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>This model shows that the cumulative number of death sentences previously imposed in the same county is a strong predictor of the number imposed in a given yea

>This model shows that the cumulative number of death sentences previously imposed in the same county is a strong predictor of the number imposed in a given year. Sorry to be dismissive, but this is obvious. People who ate a lot of steak last year are likely to eat a lot of steak this year. People who did X a lot last year are more likely to do X a lot this year than people who did X less last year. Some district attorneys' offices are more interested in pursuing the death penalty than others. How often to pursue the death penalty is a political question. Liberal district attorneys are much less interested in it than conservative district attorneys. And because the last 40 years of case law have made it very difficult to correctly prosecute a death penalty case without getting overturned for some reason on appeal, it is a significant financial investment for a prosecutor's office to pursue the death penalty. And the expense is not just the prosecution but the decades of appeals and other legal actions that will follow. So it makes sense that death penalty prosecutions are centered in places committed to pursuing the death penalty.

geofft 5y ago
On the other hand, people who bought a house last year are far less likely than the general population to buy a house this year. The non-obvious part is that the death penalty follows the first model and not the second. You could reason from first principles that the death penalty's intended effect is to prevent crime by executing a criminal, which is a long-term action like buying a house and not a short-term one like buying a steak. Or you could reason that its intended effect is to deter crime by presenting a deeply undesirable outcome for criminals. The surprise is that it's neither, and the counties so often have more people to execute.
- naniwaduni 5y ago
  > On the other hand, people who bought a house last year are far less likely than the general population to buy a house this year. Is this even true? This is a non-obvious claim where the exact opposite phenomenon is allegedly true of other seemingly one-time purchases (e.g. cars, household appliances).
  - fiddlerwoaroof 5y ago
    I sort of wonder if this is the data behind Amazon’s bizarre tendency to do things like advertise the same GPU to people who just bought one: I’ve always assumed that it’s just bad ML, but I’ve had this nagging thought that repeat purchases are somehow correlated (if only because seeing an ad for the thing you just bought might remind you that you need to purchase a related accessory in a way that seeing the accessory wouldn’t)
    - hnick 5y ago
      Yes this comes up a lot. If something like 2% of people ever buy a GPU, but 5% of GPU buyers will buy another one soon, then you spend a lot less overall and also get a better conversion rate advertising only to GPU buyers even if most of them think you're silly for showing them the ad. It also preys on FOMO (show a better deal, they might cancel and re-order from you), brings you top of mind if they need a refund/replacement in short order, and does work for general brand awareness for next time, or conversations with a friend (since the ad knows you are now a GPU buying type of person). "Yeah I got XYZ GPU but I saw ABC GPU is cheaper and probably what you need." I probably missed a few things, but briefly it wouldn't be done if there wasn't a reason with the number of metrics they have these days.
  - unishark 5y ago
    I think it's even less likely to be true in geographical terms; counties where people bought more houses last year are probably more likely to be the places where people buy more houses this year. Even if the individuals who did buy houses are no longer in the market.
- Spooky23 5y ago
