Algorithm Predicts US Supreme Court Decisions 70% of Time 177
stephendavion writes A legal scholar says he and colleagues have developed an algorithm that can predict, with 70 percent accuracy, whether the US Supreme Court will uphold or reverse the lower-court decision before it. "Using only data available prior to the date of decision, our model correctly identifies 69.7 percent of the Court's overall affirm and reverse decisions and correctly forecasts 70.9% of the votes of individual justices across 7,700 cases and more than 68,000 justice votes," Josh Blackman, a South Texas College of Law scholar, wrote on his blog Tuesday.
biased algorith (Score:5, Insightful)
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If only he could have made some predictions, travelled to the future to test the predictions, then travelled back and put the results in his blog post.
Sadly, testing future predictability can only be done after the future has passed.
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But once the future has passed, it's no longer future. So one can only assert to have tested the predictability formerly called future; also known as the Prince test.
Re:biased algorith (Score:5, Insightful)
You could train it with 80% of the historical data and see if it predicts the next 20% of historical data.
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It would be more accurate to train with all the data available up to, say, year 2000 and then see what the model 'predicts'.
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And wouldn't spotting trends be part of a viable model?
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Essentially what you are doing there is manually running an evolutionary algorithm, discarding ones that don't fit the last 20%, and improving on ones that do.
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That's why you should always divide your data set into one subset for fitting/training of the algorithm, and another subset to verify its predictive ability.
The algo doesn't know or care whether the data is actually from the future. That is irrelevant as long as it wasn't fitted on it.
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But of course you tweak and change over time rather than having the first try work just perfectly and so that subset for verification ends up influencing the algorithm anyway.
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what they have done here is taken a data set and made algorithms until one of them matched well. If I have a model that predicts traffic patterns or weather patterns in the past, its only useful if it is then applied after the fact and is still comparably accurate to when it was developed.
Re:biased algorith (Score:4, Informative)
That why you train your algorithm on all the available cases but the last year ones. Then you can test it on that last year of cases. For the system the last year is the "future" on which you do your testing.
Re:biased algorith (Score:5, Informative)
Yes, and then when the algorithm doesn't work you finetune it a bit and test again and suddenly you end up with an algorithm that has been trained on all data without actually training it against all data.
One should be very skeptical against future predicting algorithms. Until they have been released in the wild for a while without the developer tampering with it it is pretty safe to guess that it more or less is another version of the Turk [wikipedia.org], even if its inventor doesn't realize it.
The same principle can be applied to market research or climate studies. If the algorithm used is tampered with to produce more accurate results one can assume that it is useless.
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I would assume that any person doing professional statistical research knows how to validate to a certain degree of trust.
For example from:
http://en.wikipedia.org/wiki/C... [wikipedia.org]
"Repeated random sub-sampling validation
This method randomly splits the dataset into training and validation data. For each such split, the model is fit to the training data, and predictive accuracy is assessed using the validation data. The results are then averaged over the splits."
So you actually train against all data and validate aga
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In this particular case, I'm not very impressed with a 70% prediction rate on a binary decision... you could get similar results by saying "Uphold" every time and ignoring all the data.
What would be more impressive is if the algorithm could predict (with greater accuracy) how theoretical courts would perform with new justices assigned to the bench. Say a seat is opening up and there are several candidates for the position, can the algorithm tell you what the outcome of an upcoming case will be with the var
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I beg to differ. While constructing a model there are often unknown relationships and parameters between variables for which you have to make assumptions. Like, for example, you suspect that two variables are related, but instead of digging in deeper and deeper in order to exactly resolve the relation you assume an e.g. linear relation, you fit the parameters to some data and move on. As long as you clearly present your methodology, I don't think there is anything wrong with this. The next guy can look clos
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However, time marches on. There will always be new data to test against.
The more interesting question though is to look at what factors were involved in the successful algorithm. Ideally there won't be terms in there like gender or race of the justices or political affiliations. That, in turn offers a way to look (theoretically, of course) at how the current SCOTUS might have decided key cases in the past.
