Remember that the federal government is still of the opinion that NYPD is disproportionately targeting black people with its stop and frisk policy, today.
That is, almost a decade after it was ruled unconstitutional in federal court. (Edit: "it" being stop & frisk as a whole, not just the targeting of minorities)
There is certainly a growing disconnect between federal court decisions and on-the-ground reality. This disconnect is a recognized problem. Courts are no longer respected as they once were. Many people just dismiss federal courts as political theater. And elected officials often make their reputations by defying courts, or at least pretending so to do, which trickles down to individual employees not respecting judicial decisions.
No. The big question is whether we want cops to be "randomly" stopping and frisking any people regardless of race/location. The idea that armed people are allowed to just accost people on the street to conduct cursory searches seems incompatible with basic liberties. It is a stone's throw from the "papers please" interaction that so many Americans loath. (I was about to say uniformed, but cops don't always wear uniforms these days.)
No. The big question is whether we want to live in a society that requires the police to randomly stop and frisk people in order to stop crime. There is crime, I don't think anyone can dispute that.
Honestly, I personally have no problem with criminal-looking individuals being stopped and frisked in high-crime areas. And I say this as someone that's been profiled as a white person in a black country, and held at gunpoint by assault-rifle wielding police.
And if stop-and-frisk is extended to vehicles? Would America tolerate cops randomly pulling over cars that looked "criminal"? Or we could take it a step further and just randomly search homes.
Sure, it could be a slippery slope, but the problem is that no one can strictly define what “criminal-looking” means. That term is often used synonymously with “urban style,” which means “black people, and others who dress like black people.”
If stop and frisk were started in the rural south and had this loose “criminal-looking” definition applied to it, all those MFers would get stopped every day for being skinny, having shitty teeth, etc.
The point being that criminals look exactly like normal, non-criminal people.
But can't you define everything as a slippery slope?
If we allow cops to arrest people for discharging a firearm in public, next they'll arrest people for simply pulling a gun in public...then eventually just having a gun in public!
The TLDR is that you can analyze the difference between stops on summer evenings (sunny) and winter evenings (dark) and detect a racial bias depending on whether officer can see the driver or not. The raw data is also available through Minneapolis' Open Data website, so you can repeat the analysis yourself.
The problem with that methodology is that it doesn't only hide race. Criminals tend to be repeated offenders. It only proves that the police couldn't recognize them.
> Two strikingly different types of areas experience high police vehicle deployments — 1) dense, higher-income, commercial areas and 2) lower-income neighborhoods with higher proportions of Black and Hispanic residents. We discuss the implications of these disparities for policing equity and for algorithms trained on policing data.
You can see the history of police in this. Uniformed police depts were founded by merchants wanting to protect their property and socialize the costs.
Prior to uniformed police, we had town watch/night watch/shire reeves . These folks were drawn from the citizenry and pulled a shift watching things, and it was considered quite a nuisance and unglamorous.
Eventually, wealthy folks started paying others to take their shifts on the watch, and a cottage industry emerged. At that time, watches were still loosely organized and without uniform.
In the mid 1800s, two phenomena occurred that molded police. The first was the idea that a uniformed guard would have a preventative effect on crime in wealthier areas (which resulted in early police depts in London and Boston, iirc). And the second was the increasingly structured and bold slave patrols. The two concepts both focused on protecting wealth (at that time, slaves were property just like warehouses and factories).
Over time, the two merged somewhat. Some police departments emerged directly from slave patrols, others never had anything to do with slave patrols and instead focused on protecting docks and the like.
The results of this research saying, "wealth and race seem to be where police are deployed" is a fascinating rhyme to the origins of police.
(Note, I'm deliberately not saying "cause" or "reflection" here - I do not have the data to say why police are deployed this way. I'm just noting the way it rhymes with history.)
I'm saying the opposite. Originally, enforcement was communal - it was a periodic expectation, something you did but didn't get paid for.
Then the wealthy started paying people to take the unpleasant shift, but even then the pay wasn't to enforce the law, it was pay to take over for some rich guy who didn't want to be up all night.
People whose career is law enforcement is newer and the compensation and expectations are different.
