker 1: why I do this. I wanted to ask you just 60 00:04:35,596 --> 00:04:39,316 Speaker 1: to begin by giving us your working definition of what 61 00:04:39,516 --> 00:04:42,556 Speaker 1: counts as a hate crime or a bias crime from 62 00:04:42,596 --> 00:04:49,956 Speaker 1: your perspective, Okay, hate crimes are crimes motivated by bias 63 00:04:50,036 --> 00:04:56,956 Speaker 1: on the basis of race, religion, sexual orientation, gender, gender identity. 64 00:04:57,596 --> 00:05:02,356 Speaker 1: The precise categories, and it's important that you understand that 65 00:05:02,396 --> 00:05:09,436 Speaker 1: they are categories, not groups. The precise categories vary by stack. Shoot, 66 00:05:09,836 --> 00:05:13,996 Speaker 1: whatever hate crime statute you're looking at, it's mostly federal 67 00:05:14,036 --> 00:05:18,116 Speaker 1: in state, and there are some states, like the state 68 00:05:18,156 --> 00:05:23,116 Speaker 1: I'm in right now, Indiana, that prevent localities from enacting 69 00:05:24,236 --> 00:05:28,196 Speaker 1: their own legislation in the context of criminal law. So 70 00:05:29,076 --> 00:05:32,716 Speaker 1: even if we wish to, and I think that my 71 00:05:32,916 --> 00:05:37,396 Speaker 1: particular city would probably wish to, particularly for the number 72 00:05:37,436 --> 00:05:40,036 Speaker 1: of years that we did not have hate crime legislation, 73 00:05:40,836 --> 00:05:45,236 Speaker 1: enact something, they cannot. They are forbidden by the legislature 74 00:05:45,316 --> 00:05:49,676 Speaker 1: from doing something like that. When did federal or state 75 00:05:49,716 --> 00:05:55,556 Speaker 1: governments start enacting laws that specifically punish hate crimes. In 76 00:05:55,596 --> 00:06:00,916 Speaker 1: the nineteen nineties, most of the statutes were passed. This 77 00:06:01,236 --> 00:06:06,636 Speaker 1: happened after the creation of the nineteen Hate Crime Statistics SECTS, 78 00:06:06,956 --> 00:06:11,316 Speaker 1: which was a federal piece of legislation, So mostly in 79 00:06:11,356 --> 00:06:16,876 Speaker 1: the nineteen nineties before that time, only Connecticut had biased 80 00:06:16,916 --> 00:06:19,636 Speaker 1: crime legislation, and had Connecticut had it for a long time, 81 00:06:19,756 --> 00:06:22,356 Speaker 1: or was it relatively new there as well, mid nineteen eighties. 82 00:06:22,916 --> 00:06:27,116 Speaker 1: So these are all relatively recent in grand historical terms, 83 00:06:27,596 --> 00:06:29,836 Speaker 1: although I guess there's now thirty years, almost thirty years 84 00:06:29,876 --> 00:06:33,116 Speaker 1: of experience with a lot of them. Both yes and no, 85 00:06:34,076 --> 00:06:37,636 Speaker 1: they're similar. Some of them are similar to federal civil 86 00:06:37,716 --> 00:06:41,956 Speaker 1: rights legislation that we've had, you know, for one hundred 87 00:06:42,036 --> 00:06:47,876 Speaker 1: years or so, similar in what sense, similar in targeting 88 00:06:48,596 --> 00:06:54,956 Speaker 1: a particular type of terrorism bias motivated violence, and civil 89 00:06:55,036 --> 00:07:00,956 Speaker 1: rights acts targets motivated violence, but without the categories. The 90 00:07:00,996 --> 00:07:04,956 Speaker 1: innovation of hate crime is the adding in of the 91 00:07:04,996 --> 00:07:11,476 Speaker 1: categories bias on the basis of race, religions, orientation, ethnicity, etc. 92 00:07:12,716 --> 00:07:16,116 Speaker 1: Whereas the Civil Rights Statute said that it's a crime 93 00:07:16,196 --> 00:07:19,916 Speaker 1: to interfere with a person's exercise of his or her 94 00:07:20,116 --> 00:07:23,276 Speaker 1: civil rights, and it just so happened that many people 95 00:07:23,276 --> 00:07:25,876 Speaker 1: who are committing such crimes are doing so on the 96 00:07:25,916 --> 00:07:32,556 Speaker 1: basis of race, or exactly precisely, that is precisely the issue. 97 00:07:32,756 --> 00:07:34,756 Speaker 1: I have a lot of, you know, in the weeds 98 00:07:34,836 --> 00:07:36,316 Speaker 1: questions which will come to it a second but I 99 00:07:36,396 --> 00:07:38,676 Speaker 1: wanted to ask you if at the biggest level, you 100 00:07:38,756 --> 00:07:43,676 Speaker 1: had to say, how successful has this body of legislation been? 101 00:07:43,756 --> 00:07:45,276 Speaker 1: And this is the body of legislation that I think 102 00:07:45,276 --> 00:07:48,636 Speaker 1: you've studied as deeply as anyone living. What's the measure 103 00:07:48,676 --> 00:07:51,756 Speaker 1: of whether laws like this are doing their job? And 104 00:07:51,796 --> 00:07:54,956 Speaker 1: then by whatever measure that is, are they doing their job? 105 00:07:56,076 --> 00:08:01,636 Speaker 1: That's a hard question. It's hard first because this is 106 00:08:01,876 --> 00:08:08,316 Speaker 1: violence that goes largely unpunished, but for the existence of 107 00:08:08,356 --> 00:08:13,996 Speaker 1: these particular killer pieces of legislation. Take cross burning, for instance, 108 00:08:14,916 --> 00:08:19,636 Speaker 1: if someone burns across on my lawn, then there are 109 00:08:19,916 --> 00:08:26,276 Speaker 1: very few criminal statutes that you can use to prosecute them. 110 00:08:27,796 --> 00:08:33,476 Speaker 1: For arson, for example, you need a burned spot, right, 111 00:08:34,036 --> 00:08:36,396 Speaker 1: and a lot of times when someone burns across there 112 00:08:36,436 --> 00:08:40,076 Speaker 1: isn't a burned spot. And there was a famous case 113 00:08:40,196 --> 00:08:43,796 Speaker 1: that I'm sure you have heard of in which the 114 00:08:43,876 --> 00:08:48,836 Speaker 1: perpetrators burned across r A V burned across on the 115 00:08:48,916 --> 00:08:52,036 Speaker 1: lawn of the black family that it integrated the neighborhoods. 