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The utility of the algorithm doesn't become evident until it is tested against data which wasn't available when designing it a
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In this particular case, future predictability doesn't work. The sample size is way too small (as SCOTUS only hears ~80 cases/year), and the cases are not evenly distributed. The last couple years, for example, the court has become very conservative and happens to hear a significantly higher percentage of business-related cases. It's hard to predict anything from that.
It would make more sense to divide the data into training and validation/cross-validation data sets like in a standard machine learning appro
Algorithm based on bias (Score:3)
I wouldn't be surprised if the primary predictive trait used is simply to check the biases of each judge and then assume they will vote along those biases. Assuming conservative judges will vote conservative and liberal judges will vote liberal should give you a pretty good score right off the bat.
Re:Algorithm based on bias (Score:5, Informative)
I wouldn't be surprised if the primary predictive trait used is simply to check the biases of each judge and then assume they will vote along those biases. Assuming conservative judges will vote conservative and liberal judges will vote liberal should give you a pretty good score right off the bat.
Only in a small minority of cases. Contrary to popular belief, most SCOTUS cases aren't highly politicized cases with a clear conservative/liberal divide. Most cases deal with rather technical issues of law which are much less susceptible to this sort of political analysis.
The Roberts Court, for example, has averaged 40-50% unanimous rulings in recent years (last year about 2/3 of rulings were unanimous). So, your idea of "assume conservative vote conservative, liberal vote liberal" would tell you nothing about maybe half of the cases that have come before the court in recent years. (Historically, I believe about 1/3 or so of rulings tend to be unanimous.)
And even with the closely divided cases, you have a problem. Of the 5-4 rulings (which in recent years have been only about 20-30% of the total rulings), about 1/4 to 1/3 of them don't divide up according to supposed "party lines."
In sum, I don't know what factors this model ends up using, but "conservative vs. liberal" is way too simplistic to predict the vast majority of SCOTUS rulings. If you could factor in detailed perspectives on law (which often have little to do with the stereotyped political spectrum), you might have something... but that would require a lot more work, particularly over the 50 years of rulings TFA deals with.
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Bear in mind, the model only gets it right 70% of the time, and a red-black roulette spin would get it right nearly 50% of the time.
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Bear in mind, the model only gets it right 70% of the time, and a red-black roulette spin would get it right nearly 50% of the time.
Yes, and if we were talking about a handful or even a few dozen outcomes, 70% accuracy wouldn't be significant. But we're talking about 68,000 individual decisions of justices. If your roulette spin came up red 70% of the time over 68,000 spins, you'd be darn certain it was rigged. Besides, focusing on this one statistic is relatively meaningless -- a model that gets 70% correct could be simplistic and stupid, or it could have a tremendous amount of insight... that one number says nothing.
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Personally, I'd call an simplistic algorithm that gets 70% right brilliant, and one that has a tremendous amount of insight that also gets 70% correct overly complicated and prone to unpredictable failure.
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So 40-50% are unanimous, and those should be easy to predict. For the remainder, predict party line, and you will get an additional 30-40% right. So an algorithm that gets only 70% right doesn't seem very impressive. Even simplistic guessing should do at least that well.
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Just ran some numbers, since I was curious
So 40-50% are unanimous, and those should be easy to predict.
Only if you can predict which decisions will be unanimous with 100% accuracy.
For the remainder, predict party line, and you will get an additional 30-40% right.
Let's assume we can predict the 45% or so of unanimous decisions of the past few years with 100% accuracy (a dubious assumption), so we have the other 55% to deal with. Even if we assume an incredibly simple model where 4 justices are solidly on each "side" and only one justice is consistently a swing vote (empirically not true), we still have to deal with predicting the roughly 1/3 of cas
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he Roberts Court, for example, has averaged 40-50% unanimous rulings in recent years
If at all possible courts rule only on the parts they all or the vast majority agree on and skip parts they don't agree. For example, one judge might want to overturn the entire law, another just this specific application. Then the court unanimously rules to reverse the case and remains silent on the bigger issue.