  You could also reason that killing people is good for getting certain kinds of votes, and generating lots of wasteful and stupid appeals work is good for outside counsel. (Aka donors)
- dragonwriter 5y ago
  > You could reason from first principles that the death penalty's intended effect is to prevent crime by executing a criminal, which is a long-term action like buying a house and not a short-term one like buying a steak. Or you could reason that its intended effect is to deter crime by presenting a deeply undesirable outcome for criminals. The surprise is that it's neither This doesn’t say anything about the intended effect. It says a lot about the actual dynamics, but there is no necessary relationship between those two things.
  - gustavo-fring 5y ago
    It not only doesn't say anything about the intended effect, it can't as it is designed, and the intention is different across the people involved - juries, victims, judges, and voters.
- deleted 5y ago
  [deleted]
willvarfar 5y ago
Obvious in hindsight? Myself, if I'd been asked to guess the distribution of death penalties an hour ago before I'd read this article, would have cited all kinds of things as plausible factors and gone in completely the wrong direction. We're a bunch of programmers, we like to talk here about our biased mental models of things. Give us data, let us fine tune our models and make them more realistic for those future discussions. Real data, even when it confirms something 'obvious', is still good, right?
- throwaway8581 5y ago
  No, obvious in foresight too. If you asked me which places are likely to give the most death penalties this year, I'd just give you the list from last year. I know that something being dressed up as SCIENCE makes us want to think it's profound. But most of the time, research findings are steaming piles of worthless crap that people pretend are insightful because their careers depend on it.
amluto 5y ago
I would go even farther: I am highly skeptical of the paper’s analysis. The analysis seems to assume that the rate of death penalties is entirely predicted by a handful of time-invariant parameters plus the prior death penalty rate. Under such a model, if the parameters chosen do not adequately predict the rate, and the rate is roughly constant over time, then of course the prior rate predicts the rate. This seems tautological. The fact that a model of this type does not support the author’s theory of self-reinforcement — the model is equally consistent with the death penalties being predicted by the second letter of the name of the county or the “racial threat” mod 0.1 or just about anything else. (I have not rigorously verified my objection, but I’m moderately confident I’m right.)
- cycomanic 5y ago
  You're right the authors have not proven causality (they did find correlation though). They don't claim that either, they say it's consistent. Causality is typically difficult to prove. However, to verify your objection you need to first give the parameter that they have not used, and second come up with a good causality why your parameter explains the variation better (hint second letter of the county name is not it).
  - amluto 5y ago
    I beg to differ. The authors did not find a parameter other than death penalty rate that predicts death penalty rate. They claim that this implies that the high death penalty rates happen because the death penalty rate was high. This authors are _wrong_: this conclusion does not follow from their analysis; their analysis is unsound. A demonstration of unsoundness does not require a proof that the conclusion is wrong; unsoundness means that the argument is wrong. The onus is in the authors to present a sound argument, not on the reader of the paper to demonstrate that the conclusion is incorrect. (As a different example, Andrew Wiles’ first proof of Fermat’s Last Theorem was unsound. This didn’t mean that the theorem wasn’t true; it meant that Wiles failed to prove it. Similarly, in my opinion, the authors of this paper have not provided sound evidence in favor of their claim. This doesn’t mean I disbelieve their conclusion.)