116 00:08:52,716 --> 00:08:56,716 Speaker 1: It was actually part of a reign of terror that 117 00:08:56,836 --> 00:09:02,556 Speaker 1: these white supremacists had directed at the family. They'd done 118 00:09:02,596 --> 00:09:06,636 Speaker 1: other things, but they eventually burned across on the lawn 119 00:09:06,636 --> 00:09:12,356 Speaker 1: of the family Middle and ninth, and the prosecutor chose 120 00:09:12,596 --> 00:09:19,996 Speaker 1: to use a hate crime statute because there wasn't really 121 00:09:20,316 --> 00:09:26,436 Speaker 1: much else that wasn't a felony. The adult involved had 122 00:09:26,516 --> 00:09:31,436 Speaker 1: pled to misdemeanors, so they didn't want to charge the 123 00:09:31,556 --> 00:09:38,116 Speaker 1: juvenile involved with a felony, so they chose this hate 124 00:09:38,116 --> 00:09:41,996 Speaker 1: crime statute because there isn't much else you can use 125 00:09:42,316 --> 00:09:47,676 Speaker 1: for cross burning. And is that a typical situation. I mean, 126 00:09:48,556 --> 00:09:50,756 Speaker 1: that's fascinating what you're telling me, because it runs sort 127 00:09:50,796 --> 00:09:52,956 Speaker 1: of counter to my own intuition, which obviously was wrong. 128 00:09:52,996 --> 00:09:56,076 Speaker 1: I mean, my intuition was something like, if it is 129 00:09:57,196 --> 00:10:01,716 Speaker 1: under these statutes, for example, a crime to beat someone 130 00:10:01,796 --> 00:10:05,316 Speaker 1: up on the basis of racial bias, then you could 131 00:10:05,436 --> 00:10:07,996 Speaker 1: charge them already with the beating them beating the person up, 132 00:10:08,276 --> 00:10:10,276 Speaker 1: and then you could a ad and enhanced the sentence 133 00:10:10,316 --> 00:10:13,156 Speaker 1: and add a separate crime the for the bias motivations. 134 00:10:13,196 --> 00:10:14,916 Speaker 1: That was my intuition. But what I hear you saying 135 00:10:14,956 --> 00:10:18,676 Speaker 1: is maybe that intuition is backwards. All right, You've zeroed 136 00:10:18,676 --> 00:10:22,036 Speaker 1: in on something important, but you're still not quite correct. 137 00:10:22,676 --> 00:10:28,836 Speaker 1: Cross burning is unusual in the context of hate crime 138 00:10:29,636 --> 00:10:34,796 Speaker 1: and the sort of lack of overlap with the regular 139 00:10:34,836 --> 00:10:40,916 Speaker 1: criminal law. What about assault bias motivated assault? Assuming it 140 00:10:41,076 --> 00:10:45,836 Speaker 1: is a low level crime, right, meaning I'm not seriously injured. 141 00:10:46,356 --> 00:10:50,716 Speaker 1: The perpetrator beats me up terribly, but you know, I'm 142 00:10:50,756 --> 00:10:54,756 Speaker 1: not really seriously I mean, it's not life threatening, and 143 00:10:54,956 --> 00:11:00,036 Speaker 1: it falls into the category of low level assault. You 144 00:11:00,076 --> 00:11:04,316 Speaker 1: have a couple of problems with that. The first is 145 00:11:04,916 --> 00:11:09,436 Speaker 1: low level crimes are largely not investigated by the police. 146 00:11:09,796 --> 00:11:15,636 Speaker 1: They just don't. Criminologists estimate that nearly eighty percent of 147 00:11:15,716 --> 00:11:19,956 Speaker 1: low level crimes are not investigated by the police. It 148 00:11:20,036 --> 00:11:25,396 Speaker 1: doesn't really matter that this is an assault that targets 149 00:11:25,436 --> 00:11:29,676 Speaker 1: me because of my background. It's still a low level sault, 150 00:11:29,956 --> 00:11:34,156 Speaker 1: and this is not a priority for law enforcement officers. 151 00:11:34,636 --> 00:11:39,676 Speaker 1: So I've just been terrorized and the police are not 152 00:11:39,796 --> 00:11:43,276 Speaker 1: even going to try to figure out who did it, 153 00:11:43,556 --> 00:11:48,356 Speaker 1: let alone try to catch the perpetrator. So I have 154 00:11:48,516 --> 00:11:55,596 Speaker 1: been terrorized, and that same perpetrator could victimize somebody else 155 00:11:56,276 --> 00:12:00,036 Speaker 1: and I could certainly could be victimized again. So one 156 00:12:00,116 --> 00:12:03,156 Speaker 1: of the things that hate crime laws do is they 157 00:12:03,236 --> 00:12:09,436 Speaker 1: create an incentive for law enforcement officers to investigate times 158 00:12:09,436 --> 00:12:14,236 Speaker 1: that they would not. I call that a success because 159 00:12:14,436 --> 00:12:19,156 Speaker 1: we as society have said that these crimes are more damaging, 160 00:12:19,836 --> 00:12:24,876 Speaker 1: so they should be investigated. Help me fill in how 161 00:12:25,596 --> 00:12:28,756 Speaker 1: proof gets constructed by the police and argued by the 162 00:12:28,836 --> 00:12:33,716 Speaker 1: prosecutors and considered by the jury in cases where it's 163 00:12:33,796 --> 00:12:37,516 Speaker 1: not flatly obvious on the surface. So maybe we could 164 00:12:37,516 --> 00:12:41,076 Speaker 1: take as an example the Atlanta shootings that are fresh 165 00:12:41,076 --> 00:12:45,356 Speaker 1: in our minds, where a disproportioned number of the victims 166 00:12:45,636 --> 00:12:48,476 Speaker 1: were Asian American and that immediately led to a national 167 00:12:48,476 --> 00:12:53,196 Speaker 1: discussion about bias and hate against Asian Americans, but in 168 00:12:53,236 --> 00:12:58,716 Speaker 1: which it's also conceivable that the shooters motives were not 169 00:12:59,116 --> 00:13:05,076 Speaker 1: tagged specifically to the ethnic or racial characteristics of the victims, 170 00:13:05,116 --> 00:13:07,356 Speaker 1: which is not to say that they weren't, just to 171 00:13:07,396 --> 00:13:10,876 Speaker 1: say that it seems conceive that there's another explanation. How 172 00:13:10,916 --> 00:13:13,116 Speaker 1: would we go about figuring out