www.Justodians.org/Statistical Analysis Of Judicial Misconduct
Statistics Put A Stop To Racial Profiling By N.J. State Police.
Racial profiling has been eradicated just like polio, and the vaccine is statistical analysis. For more than 25 years, the New Jersey State police had targeted minorities in routine traffic stops. This became widely known in New Jersey as being pulled over for driving while black. But whenever this practice was challenged in court, the officers would make up some nonsense probable cause that was impossible to disprove. It wasn't until citizens started keeping statistics on traffic stops that we were finally able to prove in court that racial profiling existed and that it was epidemic. This effectively ended racial profiling.
We Can Stop Judicial Misconduct The Same Way.
Is it reasonable to believe that police detain people solely because of race but judges never do? Of course not; all other things being equal, White judges are more likely to convict black people than white people. In divorce, women judges are more likely find in favor of women and men judges are more likely to find in favor of men. Judges will swear they are not biased and in fact some may not even be aware that they are. Still other judges may have a personal agenda and are blatantly biased because they know that with out statistical proof, we have no means to challenge them.
If a cop detains you without cause, it can ruin your entire day.
If a judge does it. It can ruin your entire life.
So why aren't we applying statistical analysis where it can make the most difference?
Because there is nothing to analyze. Our courts aren't collecting any trial data.
Why not? Because they know that the numbers will tell us which judges are administrating the law and which ones are making their own.
If we want data on Judicial Misconduct and Judicial Bias we will have to collect it ourselves. Here's how. ProjectCSPAN
See Below For More On This Topic
Let's Try A Simple Experiment
In your google search engine, try typing "Statistics On Racial Profiling". I got 61 hits. That means, there are at least 61 places the public can go to find out which cops are targeting minorities.
Now try typing "Statistics On Judicial Misconduct" in to your google search engine. I got Zero hits. That means that there aren't anyplaces the public can go to find out which judges are abusing their office.
Maybe it's unreasonable to assume "Misconduct" from just statistics alone. So let's remove the "Mis" from Misconduct and try our search again. Your search string will look as follows, ("Statistics on Judicial Conduct"). I got Zero hits.
What about "Statistics on Judicial Bias" Surprise! Zero Hits on Google.
Ok, lets remove our own bias from the question. Try "statistical analysis of judicial findings" Again, Zero Hits.
This experiment indicates that no one is collecting any statistics about the decisions our judges are making and that there is no information that can tell us which judges are administrating our laws and which ones are adminstrating thier own agendas.
A Call For Scholarly Papers.
The benefits of Statistics are to important to be ignored. Statistics extend our lives by identifying which cars we are most likely to die in, which products are most likely to cause us cancer, and which medicines are most likely to have side effects. Statistics improve our lives by showing us how our public policies affect the lives of our people. Statistics have been used to positively prove which teachers are helping their students cheat on standardized tests. And statistics have been used locate where serial killers live just from the knowledge of where their victims are found. Still, statistical analysis is not simple. Even the science of statistically measuring a baseball player's performance is only now starting to be fully understood.
I am making a plea to all statisticians, economist, information technologists, members of the justice community, lawmakers, and most importantly all members of the public who think they have something to contribute. I am asking for all scholarly papers and letters with your ideas on how statistics can be applied to the measurement of judicial bias and for the identification of judges who consistently engage in judical misconduct.
Here are some of the issues that your papers might address:
What specific questions should we be seeking to answer when looking through trial data?
What specific trial data should be collected?
Who will collect the data?
How will the data be collected?
How will the data be published?
Who will Pay for the collection, storage, and publication of the data?
What statistical methods will be used to analyze the data?
How can we get legislation mandating the collection and publication of trial data.
Please mail submissions to: firstname.lastname@example.org
All Serious submissions will be posted here.
Quantitative Analysis of Judicial DecisionMaking
by Thaddeus Hwong, PhD Candidate Osgoode Hall Law School, York University
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