You are saying that for thousands of years of civilization nobody got paid for law enforcement before capitalism? Yeah, that doesn't sound very plausible.
People were paid to protect someone's stuff, those people were called guards, but they weren't enforcing law. Some people were given ownership of a place and the people in that place, they were called lords or knights, but they weren't enforcing laws, they were enforcing their will.
Some communities had expectations and rules, and the community was self policing - if you did theft, the mob would come punish you. They weren't enforcing laws and certainly weren't paid. Their justice was uneven and often brutal.
Sometimes soldiers would be pressed into enforcing laws, but they were being paid to be soldiers.
Eventually we got to some folks who were paid to enforce laws. Some of the earliest were "Shire Reeves" (from which we derive the word sheriff). A shire reeve was a single man who was charged with keeping order in a shire. That's not exactly enforcing laws, but it's close enough in spirit. A reeve would hire temporary folks in a posse if needed to achieve a temporary goal, but did not have a police department.
Temporary posses were not uniformed, and were typically paid for short term labor - arrest this guy or get that property back. A reeve may have guards for his safety or to intimidate local folks, but those guards weren't really law enforcement.
Around the fourteenth century, governments started relying on formal roles known as justices of peace, or conservators of peace, who were explicitly charged with binding people to laws and enforcing laws. They were relatively large in number and the practice continued through to the industrial revolution. Except JPs weren't paid, they were typically gentry who enjoyed the social status it granted them.
The history of US police is really fascinating, and not something most people really every dive into. They believe it was always this way, but it very much wasn't. Police as a concept like we know them is very, very modern.
> People were paid to protect someone's stuff, those people were called guards, but they weren't enforcing law.
So you deny that some people were paid to enforce the law at some point of time somewhere? So the Code of Hammurabi was just a useless piece of stone nobody cared about?
> Some people were given ownership of a place and the people in that place, they were called lords or knights, but they weren't enforcing laws, they were enforcing their will.
Lords and knights is a very recent phenomena. Civilization is much older than lords and knights. In fact, feudalism is a very peculiar part of human history. Most of the time, power was very "centralized" even if "devolved".
> Sometimes soldiers would be pressed into enforcing laws, but they were being paid to be soldiers.
They also were being paid to police, evidently, thus being the police.
> Eventually we got to some folks who were paid to enforce laws. Some of the earliest were "Shire Reeves" (from which we derive the word sheriff).
They weren't the earliest. State monopoly on violence is much older than Shire Reeves.
> The history of US police is really fascinating, and not something most people really every dive into. They believe it was always this way, but it very much wasn't. Police as a concept like we know them is very, very modern.
People believe everything in the US is a consequence of slavery. They can't comprehend that laws and cities existed before 1619, let alone before Anglo-Saxons came to Albion.
Police departments in the US derived from English law, which had a system of unpaid enforcement via gentry. Prior to that, reeves were individuals charged with keeping the peace. Prior to that it was expected everyone contributed via frankpledge.
This takes us back to around the year 1000.
There's not much evidence of law enforcement prior to that in the direct historical lineage of US policing.
In other cultures we see military (gendarmes or "men at arms") and slaves being deployed to enforce laws. (Common in Rome and Byzantine culture.)
In other cultures a leader would create justifications and appoint a single person to ensure the jurisdiction was peaceful. That single individual was paid, and they likely hired guards when they wanted, but I generally wouldn't consider a guard or posse to be law enforcement in the way we understand that term today. Those roles were closer to bounty hunters. This is how the Egyptian pharaohs ran things thousands of years ago.
Hammurabi, btw, isn't like the inventor of laws. He just very famously decided to punish violence with violence. Sumerian law existed prior. But the existence of laws says nothing about their enforcement. If you've got good resources on Sumerian or Mesopotamian enforcement, I'd be interested, but it's pretty far off topic of the US law enforcement lineage.
> Police departments in the US derived from English law, which had a system of unpaid enforcement via gentry. Prior to that, reeves were individuals charged with keeping the peace. Prior to that it was expected everyone contributed via frankpledge.
> This takes us back to around the year 1000.
> There's not much evidence of law enforcement prior to that in the direct historical lineage of US policing.
There is. Police departments in England are derived from police departments in France.