the way the system 173 00:13:13,116 --> 00:13:16,596 Speaker 1: would determine whether those crimes, which were crimes of murder 174 00:13:16,596 --> 00:13:19,156 Speaker 1: and we're serious crimes and will be taken seriously in 175 00:13:19,236 --> 00:13:23,356 Speaker 1: terms of identification and enforcement, whether that is in addition 176 00:13:24,076 --> 00:13:27,196 Speaker 1: a bias crime that should be charged as such. Well, 177 00:13:27,236 --> 00:13:32,156 Speaker 1: I'm glad you brought up that case, in particular, if 178 00:13:32,236 --> 00:13:38,116 Speaker 1: that case had been investigated by police officers who knew 179 00:13:38,436 --> 00:13:44,116 Speaker 1: really anything about a hate crime, they say, all right, 180 00:13:44,396 --> 00:13:50,316 Speaker 1: so there's a disproportionate racial group of individuals who may 181 00:13:50,356 --> 00:13:54,476 Speaker 1: have been targeted because of bias. So what do we 182 00:13:54,516 --> 00:13:58,756 Speaker 1: need to do. Well, we need to interview survivors. Let's 183 00:13:58,956 --> 00:14:05,956 Speaker 1: interview survivors about what happened during the crime. The individuals 184 00:14:05,996 --> 00:14:10,396 Speaker 1: who are survivors, their native language was not English. So 185 00:14:10,476 --> 00:14:15,476 Speaker 1: you send in individuals who speak to the grieving survivors, 186 00:14:15,476 --> 00:14:21,796 Speaker 1: grieving and traumatize survivors in their language, right, and you 187 00:14:21,876 --> 00:14:26,876 Speaker 1: gather all the evidence of what happened during the crime. 188 00:14:27,196 --> 00:14:32,156 Speaker 1: So if you look at the for instance, Korean language press, 189 00:14:33,236 --> 00:14:39,876 Speaker 1: which actually did this, unlike law enforcement officers, they have 190 00:14:39,956 --> 00:14:45,636 Speaker 1: a different story to tell about what happened. When the 191 00:14:45,676 --> 00:14:52,836 Speaker 1: perpetrator came to the establishments, perpetrator said things like, and 192 00:14:53,036 --> 00:14:56,316 Speaker 1: you can see this in the press. They said the 193 00:14:56,356 --> 00:15:02,556 Speaker 1: perpetrator was there to kill all Asians. That's evidence of motivation. Right. 194 00:15:02,836 --> 00:15:08,076 Speaker 1: You don't just interview the perpetrator and ask so why'd 195 00:15:08,076 --> 00:15:14,956 Speaker 1: you do this? That's proper hate crime investigation. So you 196 00:15:15,116 --> 00:15:20,716 Speaker 1: look in every location for evidence of motivation, just as 197 00:15:20,796 --> 00:15:25,076 Speaker 1: you might any other crime. Murder for hire, for instance, 198 00:15:25,516 --> 00:15:29,796 Speaker 1: you don't just act ask the perpetrator so, hey, anybody 199 00:15:29,796 --> 00:15:44,996 Speaker 1: pay you to do this, We'll be right back. So 200 00:15:45,996 --> 00:15:51,356 Speaker 1: interviewing survivors, doing so in a culturally and linguistically sensitive 201 00:15:51,396 --> 00:15:55,396 Speaker 1: way is a crucial element. What else should what else 202 00:15:55,476 --> 00:15:59,516 Speaker 1: is best practices for law enforcement to try to gather motive? 203 00:15:59,556 --> 00:16:03,596 Speaker 1: I mean, is profiling a perpetrator, not by interviewing the perpetrator, 204 00:16:03,676 --> 00:16:06,916 Speaker 1: but by talking to people a meaningful undertaking or is 205 00:16:06,916 --> 00:16:12,516 Speaker 1: that more misleading than anything else? It's likely misleading, but 206 00:16:12,716 --> 00:16:16,156 Speaker 1: you do talk to the perpetrators and moreover, one of 207 00:16:16,196 --> 00:16:19,196 Speaker 1: the things that I think the literature is often really 208 00:16:19,236 --> 00:16:28,116 Speaker 1: confused about is how secretive perpetrators are about their motives. 209 00:16:28,156 --> 00:16:34,316 Speaker 1: In these cases. These are often individuals who have an 210 00:16:34,476 --> 00:16:40,836 Speaker 1: ideological commitment to committing the crime. It's not as if 211 00:16:41,356 --> 00:16:47,236 Speaker 1: they want to hide they're bias. And this is something 212 00:16:47,316 --> 00:16:51,156 Speaker 1: that I explored with police when I was writing my 213 00:16:51,236 --> 00:16:54,476 Speaker 1: first book, because I said, so, do you have all 214 00:16:54,476 --> 00:16:58,236 Speaker 1: these perpetrators who you know, don't want to tell you 215 00:16:58,756 --> 00:17:03,156 Speaker 1: that they were biased? And the law enforcement office of no, 216 00:17:03,596 --> 00:17:07,316 Speaker 1: of course not. They're people who are biased, so they 217 00:17:07,356 --> 00:17:10,516 Speaker 1: don't hide it. What's the right way to think about 218 00:17:10,556 --> 00:17:16,116 Speaker 1: it where a perpetrator has let's call them mixed motives, 219 00:17:16,196 --> 00:17:19,156 Speaker 1: and where a prosecutor would have to try to, I guess, 220 00:17:19,716 --> 00:17:22,996 Speaker 1: impose a logic on them for purposes of convincing a 221 00:17:23,076 --> 00:17:26,596 Speaker 1: jury that might not fully be present in the thought 222 00:17:26,596 --> 00:17:29,956 Speaker 1: world of the person who's the perpetrator. So I mean, 223 00:17:29,996 --> 00:17:33,276 Speaker 1: imagine not this case, but imagine a case where you know, 224 00:17:33,356 --> 00:17:37,076 Speaker 1: someone is very a male perpetrator is extremely angry at 225 00:17:37,156 --> 00:17:42,356 Speaker 1: sex workers who are women and are also members of 226 00:17:42,356 --> 00:17:47,756 Speaker 1: a particular racial group, and goes and kills them. And 227 00:17:48,556 --> 00:17:51,756 Speaker 1: you know, where there isn't let's say, contemporaneous evidence that 228 00:17:51,796 --> 00:17:54,076 Speaker 1: he said, you know, I'm here to kill all Asians 229 00:17:54,116 --> 00:17:58,076 Speaker 1: are similar. But where you know, we could infer from 230 00:17:58,076 --> 00:18:01,116 Speaker 1: the circumstances that there seems to be some nature of 231 00:18:01,156 --> 00:18:05,636 Speaker 1: hatred against women, there seems very probably to be racial hatred. 