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The still need a reason to reverse the case. The SCOTUS or any court for that matter does not just go because we said so. They have reasons. Now, I agree that they may or may not overturn a law based on how much they agree with each other, but they still need a reason to invalidate a lower courts judgement.
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I was going to say: media preference datapoint: NPR vs FOX, might be the strongest predictor.
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That is why you use split data sets. You calibrate on one half, or less, of historical data and then verify against data you did NOT calibrate against.
Re: biased algorith (Score:2)
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I (read: anyone) can make an algorithm that fits any previous data
Unless it was an honest test where the sets of cases used to build and train the algorithm were required to be random samples, AND the cases the prediction was tested against were also a random sample with no overlap with the cases used to build the algorithm (with no training of the algorithm based on the cases supposedly being used to validate it).
Re:Replace them (Score:5, Insightful)
Lawyers: We want people to carry their rights with them, even when operating as a group of people Congress defined as a "corporation" because Congress cannot force them to give up their First Amendment rights.
Scotus (in the voice of Nomad): Logic correct. Opposing lawyers are in error. Must sterilize.
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More like: They already do. Let each advocate and vote as his conscience dictates,. Their votes will align with the values of any corporation they might create.
Corporate personhood gives the owners a double vote.
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Not at all. The entire concept of a corporation is that you can invest without operating. The corporation acts on its own and independent of it's owners if they chose not to directly participate. This is important if you ever wanted to make something happen but didn't have the skills or just wanted to invest finds for other purposes.
Now corporate person hood, which is not the same as corporations are people, has been upheld by the supreme court since 1819 with Trustees of Dartmouth College v. Woodward. But
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Sure, and absent the whole corporations = people with free speech, they can remain hands off if they like. No change there.
Corporations don't actually get a vote, but they do spend bazillions on lobbiests and campaign funds. Instead, how about they tell their owners (stockholders) what will be good for the company (and presumably the investment) and if those stockholders care to lobby or donate, they are free to do so.
Nowhere in there are the owners being denied the ability to carry their rights with them (
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It does not make any sense at all to set up something where investors and owners can be hands off and then require them to be hands on in order for the corp to fulfill its fidiciary duties/responsability.
Maybe you are not aware, but nost of the colonies that became states were set up by companies. They were chartered and run by them. The founders knew exactly what they were and capable of in ways that make today's companies look like kids selling cookies. And yet they purposely gave them autonomy and a resp
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The corporation would in no way be impared from fulfilling it's fidiciary duties. In the same way that making theft and fraud illegal doesn't prevent a corporation from fulfilling it's fidiciary duties.
As for the rest, you are referring to crown charters that were granted by the king of England when the states were still colonies and so subject to English law and the king. I cannot imagine why you might think that would have any bearing on U.S. law. Further, I can't imagine why you would think the foundin
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I never said the corporation would in no way be impared from fulfilling it's fiduciary duties. I said it makes no sense to force the hands off benefit of a corporation aside in order to maintain it.
Or in other words, you could no longer purchase stock X and have it in your retirement only knowing you have sto
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Or in other words, you could no longer purchase stock X and have it in your retirement only knowing you have stock X as an investment. You could no longer purchase a mutual fund for the same without knowing all the ins and outs of each and every company and listening to their pitch on what might harm them and adjust your speech accordingly
Good. Absentee owners are a problem we would be better off without. If you can't be bothered to read a newsletter every 2 years and understand the issues, you should probably abstain from voting anyway. Really though, there are only two likely states. In one, you already agree with what teh corporation wants and so you vote accordingly. In the other you believe differently and it is best if the corporation you own part of doesn't act against you.