> If you've got good resources on Sumerian or Mesopotamian enforcement, I'd be interested, but it's pretty far off topic of the US law enforcement lineage.
It is not. People in the US like to find idiosyncratic reasons for why things are so in the US and why their country is oh so unique, but the truth often is that things are like that everywhere —even in places where such idiosyncratic reasons couldn't exist.
In earlier times, there was more decentralization. So, such decentralized localities couldn't be what we call states today. Yes, some elders, some wise men, some people with more clan-power, etc., were involved in settling property disputes that arose in their villages, camps, places, etc (whatever such locality could be called).
It was not so much law enforcement, but protection of property. Especially during harvest seasons in old days, farmers pay a share of harvest to protectors. Some kind of such protection has had existed, for sure, without formal laws or without formal law enforcements. It was more of customs, traditions, with some sense of reasonableness.
Which (even to the extent it was true—it wasn't, always) doesn't change the fact that their goals and incentives weren't the same as those of modern professional law enforcement.
I remember the outcry when Google Glass first came out. Now ordinary cams, image datasets plus AI reveals much more than an ordinary people moving around and seeing/recording things as they are happening.
What could we uncover from the data if more cams and sensors are added to AI systems which can process real time data.
We watched Person of Interest as Sci-Fi, but it's becoming utopian considering what we possibly have now.
I'm not far into it, so I don't know how good it will be. However FX's 'Class of 2009' seems interesting too where FBI agents have AI strapped to them feeding the dataset at all times. The show jumps between 2009, 2023, and like 2035 or something and the implications of such a system.
A lot of the hot spots are just police stations. Most stations don't have enough reserved spaces and cars end up scattered around the neighborhood. That isn't an indicator of ongoing policing activity.
They talk about that in the paper, noting not police departments but also prisons (eg, Rikers). But the data is collected on a per census block level, so even though there exists some outlier blocks, the overall trends are still quite visible.
>Areas with more police vehicle images included wealthy commercial zones and low-income neighborhoods with higher proportions of Black and Latino residents.
Does this really surprise anyone?
Lower income areas have more crime. I don't understand why race is a factor here.
Race doesn't matter if "low-income neighborhoods with higher proportions of Black and Latino residents" is simply stating that all low income neighborhoods have higher proportions of Black and Latino residents. Although it's kind of relevant if all downstream bias in arrests etc, say, goes away when you control for income.
But I read it as "of all low income neighborhoods, ones with higher proportions of Black and Latino residents had more police vehicle images". In which case, the question is:
Why would similar-income neighborhoods (which you theorize should have similar crime levels regardless of race) be policed differently based on the race of the population?
“We report racial and socioeconomic disparities without attempting to control for other covariates. First, if New York City residents of different races face different levels of police deployments, that disparate impact is itself important; it can also bias algorithms trained on downstream policing data irrespective of the true causal mechanism. Second, controlling for other factors in policing data can be difficult to interpret, introducing concerns about omitted variable bias and model misspecification which make it difficult to identify which factor is truly the “cause” of higher police deployments. For the sake of transparency and simplicity, therefore, we report results by stratifying each variable separately, noting that these disparities are themselves important but that multiple causal mechanisms may underlie them.”
Misled implies a degree of intent, the wording is ambiguous but I don't assume ill intent by the author, especially when they later spend a paragraph explaining why they did not slice by covariates.
It is either purposefully misleading or unreasonably reckless. It is obviously ambiguous and screams of ragebait. I wanted to punch my monitor and fire the author of article when I read this sentence because it is just inflammatory racebait.
You should consider checking your humors or mediate or something, because wanting to do violence because of some Internet text is not healthy human behavior.
Interestingly, you are correct, but you omitted the rest of the paragraph where they articulate why, emphasizing that across booth residential and commercial neighborhoods there is a striking difference in policing.
> We note that we report racial and socioeconomic disparities without attempting to control for other covariates for two reasons. First, if New York City residents of different races face different levels of police deployments, that disparate impact is itself important; it can also bias algorithms trained on downstream policing data irrespective of the true causal mechanism. Second, controlling for other factors in policing data can be difficult to interpret, introducing concerns about omitted variable bias and model misspecification which make it difficult to identify which factor is truly the “cause” of higher police deployments. For the sake of transparency and simplicity, therefore, we report results by stratifying each variable separately, noting that these disparities are themselves important but that multiple causal mechanisms may underlie them.