232 00:18:05,796 --> 00:18:08,476 Speaker 1: What's the best way to think about the nature of 233 00:18:08,556 --> 00:18:13,596 Speaker 1: bias where the hate is against some class of people 234 00:18:13,916 --> 00:18:17,676 Speaker 1: that overlaps very much with one of the protected categories 235 00:18:17,716 --> 00:18:23,756 Speaker 1: in the hate crimes legislation. Because it's a legal system, 236 00:18:23,956 --> 00:18:28,116 Speaker 1: you need evidence of bias motivation, and in the mythical 237 00:18:29,076 --> 00:18:35,196 Speaker 1: case that you've created, there is not evidence of bias motivation. 238 00:18:35,996 --> 00:18:39,356 Speaker 1: That wouldn't suffice if someone says, you know, I'm really 239 00:18:39,396 --> 00:18:41,916 Speaker 1: angry at women, that's not I mean, that's not sufficient 240 00:18:42,796 --> 00:18:49,956 Speaker 1: motivated by bias? Right that crime? You know, we require particularization. 241 00:18:52,236 --> 00:18:58,556 Speaker 1: Was that act motivated by your bias? We need evidence? 242 00:18:58,756 --> 00:19:02,956 Speaker 1: And moreover, prosecutors are conservative. Of course, there are cases 243 00:19:03,036 --> 00:19:08,116 Speaker 1: that I see plenty of evidence of bias, statements by 244 00:19:08,196 --> 00:19:17,156 Speaker 1: perpetrators indicating they targeted the people because of their background, 245 00:19:17,356 --> 00:19:19,916 Speaker 1: and prosecutors says, listen, a jury's not going to like this, 246 00:19:20,556 --> 00:19:25,556 Speaker 1: and so doesn't bring charges hate crime charges. Do you 247 00:19:25,596 --> 00:19:29,036 Speaker 1: have a feeling that in general, law enforcement, including prosecutors, 248 00:19:29,036 --> 00:19:32,316 Speaker 1: are doing a reasonable job relative to what they could 249 00:19:32,316 --> 00:19:34,076 Speaker 1: be doing under the law, or do you think they're 250 00:19:34,676 --> 00:19:38,876 Speaker 1: under using the powers that the laws give them. Vastly 251 00:19:38,996 --> 00:19:43,636 Speaker 1: under using the powers that the law gives them. Many 252 00:19:43,716 --> 00:19:49,156 Speaker 1: more cases could be prosecuted as hate crime cases. Prosecutors, however, 253 00:19:49,236 --> 00:19:53,036 Speaker 1: are not the largest problem. The largest problem stems from 254 00:19:53,436 --> 00:19:59,436 Speaker 1: law enforcement. Law enforcement not presenting prosecutors with merely enough 255 00:19:59,476 --> 00:20:04,996 Speaker 1: cases because they're low level crimes that don't get investigated, 256 00:20:06,676 --> 00:20:10,556 Speaker 1: they are not reported to beliefs that it's a problem. 257 00:20:10,716 --> 00:20:15,676 Speaker 1: Eighty six point one percent of law enforcement agencies in 258 00:20:15,756 --> 00:20:20,876 Speaker 1: this country said in twenty nineteen that no hate crimes 259 00:20:20,876 --> 00:20:25,556 Speaker 1: that had occurred in their jurisdiction, and every other figure, 260 00:20:25,756 --> 00:20:32,196 Speaker 1: including victim surveys by the federal government, suggests many more 261 00:20:32,636 --> 00:20:38,236 Speaker 1: hate crimes. I'm kind of shocked by that number. Eighty 262 00:20:38,236 --> 00:20:43,516 Speaker 1: six point one percent of jurisdictions reported no hate crimes. Yeah, 263 00:20:43,676 --> 00:20:48,516 Speaker 1: sounds wildly implausible. Yeah, now, what's the solution to this 264 00:20:48,596 --> 00:20:51,876 Speaker 1: structural problem, not the reporting problem, but the under enforcement problem. 265 00:20:52,476 --> 00:20:58,556 Speaker 1: The solution is actually a solution that doesn't really involve police, 266 00:20:58,636 --> 00:21:06,876 Speaker 1: but rather citizens. You need victims advocacy organizations, say the 267 00:21:06,996 --> 00:21:13,036 Speaker 1: Game Lesbian Anti Violence Project for instance, to start believing 268 00:21:14,276 --> 00:21:21,996 Speaker 1: that police can do something and developing relationships with the police. 269 00:21:22,596 --> 00:21:27,396 Speaker 1: Places where hate crime law enforcement works best are places 270 00:21:27,436 --> 00:21:31,236 Speaker 1: that say, all right, we're going to use the resources 271 00:21:31,316 --> 00:21:36,196 Speaker 1: that we have, which include police departments, to find the perpetrator, 272 00:21:36,996 --> 00:21:44,956 Speaker 1: stop this terrorism directed at individuals, and prosecute the crimes. 273 00:21:45,036 --> 00:21:51,836 Speaker 1: So in places where I saw organize victims advocacy organizations 274 00:21:51,836 --> 00:21:56,196 Speaker 1: that call the police and said, hey, you know, we 275 00:21:56,276 --> 00:21:59,636 Speaker 1: have a person in our community who's been victimized by 276 00:21:59,676 --> 00:22:02,956 Speaker 1: hate crime, and what are you doing about it? Exactly? 