You chose to refer to the authority of the founding fathers, a
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Poppycock. The entire concept of a corporation is to separate investment from the operations of the business. But the silliness of your statement is full of ill places conception. The exact same can be said about people who do not even know who the current vice president are but were convinced to register and
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They had the ability to enter into a contract and otherwise conduct business as a legal fiction. They had no Constitutional rights until a few blunders by the Supreme Court granted them, but that was years later.
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lol.. No, they always had constitutional rights and the supreme court said congress cannot take them away. The court started affirming these rights as early as 1819 when all the founding fathers were still around and the constitution and the role of government was well understood.
Congress shall make no law means what it means. It does not mean congress can make a law in certain times or that congress can make a law if something is a certain way, it means congress can make no law prohibiting the freedom of s
Trivial (Score:3)
is it better than random? (Score:1)
If the decisions have 50/50 distribution, then a random guess is right 50% of the time. For any other distribution it's more than that. Soooo 70% is at best a little bit better than random guess, at worst equal to it.
Re:is it better than random? (Score:5, Informative)
That is correct, but not what the GP meant. If you can model the distribution (e.g. you 'know' that B is 90%) then you can weigh your random guessing such that it is correct in >50% of the cases, even without looking at the case itself (it is still 'random' in that sense)
Extreme case: I can predict whether someone has Ebola without even looking at them with >99.99% accuracy by just guessing "no" every time, since the prevalence of Ebola is >.001%.
Suppose the supreme court has 70% chance of overturning (e.g. because they choose to hear cases that have 'merit'), then an algorithm that guesses 'overturn' 100% will have a 70% accuracy. A random guess that follows the marginal of the target distribution (e.g. guess 70% overturn) also scores >50% (58% to be precise).
Useless (Score:5, Insightful)
According to http://www.scotusblog.com/stat... [scotusblog.com] the Supreme Court recently affirmed 27% of lower court decisions and reversed 73%. This means that if you guess that the Supreme Court reverses the lower court every time, you'll be 73% accurate. 70% accuracy is ridiculously low if you can get 73% accuracy *without* taking into consideration the records of each justice or any other kind of details.
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Re:Useless (Score:4, Informative)
Re:Useless (Score:4, Informative)
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It depends - there's a difference between saying 70% "in general" and "this one will be part of the 70%".
Of course, since the percentages seem very close the practical implications would seem to be the same.
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According to http://www.scotusblog.com/stat... [scotusblog.com] the Supreme Court recently affirmed 27% of lower court decisions and reversed 73%. This means that if you guess that the Supreme Court reverses the lower court every time, you'll be 73% accurate. 70% accuracy is ridiculously low if you can get 73% accuracy *without* taking into consideration the records of each justice or any other kind of details.
Of course, the usual reason why the case got to the Supremes in the first place is because there were two cases by different Appeals Circuits which conflicted.
Re:Useless (Score:5, Informative)
70% accuracy is ridiculously low if you can get 73% accuracy *without* taking into consideration the records of each justice or any other kind of details.
First, your link only deals with the past court term. TFA deals with predicting cases back to 1953. Is your 73% stat valid for the entire past half century?
And even if it were, the algorithm is much more granular than that, predicting the way individual justices will vote. From TFA:
69.7% of the Courtâ(TM)s overall affirm and reverse decisions and correctly forecasts 70.9% of the votes of individual justices across 7,700 cases and more than 68,000 justice votes. Also, before someone objects, please note that (contrary to popular belief) SCOTUS does not always vote 5-4 according to party lines. For instance, your own link notes that 2/3 of last year's opinions were UNANIMOUS. 5-4 decisions usually amount for only 25% of cases or so in recent years, and of those, usually a 1/3 or so don't divide up according to supposed "party line" votes.
So, I agree with you that simply predicting reverse/affirm at 70% accuracy may be easy, but predicting 68000 individual justice votes with similar accuracy might be a significantly greater challenge.