I see a viscious cycle if being policed aggressively, producing further poverty, increasing crime, encouraging more aggressive policing.
The evidence I have seen is that more aggressive policing fundamentally fails at changing systemic poverty that is the root of the issue, and the funding that is funnelled into it would be better put into things like drug programmes to rehabilitate people, social programmes to help people keep in education/work, funding for safe and legal opportunities for kids, support for education and public facilities so people get opportunity to improve their situations generationally, etc...
Race is a factor becuase slavery and post-slavery racism have created a huge wealth gap, and redlining pushed black people into these areas. Yes, of course crime is more prevelant in these areas, but that doesn't mean race isn't a factor. It doesn't have to be police officers thinking "I'm going to be racist today" for it to unfairly hurt people based on race.
> Among the researchers’ findings: Gramercy Park, in Midtown Manhattan, had the most police vehicles visible in dashcam images -- almost 20 times more than Arden Heights/Rossville, in southern Staten Island, which had the fewest.
the residential neighborhood with a quarter mil average income and a literal private garden has the most visible police presence in the city
Wage theft is also not the type of crime that is caught by police on patrol. Having more cops in a neighborhood wont stop wage theft. Wage theft requires reports of misconduct and an investigation.
That's the point, though. That "these are where police arrest a lot of people" isn't necessarily "these are where the most crimes or the most criminal damage happen".
Police could absolutely patrol for wage theft. It would look somewhat different from how police patrol for other crimes, but we know where it happens and how it is committed. In fact, because wage theft can only happen in specific places and only be committed by a small subset of people, it would be much easier to prevent wage theft via patrol than almost any other crime.
Yet we treat it as a report-only crime, to be prosecuted after the fact rather than prevented by policing. It seems like that's mostly a matter of police priorities.
It's important to note that common sense itself is a bias. It's a bias towards what we already think. Don't mistake that as trying to say that for "we should avoid priors" - that's not possible. What would it take for you to soften (not move) your priors on the common sense that "police aren't co-creators in crime through the act of observation"?
Police aren’t co-creators of crime, they’re co-creators of crime statistics. Crimes that go unreported, with no arrest made, are invisible to crime statistics. When the police arrest someone and charge them with a crime, it counts as both an arrest and a reported crime.
So even if crime were uniformly distributed across the city, if police spent the majority of their time in one neighbourhood they’d make more arrests there and so it follows that the statistics would show higher crime in that neighbourhood.
Police are also demonstrably co-creators of crime.
We know very well that police injure and kill people—disproportionately people of color—at a much higher rate than the general population.
We also know that they (technically legally, but c'mon, it's theft) steal large amounts of money and other property from people through civil asset forfeiture.
Instead of reacting, why don't you get curious instead?
I stand by my claim. Crimes are social facts. They exist within a reality supported by whichever laws those with the monopoly of violence believe in. Crimes exist within the symbol register of thought. I'll ask you a question in return, why did you choose your ontology of crime among all those that could possibly exist?
"Crime" has multiple elements: the law, the act, the observation, and the prosecution.
We disproportionately outlaw things that poor people do. ("The law, in its majestic equality, forbids rich and poor alike from sleeping under bridges.") We disproportionately observe poor people, as shown by this article. We disproportionately convict poor people, who can't afford bail or good legal representation.
Yet people always want to jump to that other element. The disproportionate crime rates can't be due to all those other things, it must be due to them committing more crimes.
The only thing we can say for sure is that poor people commit different crimes. They use different drugs and in different settings; they are more likely to commit theft than embezzlement; they are more likely to cause property damage than violate building codes. The rest is made murky by an unfair legal system and a societal tendency to treat crimes of poverty as individual in nature and crimes of wealth as systemic failures.
I think it also depends on your definition of crime or the type of crime that is being committed as outside of the scope of truly violent crimes or crime where there is a clear victim there are a lot of crimes that really should not be a crime in the first place (like possession of certain plants) and there may be many instances of truly victimless crimes that would go "uncaught" and thus untracked if an authority figure was not observing them.