277 00:22:04,036 --> 00:22:12,316 Speaker 1: Those police departments are incentivized to investigate crime, create bias units, 278 00:22:13,356 --> 00:22:18,676 Speaker 1: press prosecutors, present cases to prosecutors, because police are the 279 00:22:18,676 --> 00:22:24,316 Speaker 1: ones responsible for investigation. Prosecutors don't do this. Can I 280 00:22:24,356 --> 00:22:27,956 Speaker 1: ask you a slightly bigger picture philosophical question that I 281 00:22:28,036 --> 00:22:32,156 Speaker 1: was really puzzling over. I take it that the thrust 282 00:22:32,156 --> 00:22:35,756 Speaker 1: of your research is that the statutes are pretty good. 283 00:22:36,316 --> 00:22:39,716 Speaker 1: The challenge is really in law enforcement. As you were saying, 284 00:22:39,716 --> 00:22:42,396 Speaker 1: there might be some tools to enable advocacy groups in 285 00:22:42,396 --> 00:22:44,916 Speaker 1: civil society groups to help raise the consciousness of law 286 00:22:44,956 --> 00:22:48,036 Speaker 1: enforcement and put put some political pressure on them to 287 00:22:48,036 --> 00:22:52,716 Speaker 1: create bias units and improve enforcement. And everything that you 288 00:22:52,796 --> 00:22:56,476 Speaker 1: said makes perfect logical sense to me. Then I think 289 00:22:56,516 --> 00:23:01,836 Speaker 1: of what some of my most committed and idealistic students 290 00:23:02,076 --> 00:23:05,236 Speaker 1: in that I teach in my law school are saying 291 00:23:05,276 --> 00:23:07,396 Speaker 1: these days, and I bet that's the same as true 292 00:23:07,396 --> 00:23:11,436 Speaker 1: for some of your students. They're talking about abolition of 293 00:23:11,476 --> 00:23:17,596 Speaker 1: police departments, they're talking about abolition of prisons, and beyond 294 00:23:17,636 --> 00:23:23,716 Speaker 1: those concrete proposals, they're also expressing a deep skepticism of 295 00:23:23,756 --> 00:23:28,276 Speaker 1: the very capacity of police and law enforcement ever to 296 00:23:29,196 --> 00:23:34,716 Speaker 1: overcome systemic racial bias, and in turn, that's causing these 297 00:23:34,716 --> 00:23:38,716 Speaker 1: students to be very skeptical of criminal law as a 298 00:23:38,756 --> 00:23:45,036 Speaker 1: tool for improving equal outcomes in society. And so the 299 00:23:45,076 --> 00:23:49,796 Speaker 1: philosophical question is, how do you relate to these movements 300 00:23:50,036 --> 00:23:53,796 Speaker 1: with respect to your own research project, which has been 301 00:23:53,836 --> 00:23:58,516 Speaker 1: so focused on facilitating the police doing a better job 302 00:23:58,556 --> 00:24:02,116 Speaker 1: than they are doing. So again, not that you're giving them, 303 00:24:02,196 --> 00:24:04,516 Speaker 1: giving the police some free paths. To the contrary, you're 304 00:24:04,556 --> 00:24:06,396 Speaker 1: calling on them to do their jobs. But if they 305 00:24:06,396 --> 00:24:08,996 Speaker 1: were to do their jobs, it would mean more law enforcement, 306 00:24:09,476 --> 00:24:14,956 Speaker 1: more criminal laws, and potentially more prison sentences. All right, 307 00:24:15,476 --> 00:24:21,156 Speaker 1: So do you think Dylan Roof should be walking around? 308 00:24:21,716 --> 00:24:25,716 Speaker 1: Dylan Roof is the young man who went to the 309 00:24:25,836 --> 00:24:33,516 Speaker 1: church in Charleston, South Carolina and killed I believe nine 310 00:24:34,396 --> 00:24:40,116 Speaker 1: people at a Bible study African Americans, all of them 311 00:24:41,116 --> 00:24:45,716 Speaker 1: praying or praying and study Bible. So I certainly do not. 312 00:24:45,956 --> 00:24:50,116 Speaker 1: But I'm also not a part of the abolition movement. 313 00:24:50,716 --> 00:24:54,116 Speaker 1: So there's a role then for police here, and that's 314 00:24:54,276 --> 00:25:00,876 Speaker 1: the first mistake that those abolitionists make, right, we have 315 00:25:00,916 --> 00:25:05,356 Speaker 1: a role for they want law enforcement all they do, 316 00:25:05,476 --> 00:25:10,956 Speaker 1: and they want law enforcement in this contact right very 317 00:25:10,996 --> 00:25:17,276 Speaker 1: clearly a hate crime. Law enforcement is the reason Dylan 318 00:25:17,356 --> 00:25:23,356 Speaker 1: Roof is not walking around. I think that you can 319 00:25:23,476 --> 00:25:31,196 Speaker 1: extrapolate Dylan Roof to the person the kid who decides 320 00:25:31,356 --> 00:25:38,236 Speaker 1: they want to leave racist flyers on my lawn or 321 00:25:38,356 --> 00:25:44,156 Speaker 1: burn across on my lawn, scrawl something on my garage door. 322 00:25:45,316 --> 00:25:49,796 Speaker 1: I think that there's a role for law enforcement to 323 00:25:50,556 --> 00:25:56,076 Speaker 1: be involved in that. And to the concern about, well, 324 00:25:56,076 --> 00:26:00,036 Speaker 1: we can't trust law enforcement to do this, I've seen 325 00:26:00,156 --> 00:26:05,116 Speaker 1: law enforcement do this, and if we properly incentivize law 326 00:26:05,236 --> 00:26:10,756 Speaker 1: enforcement and provide them this sport they need to do this, 327 00:26:11,516 --> 00:26:17,836 Speaker 1: they can actually be quite good victim advocates. So I 328 00:26:17,836 --> 00:26:22,596 Speaker 1: think that it's important not to throw the baby out 329 00:26:22,636 --> 00:26:27,316 Speaker 1: with the bathwater. There are law enforcement officers who are 330 00:26:28,916 --> 00:26:34,316 Speaker 1: quite biased. We know this, right, but it doesn't mean 331 00:26:34,756 --> 00:26:39,956 Speaker 1: that we should not expect law enforcement officers who don't 332 00:26:39,996 --> 00:26:43,636 Speaker 1: have such biases to serve the public in the way 333 00:26:43,956 --> 00:26:50,116 Speaker 1: that the legislators have determined they should. When you make 334 00:26:50,156 --> 00:26:57,956 Speaker 1: that very compelling response to actual abolitionists, prison abolitionists, or 335 00:26:57,956 --> 00:27:01,516 Speaker 1: police abolitionists, if you have had occasion too, would imagine 336 00:27:01,516 --> 00:27:04,316 Speaker 1: you probably have. How is it taken? I mean, it 337 00:27:04,396 --> 00:27:06,836 Speaker 1: seems so compelling to me, But again, I'm not starting 338 00:27:06,836 --> 00:27:08,996 Speaker 1: from the same position as some of those critics of this. 339 00:27:09,236 --> 00:27:17,116 Speaker 1: They respond by saying, listen, we can't trust