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In fact, it looks like very much the same challenge: with most decisions being unanimous reversals, it seems only a small minority of those individual votes are votes to affirm the lower court decision. So, just as 'return "reverse";' is a 70+% accurate predictor of the overall court ruling in each case, the ver
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In fact, it looks like very much the same challenge: with most decisions being unanimous reversals, it seems only a small minority of those individual votes are votes to affirm the lower court decision.
Nope -- you just made the same error the GP did: extrapolating a false inference based on one year of data. It's true that last year had 2/3 unanimous rulings, but that was an outlier -- which I was mainly using to make a point about how the 5-4 rulings that make the news are not as common as we think.
In reality, the Roberts court has averaged maybe 40-50% unanimous rulings, but this is an outlier historically too. Over the 50 years TFA deals with, the unanimous rate is more like 30-40%, I think, maybe
Simplified algorithm (Score:4, Insightful)
if defendant.bank_balance > plaintiff.bank_balance
winner = defendant
else
winner = plaintiff
I'd guess about 90% accurate.
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my algorithm is even better, and even more accurate. its simple: What is the worst possible outcome for the citizenry?
Re:Simplified algorithm (Score:5, Insightful)
my algorithm is even better, and even more accurate. its simple: What is the worst possible outcome for the citizenry?
I don't know about the accuracy of your SCOTUS result-picking algorithm, but you and mwvdlee have a good algorithm to get modded up on slashdot: Just express deep cynicism about the system. Doesn't have to be true in the slightest.
FWIW, I watch SCOTUS pretty closely, and I'd say their bad decisions are fairly rare. I'm unhappy with the outcome in a larger minority of cases, but it's not very common that upon reading the opinions and dissents that I find myself ultimately in disagreement with their conclusions. And in most cases I think they not only make the right legal call, but the right call for the citizenry (though that isn't, and shouldn't be, their primary focus).
Of course, you and I may well disagree about some of the decisions.
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Cynicism? Yes. Warranted? Yes.
To be fair, most of their decisions aren't earth shattering or even really newsworthy, so they dont get reported.
But of those that are big deals...this current court is pretty atrocious. Particularly in terms of business, this court is one of the most pro-corporation-as-the-expense-of-citizens/consumers that has ever existed.
Good decision: killing DOMA, upholding the ACA in general
Bad decisions: allowing unlimited money in politics...twice (total ban on contribution limits will
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The Court's first responsibility is to uphold the law -- not the law as they or anyone else wants it. This includes the Constitution, the "supreme law of the land" - they can't uphold a law that Congress has no authority to pass in the first place.
From this viewpoint, let's take a look at those decisions:
Bad decision: Calling the ACA a "tax". The ACA originated in the Senate, even though the Constitution requires that new taxes originate in the House. Furthermore, you can't compel people to buy something, a
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so money = speech, and if some just happen to have a louder voice because they have more money...oh well?
Bugger that.
and the rest of your comments are nonsense too: the ACA did originate in the house; if we can require people to carry car insurance so they dont become a burden and impose a burden on others then theres no reason not to do it for healthcare, especially when healthcare costs are 20% of our entire economy (course this whole "problem" goes away if we just instituted medicaire for all....plus it'
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and just so I can be especially clear: if it happens that the right decision in terms ofthe Law is NOT the right decision in terms of the public good, then the Law MUST be changed. The two concepts should, indeed they must, be aligned.
Otherwise you become a country who worships the law even to the detriment of soctety itself.
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You don't own a newspaper to deliver your opinion to the front steps of millions of people... Oh well?
That doesn't mean we can go around neutering newspapers. Now, I never said "money = speech", but that doesn't make the First Amendment implications any less relevant. You cannot enforce a law that has the effect of chilling speech. Period full stop.
Everything for Obamacare/PPACA, including the "penalty" tax and tax on medical devices, was introduced in the Senate. They could only pass the Senate version bec
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and just so I can be especially clear: if it happens that the right decision in terms ofthe Law is NOT the right decision in terms of the public good, then the Law MUST be changed. The two concepts should, indeed they must, be aligned in a nation of free people.
