The Supreme Court Splits the baby in the Scottsdale Crime Lab Cases.

The highly anticipated Arizona Supreme Court opinion regarding the Scottsdale Crime Lab scandal was issued yesterday.   In a very Solomon like decision, the Court granted both sides some relief.

 

The decision contains a lot of legal nuance requiring explanation. Here is a summary and a few thoughts:

 

Admissible Is Not The Same As Reliable

 

While the Court decided the blood alcohol measurements are admissible - they did not hold they are reliable. There is a big difference.  As a matter of fact, the Court expressed its concerns with the Scottsdale Crime Lab's "shaky" evidence. 

 

The Court merely held the prosecution may present the blood alcohol measurements to a jury and argue they are reliable.  The jury will make the final decision.

 

This standard is similar to a finding there was probable cause for a person's case to proceed to trial.  However, at trial, the same evidence will now need to exceed a much higher threshold - beyond reasonable doubt.

 

What Effect Did Yesterday's Decision Have On The Lower Courts' Rulings?

 

There were two lower court rulings: (1) the trial court's ruling suppressing the evidence; and (2) the Court of Appeals ruling reversing.

 
The Arizona Supreme Court vacated the relevant portions of the Court of Appeals decision and the trial court's ruling.  It then issued a new opinion which provided additional guidance on the admissibility of scientific evidence in a jury trial.
 
The Legal Boundaries Of The Supreme Court's Decision.
 
A few years ago, Arizona adopted something called the Daubert standard for the admission of scientific evidence. This was reflected by an amendment to Rule 702 of the Arizona Rules of Evidence.
 
The Court's holding here was limited to only one of the requirements of Rule 702.  Specifically the ruling is limited to subsection (d) of Rule 702, which focuses on the reliable application of a methodology to the facts.
 
What Did Each Side Get Out Of The Supreme Court's Decision?
 
The prosecution avoids mass dismissals of cases where they claim a driver was impaired, but now they have to persuade a jury in every case that the crime lab's forensic malpractice does not matter.
 
The defense is primarily benefited in two ways: (1) the right to present all the evidence of the crime lab's malpractice is firmly established; and presumably (2) the right to obtain evidence of software malfunctions and errors from the crime laboratory also appears to be affirmed. 
 
The Court's acknowledgement that the evidence presented at the 17 day pretrial hearing was both relevant and admissible at trial, implicitly holds that the defense has a right to this evidence in discovery.  This is a significant change.
 
The majority of the evidence presented to the trial court by the defense was not provided by the prosecution.  It was obtained through the collaboration of the defense community and through requests made pursuant to Arizona's public records laws.  
 
Moreover, before the pretrial hearing, there was a court order requiring the Scottsdale Crime Lab to provide the defense with all the data produced in 2011.  They were given a significant amount of time to comply, but did not even attempt to gather the information. Instead, the prosecution appealed the order, and the Arizona Court of Appeals reversed.  
 
The prosecution convinced the appellate court that the defense was merely on a "fishing expedition."  However, in hindsight, it turns out there were some pretty big fish in the pond. We can only imagine what we would have found if the yesterday's opinion had been in place at that time.
 
The holding also appears to clear the way for the defense to present a jury with evidence of the hundreds of catastrophic software malfunctions resulting in unreliable and misleading evidence.  The jury may now discover, that for years, the lab hid this damming evidence.  They may hear of internal crime lab emails from analysts admitting to deleting "incorrect results." 
 
And yes, prior to this decision, the prosecution vigorously argued the jury should not hear this evidence.
 
Does This Decision End The Debate Over The Scottsdale Crime Lab's Forensic Malpractice Issues?
 
Nope.
 
The issues will continue to be litigated - one case at a time. However, we now have some new rules of the road that empower the defense to present their case.  
 
In Sum
 
...the decision means we can't shop for justice at Costco. While there will not be a bulk dismissal of consolidated cases, we still get to present these issues one case at a time...jury by jury. 
 
This could take a while.
 
RELATED:
 
 

Arizona Supreme Court: Scottsdale Crime Lab Update

Tomorrow around 10:00 a.m. the Arizona Supreme Court will issue its decision regarding the Scottsdale Crime Lab.  Here are some of the new stories about the case of STATE v HON. BERNSTEIN/HERMAN:

I will provide a summary of the Supreme Court's opinion following its release.

Lawrence Koplow

Measuring and Counting

 MEASURING

Measuring is the assignment of a number, and all the uncertainties of that of that number, to something.  The purpose of assigning a number is to give meaning to the object measured.

  • Uncertainty: A bag placed upon a scale shows its weight to be 41 pounds.  If the bag must be less than 50 pounds, then the number produced by the scale indicates it meets this requirement.  However, you must know how far from its true value might the 41 pound number be off by?  Uncertainty is the amount of doubt (e.g. the amount of possible variation) you should expect that number might be off.
  • Fit for Purpose: Assume there are two scales.  The same bag weighing 41 pounds is place on both scales.  However, it was determined that Scale A produces numbers that can be off by as much as 30 pounds.  It was also determined that the number produced by Scale B merely off by as much as 3 pounds.  Knowing the amount of uncertainty contained in the number helps distinguish counting from measuring.  Knowing the uncertainty allows you determine if the measurement is fit for the purpose of determine if the object exceeds 50 pounds.

Measuring relies upon estimation.  The choice of data, the methodologies employed, and level of quality measures used tells you how confident you can be in the estimation.  Once you have a reliable estimation of how close a number may be (or not be) to the true value, you can make informed decision as to what purposes the number can be used - and not used.  

 

COUNTING

Counting is not the same as measuring.  However, the two are often confused.  Counting is usually a technique within a measuring process (methodology).  Counting can result in an exact number.  However, measurement will never claim to represent a true value. Measurements are merely estimations.

Counting an exact amount of something is often not possible or practical.  The thing you are intending to measure (the measurand), the matrix it is found in, or the level of accuracy required may make counting impossible.   Thus a system is needed to provide a reliable estimation which you can rely upon.  

Some things to take into account when making an estimation:

  • Distinguishing: Some molecules are so similar to others that it is often impossible continuously distinguish them from each other.  Thus, they cannot be easily counted.
  • Location: Some substances are contained in places we cannot practically enter to count them.  The best way to know how much alcohol is affecting a person's brain at a particular time would be to take a sample of brain tissue.  However, society has not yet determined such a procedure falls outside the protections of a person's 4th Amendment rights.
  • Gas Chromatographs: The results of a gas chromatograph are often used to determine whether a person's alcohol concentration is above a legal limit in DUI cases.  However, the machine does not measure a person's blood alcohol concentration.  If properly used, the machine merely counts the number ethanol molecules in a gas portion of a headspace vial.  Thus, it indirectly counts a microscopic amount ethanol from a tiny sample.  

A measurement based upon a machine's indirect count of a substance results from combining it with algorithms, numerous assumptions, and historical data regarding the past performance of the machine (and software) used in the process.  This is known as an uncertainty calculation.

In this manner, measuring requires much more than counting.  Measuring requires more than merely assigning a number to an object.  More importantly, one can assign a number to an object but not create a measurement.  When this occurs it is not a measurement.  It is a misrepresentation.

 

Counting is what you do to get a number.  Measuring is what you do if you want to know the truth about the number.