law enforcement 340 00:27:17,236 --> 00:27:26,156 Speaker 1: because they lock up a disproportionate number of African Americans 341 00:27:26,156 --> 00:27:31,316 Speaker 1: for hate crime. And I say, well, actually, I've looked 342 00:27:31,356 --> 00:27:34,676 Speaker 1: at that, right, I've looked at law enforcement that was 343 00:27:34,756 --> 00:27:40,116 Speaker 1: actually doing the real work of investigating hate crime, and 344 00:27:40,236 --> 00:27:45,236 Speaker 1: I did not see evidence of that. Show me law 345 00:27:45,356 --> 00:27:49,476 Speaker 1: enforcement that is actually doing its job with respect to 346 00:27:49,556 --> 00:27:58,036 Speaker 1: hate crime, and show me that they are disproportionately enforcing 347 00:27:58,036 --> 00:28:03,556 Speaker 1: the law. You are just assuming because large numbers of 348 00:28:03,636 --> 00:28:08,436 Speaker 1: African Americans, more than you think should be, are being arrested. 349 00:28:08,756 --> 00:28:11,756 Speaker 1: And I say that's a problem that you need to 350 00:28:11,796 --> 00:28:17,396 Speaker 1: correct with law enforcement, as opposed to again saying we 351 00:28:17,436 --> 00:28:23,916 Speaker 1: shouldn't do this at all. When you work with law enforcement, 352 00:28:24,356 --> 00:28:26,676 Speaker 1: I take it that sometimes you're wearing a pure researcher 353 00:28:26,716 --> 00:28:31,316 Speaker 1: hat and sometimes you're wearing an advisor, guide advocate, help 354 00:28:31,356 --> 00:28:33,876 Speaker 1: them do a better job hat, And maybe it's possible 355 00:28:33,876 --> 00:28:37,036 Speaker 1: to wear those two hats simultaneously. I was wondering in 356 00:28:37,156 --> 00:28:40,676 Speaker 1: either of these modes. What reception do you have you 357 00:28:40,716 --> 00:28:44,156 Speaker 1: had personally as a scholar and a researcher and sometime 358 00:28:44,196 --> 00:28:50,556 Speaker 1: activist in encountering police when you discuss with them, you know, 359 00:28:50,636 --> 00:28:52,156 Speaker 1: this is how you can do it better. This is 360 00:28:52,196 --> 00:28:53,876 Speaker 1: what you're not doing, This is what the point that 361 00:28:53,876 --> 00:28:58,116 Speaker 1: you're missing. I haven't had that role actually with law 362 00:28:58,196 --> 00:29:02,916 Speaker 1: enforcement officers. I am about to take up that role. 363 00:29:04,476 --> 00:29:08,796 Speaker 1: And meaning until now you've been a pure researcher and 364 00:29:08,836 --> 00:29:11,916 Speaker 1: now going to be Yeah, I'm gonna sort of try 365 00:29:11,956 --> 00:29:18,036 Speaker 1: to start helping law enforcement locally, at least locally with 366 00:29:19,716 --> 00:29:22,636 Speaker 1: the issue of hate crime and to boost reporting of 367 00:29:22,636 --> 00:29:27,196 Speaker 1: hate crime, because that's another thing that law enforcement can 368 00:29:27,356 --> 00:29:32,876 Speaker 1: do to better address the issue of hate crime. They 369 00:29:32,996 --> 00:29:35,476 Speaker 1: can have someone on the other end of the line 370 00:29:35,876 --> 00:29:41,356 Speaker 1: when people call and who is not a Joe Friday, 371 00:29:41,436 --> 00:29:44,796 Speaker 1: just the facts man. And when you say you're about 372 00:29:44,836 --> 00:29:47,276 Speaker 1: to take up that role, it sounds like you've already 373 00:29:47,316 --> 00:29:49,636 Speaker 1: done the first steps of talking to them about how 374 00:29:49,676 --> 00:29:54,836 Speaker 1: that might be doable. Oh. Yes, in part because I've 375 00:29:54,876 --> 00:30:01,436 Speaker 1: experienced this. I was walking, you know, in the neighborhood, 376 00:30:02,116 --> 00:30:05,676 Speaker 1: and someone yelled something out of a car. I knew 377 00:30:06,636 --> 00:30:08,836 Speaker 1: because I teach the First Amendment that this was not 378 00:30:08,956 --> 00:30:16,196 Speaker 1: a hate crime, but it was unpleasant, right. So I 379 00:30:16,236 --> 00:30:18,676 Speaker 1: told a bunch of people about it, and one person 380 00:30:18,716 --> 00:30:20,596 Speaker 1: that I told about it said, you need to report 381 00:30:20,636 --> 00:30:24,476 Speaker 1: that to the police. I said, oh, come on, not good. Heavens, 382 00:30:25,116 --> 00:30:27,156 Speaker 1: you know, I know more about the police and hate 383 00:30:27,156 --> 00:30:29,476 Speaker 1: crime than most people. We don't even have a hate 384 00:30:29,516 --> 00:30:33,916 Speaker 1: crime statute, not reporting. She said, listen, the police want 385 00:30:33,956 --> 00:30:37,596 Speaker 1: to know about this. So I called the police, feeling 386 00:30:37,676 --> 00:30:41,996 Speaker 1: quite foolish about this, and had an encounter with the 387 00:30:42,076 --> 00:30:48,716 Speaker 1: law enforcement officer supposedly randomly who really got it about 388 00:30:49,516 --> 00:30:56,836 Speaker 1: how to take information about incidents like this. He understood 389 00:30:56,956 --> 00:31:01,516 Speaker 1: quite well the power of the police in these sorts 390 00:31:01,516 --> 00:31:08,396 Speaker 1: of situations. You've mentioned increasing reporting as a desirable objective, 391 00:31:08,596 --> 00:31:10,556 Speaker 1: and I want to to ask you about and this 392 00:31:10,636 --> 00:31:14,236 Speaker 1: is whearing your social scientist analysts had. When we do 393 00:31:14,516 --> 00:31:17,956 Speaker 1: see a rise in the reporting of hate crimes, do 394 00:31:17,996 --> 00:31:21,316 Speaker 1: you tend to interpret that as just more consciousness, more 395 00:31:21,316 --> 00:31:24,516 Speaker 1: people doing what you did and reporting things, police being 396 00:31:24,516 --> 00:31:27,516 Speaker 1: more receptive to taking reports, or do you see it 397 00:31:27,556 --> 00:31:31,556 Speaker 1: as reflecting background conditions