As far as what they predict, 40-50 years as explained in the government’s sentencing memo.
As far as what the impact should be—I would have to write a book on that. To start with, I see multiple, related harm-related measures here:
The amount of expected harm the offender knew or should have known about (this is the culpability-flavored measure);
The actual expected value of harm (this is more of a general deterrence-flavored measure); and
The actual harm (more of a retribution-flavored measure).
I also don’t see a unified measure of harm in economic-loss cases, as the harm associated with stealing $1,000 from a working class person is substantially higher than the harm of stealing it from me. Targeting vulnerable victims also gets you an enhancement for other reasons (e.g., it suggests a more extensive lack of moral compass that makes me value incapacitation more as a sentencing goal).
But most fundamentally, both harm and culpability go into the mix, filtered through the standard purposes of sentencing, to produce a sentence that I think is sufficient, but not greater than necessary, to accomplish those goals.
So I can tell you that the relationship between harm and sentence in fraud cases shouldn’t be −0-, both because there is little or no general deterrence against making your frauds bigger, and because there is some relationship between culpability and fraud size. It also shouldn’t be linear, both because this is impractical given the wide variance in harms, and because the degree of culpability does not ordinarily vary in a linear manner.
Most people in the sentencing realm think the federal sentencing guidelines increase the sentence too much based on loss amount (~ 25% uplift for each doubling of amount, plus some other uplifts tend to scale with size) and give too much weight to loss size in general. I agree with both of those views. Roughly and after considering a fuller measure of harm than aggregate financial loss, I might consider such an algorithm appropriate for weighing the harm factor in arriving at a sentence rather than for uplifting the sentence itself. And maybe I would increase the average sentence about 10% for each doubling, if all other factors were equal (low confidence)? But usually non-harm culpability factors increase with harm size, so the average increase in practice would probably be higher (low confidence).
As a bonus exercise: The differential impact between harm and non-harm culpability factors seems to vary quite a bit based on offense type. In drunk driving cases, actual harm seems to explain the bulk of the variance? No harm, first offense -- 2 days. Kill someone, no harm—perhaps 10 years. The non-harm culpability factors and even the expected-harm measures aren’t really that different in a lot of cases. Even here, the extra punishment for multiplied harm isn’t linear; you might get a 50% uplift for the second fatality, and a total of 85% more for three fatalities (low confidence)?
On the other hand, if you rob five convenience stores on five days before getting caught, you might get twice the sentence for robbing one (low confidence) -- even though the culpability scales here much more obviously with the number of offenses / amount of harm. One theory here is that getting caught and punished gives you the opportunity to learn your lesson; if you rob again after going through that then the argument for long-term incapacitation is stronger, etc.
As far as what they predict, 40-50 years as explained in the government’s sentencing memo.
As far as what the impact should be—I would have to write a book on that. To start with, I see multiple, related harm-related measures here:
The amount of expected harm the offender knew or should have known about (this is the culpability-flavored measure);
The actual expected value of harm (this is more of a general deterrence-flavored measure); and
The actual harm (more of a retribution-flavored measure).
I also don’t see a unified measure of harm in economic-loss cases, as the harm associated with stealing $1,000 from a working class person is substantially higher than the harm of stealing it from me. Targeting vulnerable victims also gets you an enhancement for other reasons (e.g., it suggests a more extensive lack of moral compass that makes me value incapacitation more as a sentencing goal).
But most fundamentally, both harm and culpability go into the mix, filtered through the standard purposes of sentencing, to produce a sentence that I think is sufficient, but not greater than necessary, to accomplish those goals.
So I can tell you that the relationship between harm and sentence in fraud cases shouldn’t be −0-, both because there is little or no general deterrence against making your frauds bigger, and because there is some relationship between culpability and fraud size. It also shouldn’t be linear, both because this is impractical given the wide variance in harms, and because the degree of culpability does not ordinarily vary in a linear manner.
Most people in the sentencing realm think the federal sentencing guidelines increase the sentence too much based on loss amount (~ 25% uplift for each doubling of amount, plus some other uplifts tend to scale with size) and give too much weight to loss size in general. I agree with both of those views. Roughly and after considering a fuller measure of harm than aggregate financial loss, I might consider such an algorithm appropriate for weighing the harm factor in arriving at a sentence rather than for uplifting the sentence itself. And maybe I would increase the average sentence about 10% for each doubling, if all other factors were equal (low confidence)? But usually non-harm culpability factors increase with harm size, so the average increase in practice would probably be higher (low confidence).
As a bonus exercise: The differential impact between harm and non-harm culpability factors seems to vary quite a bit based on offense type. In drunk driving cases, actual harm seems to explain the bulk of the variance? No harm, first offense -- 2 days. Kill someone, no harm—perhaps 10 years. The non-harm culpability factors and even the expected-harm measures aren’t really that different in a lot of cases. Even here, the extra punishment for multiplied harm isn’t linear; you might get a 50% uplift for the second fatality, and a total of 85% more for three fatalities (low confidence)?
On the other hand, if you rob five convenience stores on five days before getting caught, you might get twice the sentence for robbing one (low confidence) -- even though the culpability scales here much more obviously with the number of offenses / amount of harm. One theory here is that getting caught and punished gives you the opportunity to learn your lesson; if you rob again after going through that then the argument for long-term incapacitation is stronger, etc.