Otherwise you become a country who worships the law even to the detriment of society itself.
end (Score:2)
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SCOTUS + ((Mobs + Pitchforks + Torches) / Angry) = Sudden Concern for Public
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if defendant.lawyer_pay > plaintiff.lawyer_pay
winner = defendant
else
winner = plaintiff
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I'd guess about 90% accurate.
lol if you ever actually want to bet money on that algorithm, let me know. I'll even give you 5 to 1 odds, instead of the 9 to 1 you suggest.
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It would run faster if written in Swift. ;-P
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By the way, I'm keeping this algorithm -- not for the wisdom, but because it's so much more efficient than a bunch of CASE statements. Wow, vectored decision trees -- seems so much more civilized.
Sweet! Now we can start the Judge program. (Score:3)
Install software in the helmet, Set the judges loose on the city....
I AM THE LAW!
70% successful prediction (Score:2)
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It's 70% average. For the Democratic judges, it's much lower. For the Republican judges, you could probably dispense with them and use the code as it stands. Since the algorithm falls short of true AI, this clearly implies a lot about how decisions are made and what with.
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A 70% prediction rate is not impressive.
Doesn't that rather depend on what you're predicting, and how good previous algorithms were?
Isn't that a bit like complaining that "10mph is not impressive" while commenting on a story about the world's fastest snail?
In the UK, where the weather seems pretty unpredictable, "it will be pretty much the same as yesterday" is right about 70% of the time.
I can predict with 99.9% accuracy what the weather will be like in five minutes. Does that mean any prediction less than 99.9% accurate is not impressive?
not really that hard, theoretically (Score:2, Flamebait)
The US Constitution is only about 4 pages, 4400 words (and the bulk of that is structural & procedural minutiae about the US government).
The role of the USSC is simply resolving if a law does or does not conform to the US Constitution.
Given those relatively limited boundaries, it shouldn't be that complex of an issue to predict algorithmically the results of a given judicial ruling, one would think. (The devil's in the details about parsing meaning and context.)
Of course, I believe phrases like "the ri
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Since you fail on the example you tried to parse, I suggest that although the theory is easy, personal prejudice always takes precedence over what is written.
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Determining constitutionality is an important part of the Supreme Court's work, but it's hardly all of it.
Did you know that Federal law varies over the country? The law as written is the same, of course, but it's interpreted differently. One of the Supreme Court's functions is to rule on a sample case when it gets too bad.
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The original intent was to prevent the government from having too much power by ensuring that citizens could form militias. Having arms available to everyone (not just the government's army) was an essential part of being able to raise a militia.
The original intent was to make militias possible so that they could avoid having to have a standing army.
They were very big on the idea of not having a standing army.
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Federalist #46 would be to differ.
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No, the original intent was to ensure that slave owners could form militias to prevent slave revolts. The Founders were well aware of the inability of militias to stand against a professional army as consistently demonstrated in the American Revolution.
Yeah, if the colonies' professional army hadn't been able to defeat King George III's militias, we'd all be speaking English now.
Re:not really that hard, theoretically (Score:4, Interesting)
Nonsense, an editorial screed by the New Yorker is meaningless. And if you want to bring context into it, you'll lose even harder.
Firstly, judicial review wasn't even a principle until Marbury v Madison in 1803. So we're talking about the 19th century only.
In cases in the 19th Century, the Supreme Court ruled pretty much only that the Second Amendment does not bar state regulation of firearms. (For example, in United States v. Cruikshank, 92 U.S. 542, 553 (1875), the Court stated that the Second Amendment âoehas no other effect than to restrict the powers of the national government,â and in Presser v. Illinois, 116 U.S. 252, 265 (1886), the Court reiterated that the Second Amendment âoeis a limitation only upon the power of Congress and the National government, and not upon that of the States.â )
Although most of the rights in the Bill of Rights have been selectively incorporated into the rights guaranteed by the Fourteenth Amendment and thus cannot be impaired by state governments, the Second Amendment has never been so incorporated.