that they're actually might be rising 398 00:31:31,756 --> 00:31:34,876 Speaker 1: numbers of hate crimes in the United states in their 399 00:31:34,916 --> 00:31:38,636 Speaker 1: current moment, because obviously the public wants to know which 400 00:31:38,676 --> 00:31:41,316 Speaker 1: of those two things is happening. Even if it's inherently 401 00:31:41,316 --> 00:31:43,476 Speaker 1: good for more crimes to be reported, we also want 402 00:31:43,516 --> 00:31:49,236 Speaker 1: to know if there's more hate crime happening now or not. Well, 403 00:31:49,356 --> 00:31:54,036 Speaker 1: if I know something about changes in procedures among police departments, 404 00:31:54,636 --> 00:32:02,716 Speaker 1: then I will see it as better policing. But in 405 00:32:02,756 --> 00:32:09,396 Speaker 1: the absence of any evidence that suggests that police are 406 00:32:09,436 --> 00:32:14,396 Speaker 1: doing anything differently, I don't know where to place it. 407 00:32:14,956 --> 00:32:22,676 Speaker 1: I really don't because the data is very, very bad. 408 00:32:25,196 --> 00:32:31,076 Speaker 1: The data includes not just police reports right the FBI, 409 00:32:31,956 --> 00:32:36,396 Speaker 1: the bad data collected by the FBI. But there's a 410 00:32:36,956 --> 00:32:39,716 Speaker 1: center in California, the Center for the Study of Hate 411 00:32:39,716 --> 00:32:45,076 Speaker 1: and Extremism, that also collects data. Southern Poverty Law Center 412 00:32:45,196 --> 00:32:52,116 Speaker 1: collects data. There was a media organization also collecting data 413 00:32:52,516 --> 00:32:59,956 Speaker 1: and just recording incidents. So those are fairly stable sources 414 00:32:59,996 --> 00:33:04,756 Speaker 1: of data that don't have They have some problems, but 415 00:33:04,836 --> 00:33:08,876 Speaker 1: they're different types of problems than law enforcement. So if 416 00:33:08,916 --> 00:33:14,836 Speaker 1: the sorts of data show rises and the FBI data 417 00:33:14,876 --> 00:33:19,556 Speaker 1: shows a rise, then that suggests that there's a lot 418 00:33:19,596 --> 00:33:23,836 Speaker 1: more activity. That suggests there has been a rise so 419 00:33:23,956 --> 00:33:29,636 Speaker 1: you pair the law enforcement data with other sorts of data, 420 00:33:29,836 --> 00:33:32,436 Speaker 1: and that you would say, is suggestive that there actually 421 00:33:32,516 --> 00:33:34,756 Speaker 1: is a rise out there, not just a rise in reporting, 422 00:33:34,756 --> 00:33:37,236 Speaker 1: but aine a genuine rise in light of what's going 423 00:33:37,236 --> 00:33:42,276 Speaker 1: to interactundring today. Yeah, exactly, to return for a moment 424 00:33:42,316 --> 00:33:45,436 Speaker 1: to the Atlantis shooter, who has not presently been charged 425 00:33:45,436 --> 00:33:48,876 Speaker 1: with a hate crime, you were saying that with better 426 00:33:48,916 --> 00:33:54,236 Speaker 1: evidence collection and more expertise, law enforcement could well have 427 00:33:54,316 --> 00:33:56,716 Speaker 1: been able to gather information, might still be able to 428 00:33:56,756 --> 00:33:59,436 Speaker 1: gather information in a better way they would enable a 429 00:33:59,436 --> 00:34:01,436 Speaker 1: hate crime to be charged. And I guess I'm wondering 430 00:34:01,476 --> 00:34:04,876 Speaker 1: in the real world, what would it take for law 431 00:34:04,996 --> 00:34:09,636 Speaker 1: enforcement to gather that information, and what information would it 432 00:34:09,636 --> 00:34:12,156 Speaker 1: take to convince law enforcement to bring such a charge, 433 00:34:12,796 --> 00:34:15,556 Speaker 1: And then what bigger picture difference would emerge in the 434 00:34:15,596 --> 00:34:19,276 Speaker 1: world if his crimes were charged not only as crimes 435 00:34:19,276 --> 00:34:25,156 Speaker 1: of murder but also as hate crimes. A bias unit 436 00:34:25,836 --> 00:34:30,916 Speaker 1: in the police department or in area police departments, or 437 00:34:31,036 --> 00:34:36,716 Speaker 1: some sort of special focus on hate crime in the area, 438 00:34:37,276 --> 00:34:45,796 Speaker 1: some targeted attention to hate crime investigation would lead to 439 00:34:46,676 --> 00:34:52,516 Speaker 1: a change in the way that they investigate crime. And 440 00:34:53,836 --> 00:34:58,556 Speaker 1: it doesn't matter for offense. He will be at some 441 00:34:58,676 --> 00:35:04,636 Speaker 1: point charge with multiple murders, multiple accounts of first degree murders. 442 00:35:06,156 --> 00:35:08,956 Speaker 1: But it matters to the individuals who are targeted by 443 00:35:08,956 --> 00:35:13,236 Speaker 1: the is violence and by individuals targeted. I'm talking about 444 00:35:13,236 --> 00:35:17,556 Speaker 1: the entire community. Asian Americans all over the country are 445 00:35:17,636 --> 00:35:22,196 Speaker 1: reeling from this, and it does violence to their pain. 446 00:35:22,916 --> 00:35:27,956 Speaker 1: To say that it's not motivated by bias says that 447 00:35:28,996 --> 00:35:34,956 Speaker 1: someone can go in and target a bunch of you 448 00:35:36,116 --> 00:35:42,596 Speaker 1: and we can say, oh, having a bad day, that 449 00:35:42,756 --> 00:35:49,796 Speaker 1: is awful. That's a very powerful answer. I want to 450 00:35:49,836 --> 00:35:52,196 Speaker 1: thank you so much for the interview and also for 451 00:35:52,236 --> 00:35:55,116 Speaker 1: your much more importantly, for your terrific and fascinating work. 452 00:35:55,156 --> 00:35:57,636 Speaker 1: I learned so much from reading it and learn so 453 00:35:57,676 --> 00:36:00,836 Speaker 1: much from a conversation. Thank you, Thank you so much. 454 00:36:08,396 --> 00:36:12,796 Speaker 1: Listening to Professor Jeanine Bell was eye opening for me 