> By age 22, lifetime rates of addiction to drugs or alcohol were 11 to 16 percent among women from affluent families, which is similar to the national norms; the rates were 19 to 27 percent among men from affluent families, twice the national norms, according to the study.
> But a more troubling trend emerged by age 26: Lifetime rates of addiction to drugs or alcohol were 19 to 24 percent among women from wealthier upbringings and 23 to 40 percent among men from those families. These rates were three times higher than the national average for women, and two times higher in men.
Because even after controlling for income, American police still disproportionately mistreat Black people.
I'm struggling to find the data right now, but I believe the source was Phillip Atiba Goff. The tl;dr is that Black people are treated violently by police at a rate of several times that of white people, even once you control for socioeconomic status.
One of the best illustrations of this is a fascinating study about police stops and sunset time. They were able to demonstrate that when the sun is up (i.e. the driver can be seen), black drivers are more likely to be pulled over, but when the sun goes down, it equalizes. As a bonus, they controlled for other factors by looking at these stats around when daylight savings switches.
> First, they narrowed the range of variables they had to analyze by choosing a specific time of day — around 7 p.m. — when the probable causes for a stop were more or less constant. Next, they took advantage of the fact that, in the months before and after daylight saving time each year, the sky gets a little darker or lighter, day by day. Because they had such a massive database, the researchers were able to find 113,000 traffic stops, from all of the locations in their database, that occurred on those days, before or after clocks sprang forward or fell back, when the sky was growing darker or lighter at around 7 p.m. local time.
> This dataset provided a statistically valid sample with two important variables — the race of the driver being stopped, and the darkness of the sky at around 7 p.m. The analysis left no doubt that the darker it got, the less likely it became that a black driver would be stopped. The reverse was true when the sky was lighter.
Hah, just linked to the Minneapolis counterpart study above. Yes, this is an elegant natural data experiment, thanks for sharing this version that touches a larger dataset.
I found several studies by Phillip Atiba Goff that did NOT control for SES. (Easy to find a statistically significant result when you ignore confounding variables!) But none that did.
> Deployment disparities, the researchers wrote, can result in downstream biases like increased arrests: A neighborhood that’s more heavily policed than another might not necessarily have more crime, just more people arrested for it.
The discussion section of the paper also speaks to higher police presence being correlated with areas that are being gentrified.
Perhaps they are saying that it's not universal to low income areas, and that low income areas that don't have a higher proportion of Black and Latino residents don't have the increased police vehicle presence? Hard to tell based on the wording there alone.
On a different but similar idea, I had the idea of using dashcam footage to read petrol station (gas stations for you lot over the pond) signs and get info about pricing for fuel. You could reduce the amount of processing required by only looking for pricing info near a station based on gps. My blackview dashcam stores the video along with gps on a microsd card and it can be accessed using a http connection when on wifi. Just never got to it.
At least in Canada gas prices are available in Google Maps. IDK where this data comes from but I wonder if it is publicly available (or at least can be scraped from Google). It isn't 100% reliable but is very good, maybe 95% accurate?
Circa 2010 GasBuddy[0] was a pretty novel app for smartphones that allowed crowd-sourcing gas prices around you.
I imagine OPIS[1] (now owned by News Corp), who acquired GasBuddy, or one of the other Price Reporting Agencies, is providing Google with this gas price information.
I'd be surprised if it was crowd sourced. Even in fairly rural areas the prices of all stations are regularly updated. Crowd sourcing things like traffic data works as even a few people driving down a road can passively report data. It seems unlikely that manually entering gas data that changes daily would be sufficient to achieve such good coverage.
You're right, i edited my comment after you viewed the page. While GasBuddy started out crowdsourced, it seems there are now price reporting agencies that log prices directly from retailers and I imagine Google pulls data from one of them.
If I was worried about people speeding in my neighborhood I would find some Crown Vic or other common vehicle used as a police car that doesn't pass inspection (maybe even a blown engine) and leave it parked by my house. If it is a real used police car all the better.