It's only since 1939 United States v Miller, that federal court decisions considering the Second Amendment have largely interpreted it as preserving the authority of the states to maintain militias - not the '150 year history' stated in the deliberately-misleading text of the quoted article.
(much of the above is clipped verbatim from http://www.loc.gov/law/help/se... [loc.gov])
In fact, it's ONLY in the latter 20th Century that we've even HAD this debate, as all constitutional commentary and understanding previous to that was universal in its understanding of the 2nd Amendment as an individual right, *not* dependent on being in a militia: http://en.wikipedia.org/wiki/S... [wikipedia.org]
Of course, you further disregard that according to the US code, all males from 17-44 *are* by default in the militia. (http://www.law.cornell.edu/uscode/text/10/311)
lol (Score:2)
Per their own data:
They reviewed 7700 cases.
The court reversed 5077 of those cases.
So the court reverses 66% of cases it sees. Which makes sense, that's what the court does.
So I can get damn close to their results with my model which is: "The court will reverse 100% of the time"
I don't see their model in there, and I don't really care to look that hard. But they said they used the same data previous models did. Most of that data are things like:
Which court heard the origional case?
Was the decision liberal o
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More specifically, if the court is reasonably happy with a circuit court decision, there's no real need for the Supreme Court to intervene. If they Supremes disagree, they might well want to hear the case. I'd suspect that many of the upholdings were matters of different circuit courts making different interpretations, so the Supremes would grab a case and hear it to set consistent binding precedent across the country.
Good news (Score:2)
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Laws are created by men to get a society to work and last. Society is not logically coherent, so why would you expect the laws to be?
70% (Score:2)
is still withing chance because the error bars on the are huge.
Is that really hard? (Score:3)
I'd actually have expected more. I mean, let's be reasonable here:
A 50% accuracy can be achieved by the average unbiased coin. Now throw in the rulings that are easy to foresee because any other decision would be politically suicidal and you should easily arrive at more than 70%.
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Now throw in the rulings that are easy to foresee because any other decision would be politically suicidal
The supreme court doesn't have to worry about political 'suicide.' By design their position was made to be shielded from the problems of politics.
The major weak point in this type of model (Score:2)
...Is that in most cases the decision to 'give cert' for Supreme Court review of given lower-court cases vests with the Justices' law clerks. This may be as weird as that decision to give the Librarian of Congress veto power over unlocking our cellphones, but that's the way it is. How accurate can any model be at delving into the minds of law clerks?
I can predict better than 90% (Score:2, Insightful)
The Supreme Court is dominated by a bunch of fanatic right wing corporate toadies.
So, the decision comes down in favor of corporations (on economic issues) or social conservatives (on social issues).
The Constitution has nothing to do with it.
The Supreme Court is the ultimate cheerleader for our fascist state.
Re:Missing info (Score:4, Informative)
It would be useful to know how many of the court's decisions are affirm vs reverse.
http://www.americanbar.org/con... [americanbar.org]
I did some tallying on table 3 and found the following numbers on total decissions;
Reversed: 58.48%
Vacated: 12.58%
Affirmed: 28.94%
The article doesn't mention whether "vacated" is counted separately or as a reversal.
The graph shows only reversed and affirmed, so I'm assuming vacated counts as a reversal.
If this is the case, reversed and vacated together is 71.06%.
So if you'd guess "Reversed" all the time, you'd be slighly more accurate than the algorithm.
Re: (Score:2)
I know they're not the same; that's why they are different words.
TFA however, does not seem to recognize anything besides "affirmed" and "reversed", so "vacated" must be categorized as either of these.
Since the PDF I linked to grouped "vacated" with "reversed" in some of it's tables, I assumed that must have been what TFA has done, hence my use of the words "assuming vacated counts as a reveral".
Short; it doesn't matter what either of us thinks, it matter how the author of TFA defined these terms.
Re: (Score:2)