geofft 5y ago

On the other hand, people who bought a house last year are far less likely than the general population to buy a house this year. The non-obvious part is that the death penalty follows the first model and not the second. You could reason from first principles that the death penalty's intended effect is to prevent crime by executing a criminal, which is a long-term action like buying a house and not a short-term one like buying a steak. Or you could reason that its intended effect is to deter crime by presenting a deeply undesirable outcome for criminals. The surprise is that it's neither, and the counties so often have more people to execute.

naniwaduni 5y ago
> On the other hand, people who bought a house last year are far less likely than the general population to buy a house this year. Is this even true? This is a non-obvious claim where the exact opposite phenomenon is allegedly true of other seemingly one-time purchases (e.g. cars, household appliances).
- fiddlerwoaroof 5y ago
  I sort of wonder if this is the data behind Amazon’s bizarre tendency to do things like advertise the same GPU to people who just bought one: I’ve always assumed that it’s just bad ML, but I’ve had this nagging thought that repeat purchases are somehow correlated (if only because seeing an ad for the thing you just bought might remind you that you need to purchase a related accessory in a way that seeing the accessory wouldn’t)
  - hnick 5y ago
    Yes this comes up a lot. If something like 2% of people ever buy a GPU, but 5% of GPU buyers will buy another one soon, then you spend a lot less overall and also get a better conversion rate advertising only to GPU buyers even if most of them think you're silly for showing them the ad. It also preys on FOMO (show a better deal, they might cancel and re-order from you), brings you top of mind if they need a refund/replacement in short order, and does work for general brand awareness for next time, or conversations with a friend (since the ad knows you are now a GPU buying type of person). "Yeah I got XYZ GPU but I saw ABC GPU is cheaper and probably what you need." I probably missed a few things, but briefly it wouldn't be done if there wasn't a reason with the number of metrics they have these days.
- unishark 5y ago
  I think it's even less likely to be true in geographical terms; counties where people bought more houses last year are probably more likely to be the places where people buy more houses this year. Even if the individuals who did buy houses are no longer in the market.
Spooky23 5y ago
You could also reason that killing people is good for getting certain kinds of votes, and generating lots of wasteful and stupid appeals work is good for outside counsel. (Aka donors)
dragonwriter 5y ago
> You could reason from first principles that the death penalty's intended effect is to prevent crime by executing a criminal, which is a long-term action like buying a house and not a short-term one like buying a steak. Or you could reason that its intended effect is to deter crime by presenting a deeply undesirable outcome for criminals. The surprise is that it's neither This doesn’t say anything about the intended effect. It says a lot about the actual dynamics, but there is no necessary relationship between those two things.
- gustavo-fring 5y ago
  It not only doesn't say anything about the intended effect, it can't as it is designed, and the intention is different across the people involved - juries, victims, judges, and voters.
deleted 5y ago
[deleted]

willvarfar 5y ago

Obvious in hindsight? Myself, if I'd been asked to guess the distribution of death penalties an hour ago before I'd read this article, would have cited all kinds of things as plausible factors and gone in completely the wrong direction. We're a bunch of programmers, we like to talk here about our biased mental models of things. Give us data, let us fine tune our models and make them more realistic for those future discussions. Real data, even when it confirms something 'obvious', is still good, right?

throwaway8581 5y ago
No, obvious in foresight too. If you asked me which places are likely to give the most death penalties this year, I'd just give you the list from last year. I know that something being dressed up as SCIENCE makes us want to think it's profound. But most of the time, research findings are steaming piles of worthless crap that people pretend are insightful because their careers depend on it.

amluto 5y ago

I would go even farther: I am highly skeptical of the paper’s analysis. The analysis seems to assume that the rate of death penalties is entirely predicted by a handful of time-invariant parameters plus the prior death penalty rate. Under such a model, if the parameters chosen do not adequately predict the rate, and the rate is roughly constant over time, then of course the prior rate predicts the rate. This seems tautological. The fact that a model of this type does not support the author’s theory of self-reinforcement — the model is equally consistent with the death penalties being predicted by the second letter of the name of the county or the “racial threat” mod 0.1 or just about anything else. (I have not rigorously verified my objection, but I’m moderately confident I’m right.)

cycomanic 5y ago
You're right the authors have not proven causality (they did find correlation though). They don't claim that either, they say it's consistent. Causality is typically difficult to prove. However, to verify your objection you need to first give the parameter that they have not used, and second come up with a good causality why your parameter explains the variation better (hint second letter of the county name is not it).
- amluto 5y ago
  I beg to differ. The authors did not find a parameter other than death penalty rate that predicts death penalty rate. They claim that this implies that the high death penalty rates happen because the death penalty rate was high. This authors are _wrong_: this conclusion does not follow from their analysis; their analysis is unsound. A demonstration of unsoundness does not require a proof that the conclusion is wrong; unsoundness means that the argument is wrong. The onus is in the authors to present a sound argument, not on the reader of the paper to demonstrate that the conclusion is incorrect. (As a different example, Andrew Wiles’ first proof of Fermat’s Last Theorem was unsound. This didn’t mean that the theorem wasn’t true; it meant that Wiles failed to prove it. Similarly, in my opinion, the authors of this paper have not provided sound evidence in favor of their claim. This doesn’t mean I disbelieve their conclusion.)