455 00:36:13,716 --> 00:36:18,076 Speaker 1: because of the precision that she brings to analyzing both 456 00:36:18,076 --> 00:36:22,116 Speaker 1: the data around hate crimes and the technical legal issues 457 00:36:22,556 --> 00:36:27,476 Speaker 1: that surround the decisions to investigate and to prosecute. I 458 00:36:27,556 --> 00:36:30,956 Speaker 1: was stunned to hear her say that in a recent year, 459 00:36:31,076 --> 00:36:34,596 Speaker 1: eighty six point one percent of the criminal jurisdictions in 460 00:36:34,636 --> 00:36:37,836 Speaker 1: the United States reported to the FBI that they had 461 00:36:37,876 --> 00:36:41,196 Speaker 1: experienced no hate crimes, and although I would love to 462 00:36:41,196 --> 00:36:43,436 Speaker 1: live in a country where that was the actual reality, 463 00:36:43,676 --> 00:36:46,876 Speaker 1: I seriously doubt whether we do live in such a country. 464 00:36:47,636 --> 00:36:49,956 Speaker 1: It was also a very striking that she pointed out 465 00:36:50,076 --> 00:36:53,596 Speaker 1: that where prosecutors and police don't have experience in investigating 466 00:36:53,596 --> 00:36:56,356 Speaker 1: hate crimes, they might miss some of the most basic 467 00:36:56,436 --> 00:37:02,236 Speaker 1: sources of evidence, including, for example, sympathetically interviewing victims and 468 00:37:02,356 --> 00:37:05,356 Speaker 1: survivors of hate crimes in order to find out what 469 00:37:05,396 --> 00:37:09,356 Speaker 1: evidence they have to offer about the motives of the 470 00:37:09,396 --> 00:37:13,276 Speaker 1: people who committed the crimes in the first place. Overall, 471 00:37:13,516 --> 00:37:16,396 Speaker 1: I can see why Professor Bell is so focused on 472 00:37:16,556 --> 00:37:21,076 Speaker 1: encouraging police departments to develop expertise and distinctive hate crimes 473 00:37:21,116 --> 00:37:24,476 Speaker 1: units who will have the relevant institutional experience and their 474 00:37:24,516 --> 00:37:27,676 Speaker 1: elevant knowledge of how to go about investigating hate crime 475 00:37:27,876 --> 00:37:30,556 Speaker 1: in order to then bring those crimes to prosecutors to 476 00:37:30,596 --> 00:37:34,596 Speaker 1: be brought before juries. A further perspective that Professor Bell 477 00:37:34,876 --> 00:37:39,196 Speaker 1: brought that was extremely interesting to me was her gentle 478 00:37:39,276 --> 00:37:44,156 Speaker 1: pushback against those prison abolitionists and police abolitionists who are 479 00:37:44,276 --> 00:37:49,276 Speaker 1: skeptical of the capacity of hate crimes to actually enhance 480 00:37:49,716 --> 00:37:54,836 Speaker 1: racial justice. Professor Bell made the point that we all 481 00:37:54,876 --> 00:37:59,756 Speaker 1: surely think that terrible murderers like Dylan Roof need to 482 00:37:59,796 --> 00:38:02,876 Speaker 1: be put in prison, and that from there one must 483 00:38:02,916 --> 00:38:06,676 Speaker 1: embrace at least the possibility that by enforcing hate crimes 484 00:38:06,716 --> 00:38:11,036 Speaker 1: legislation more completely, more fully, and more fairly, we actually 485 00:38:11,076 --> 00:38:16,956 Speaker 1: could improve the state of criminal justice with respect to race. Finally, 486 00:38:16,996 --> 00:38:20,076 Speaker 1: I was struck that even in our terrible moment, where 487 00:38:20,196 --> 00:38:23,556 Speaker 1: there appears, based on the data, to be arise in 488 00:38:23,716 --> 00:38:27,876 Speaker 1: hate crimes around the country, she is nevertheless ultimately optimistic 489 00:38:28,196 --> 00:38:31,996 Speaker 1: about the possibility that our criminal justice system could improve 490 00:38:32,116 --> 00:38:35,556 Speaker 1: going forward by doing a better job with respect to 491 00:38:35,596 --> 00:38:39,876 Speaker 1: the enforcement of hate crimes and biased crimes. In this moment, 492 00:38:40,036 --> 00:38:42,676 Speaker 1: any optimism about the question of whether we might in 493 00:38:42,716 --> 00:38:45,596 Speaker 1: fact to do better than we're doing is to me 494 00:38:45,676 --> 00:38:50,956 Speaker 1: at least a sign of hope, array of possibility. Not 495 00:38:51,076 --> 00:38:53,476 Speaker 1: that we're in a good place now, but that we could, 496 00:38:53,796 --> 00:38:57,556 Speaker 1: by being careful, rational and precise, get to a better 497 00:38:57,596 --> 00:39:01,436 Speaker 1: place in the future. Until the next time I speak 498 00:39:01,436 --> 00:39:04,876 Speaker 1: to you, all, be careful, be safe, and be well. 499 00:39:07,036 --> 00:39:10,476 Speaker 1: Deep background is brought to you by Pushkin Industries. Our 500 00:39:10,516 --> 00:39:14,316 Speaker 1: producer is Mo laboord Our engineer is Martin Gonzalez, and 501 00:39:14,356 --> 00:39:19,076 Speaker 1: our shorerunner is Sophie Crane mckibbon. Editorial support from noahm Osband. 502 00:39:19,556 --> 00:39:23,196 Speaker 1: Theme music by Luis Guerra at Pushkin. Thanks to Mia Lobell, 503 00:39:23,516 --> 00:39:28,396 Speaker 1: Julia Barton, Lydia, Jean Cott, Heather Faine, Carl mcliori, Maggie Taylor, 504 00:39:28,796 --> 00:39:31,596 Speaker 1: Eric Xander, and Jacob Weisberg. You can find me on 505 00:39:31,636 --> 00:39:34,596 Speaker 1: Twitter at Noah R. Feldman. I also write a column 506 00:39:34,596 --> 00:39:37,316 Speaker 1: for Bloomberg Opinion, which you can find at Bloomberg dot 507 00:39:37,316 --> 00:39:41,596 Speaker 1: com slash Feldman. To discover Bloomberg's original state of podcasts, 508 00:39:41,756 --> 00:39:44,876 Speaker 1: go to Bloomberg dot com slash podcasts and if you 509 00:39:44,956 --> 00:39:47,516 Speaker 1: liked what you heard today, please write a review or 510 00:39:47,596 --> 00:39:49,996 Speaker 1: tell a friend. This is deep background