They mention they have some measures to "compensate for non-representative sampling in the dataset"
> we are reweighting the Nexar data sample, which is sampled from a non-representative set of locations, so that it matches the locations where different demographic groups actually live. For example, to calculate the police deployment levels that Asian residents of New York City experience, we reweight the original data sample to upsample neighborhoods with larger Asian populations.
and
> For example, if vehicles are prohibited from driving near protest areas, which also have larger police presences, we will not have images of large police presences near protests. It is not possible to correct for this bias with the data we have because 1) the true distribution may differ from the Nexar sampling distribution along unobservable dimensions which we cannot reweight along and 2) we may simply have no Nexar images in some regions of the true distribution (e.g. if all vehicles are banned near protests). A second potential bias is that police vehicles represent only a subset of overall police activity: for example, they do not capture officers on foot. We return to both these points below.
Not sure whether you meant this by "explicitly" but I guess the answer is that they didn't correct for it.
> Before describing the details of the framework, the high-level intuition is that we are reweighting the Nexar data sample, which is sampled from a non-representative set of locations, so that it matches the locations where different demographic groups actually live. For example, to calculate the police deployment levels that Asian residents of New York City experience, we reweight the original data sample to upsample neighborhoods with larger Asian populations.
> Overall, our estimation procedure compensates for two types of potential bias. Equation 2 compensates for a data bias, reweighting the Nexar dataset (which is sampled from a set of locations which does not necessarily match the population distribution; Figure 1) to match the population distribution of demographic subgroups. This is conceptually similar to inverse propensity weighting procedures [4] which are used to compensate for non-representative data in other settings. Equation 3 compensates for imperfect model performance, and allows us to check that model performance is unbiased (i.e., calibrated) across demographic subgroups.
Section 4.1 goes into the mathematical functions they use to address the data set.
Section 3.2 describes the data set and how it is geographically distributed.
> Data was provided to us by Nexar in two phases. Phase 1 consists of 3,987,835 images sampled prior to September 1 2020, and is extremely geographically and temporally skewed. Geographically, it is concentrated within the boroughs of Manhattan and Brooklyn, and does not contain data from the boroughs of Staten Island, Queens, and the Bronx at all; temporally, it overrepresents data from Thursday nights. Phase 2, which constitutes the majority of the dataset, consists of 20,816,019 images sampled after October 4 2020, and is much more geographically and temporally representative: it is sampled at all times of the day, on all days of the week, and also covers the entire geographic area of New York City.
> Because Phase 2 is much more representative than Phase 1, we conduct our primary analysis of disparities using only data from Phase 2. We additionally conduct numerous validations and bias corrections, described in §4.1, to compensate for non-representative sampling in the dataset. Geographic and temporal coverage during the Phase 2 period is very good. Specifically, 100% of hours during the Phase 2 period are covered; 99.6% of Census Block Groups (CBGs)3 have at least one image, with a mean of 168.2 images per CBG; 88% of roads contained within the borders of New York City are covered by at least one image, using data from OSMNX [6]. Figure 1 summarizes geographic data availability; Figure S1 summarizes temporal data availability.
Work like this is critical because powerful unions subvert operating procedures and individual liberty across the country without consequence or even serious inquiry. Who watches the watchmen? Well, the watchmen are actively investigating themselves and will get back to you, pinky promise.
This is the kind of "policing is racist" kind of propaganda that has San Francisco in it's current "hands off" state. Does anyone prefer that in every city everywhere?
So, it's research into a topic you don't think should be researched?
Do you have any problems with the methodology or conclusions? Like, science can still be science even if it's pursued in the name of social justice. If they are cooking the books, then that's one thing, but if they are making a hypothesis, gathering data, and evaluating that hypothesis fairly using real data, then it's just science.
I didn't say there was nothing wrong with crime in SF. I just shared a link showing (just as your does) that its crime rate is significantly lower than a lot of cities.
For some reason a certain segment of the national media and populace is always talking about the San Francisco crime rate but seemingly never covers stories about crime in Phoenix, Charlotte, Denver, Dallas, or Indianapolis.
That is, almost a decade after it was ruled unconstitutional in federal court. (Edit: "it" being stop & frisk as a whole, not just the targeting of minorities)