What is the purpose in Stinchcombe/McNeil disclosure or O'Connor production of maintenance records and historical data?
Government scientists are right in saying that there is no causal relationship between the historical data and the results of a subsequent subject test.
Factors like dirt in the sample chamber or degradation in the electronic signal coming out of the detector at the end of the sample chamber, over time, may cause error. Inadequate factory calibration may cause error. Negligent re-calibration across the measuring interval of the instrument may cause error. Operator error may cause error. Physiological presentations not contemplated by the design of the instrument can cause error.
Bad record-keeping does not cause error. Anomalous entries in historical data don't cause error.
Government scientists are incorrect in saying that maintenance records and historical data are irrelevant in assessing the scientific reliability of a measurement result. Maintenance records and historical data are relevant to investigation, full answer and defence, expert opinion, and evidence-based fact finding about "reliability".
Control tests, cal. checks, and simulator temperatures do not change Intoxilyzer results. They do not cause error in Intoxilyzer results. You can operate an Intoxilyzer and get an accurate subject test result with no wet-bath simulator or dry gas attached to the Intoxilyzer, but the measurement result won't be "reliable". The result might accidentally be "accurate" but it won't be "reliable". A dead battery, 12-hour clock, is accurate twice a day, but it is not "reliable". The Intoxilyzer 5000EN that you can watch at www.impaired-driving.com may sometimes be accurate, once you get it started after twenty tries, but it is not "reliable". The screening tests used by the Motherisk Lab in Toronto for quantitative analysis, might have been accurate from time to time, but they were not "reliable" for quantitative analysis for a forensic purpose.
The point is: Scientific reliability of the measurement result depends upon transparency of maintenance records and historical data. However, lawyers need to understand the meaning of "scientific reliability of the measurement result". A good starting place, in terms of "instrument reliability" (as opposed to all the additional components of reliability noted in ISO 17025), is the Hodgson definition above. You will find that both Crown and defence experts accept this definition.
Lawyers and Judges need to understand that many factors determine the correctness AND RELIABILITY of the tests. However, the concept of "correctness" or "accuracy" needs to be separated from "reliability".
With the greatest of respect to the Alcohol Test Committee of the Canadian Society of Forensic Science, the many factors are NOT limited to factors apparent at the time of the subject tests. There is therefore a need for defence lawyers to challenge government scientists who make such assertions. Canadian law should not be based on faith-based science but rather empirically-based science.
If a Crown, Judge, or CFS scientist starts heading in the direction of asking defence to prove malfunction or operator error causation of the results, a conscientious defence lawyer needs to re-direct the Court's direction to impact on "reliability" as contemplated by the SCC in St-Onge citing the Hodgson paper and the definition of "reliability" (the image above) contained therein. Please also see R. v. Lam in Ontario.
Field data from maintenance records may point to drift in "precision". "Significant drift" in precision outside of manufacturer's specifications for the instrument is, according to the Hodgson definition, unreliability. If the field data implies a problem with precision, then more stable lab data showing better precision may be probative. If lab data is not available, then the possible causes, trivial or non-trivial of the field data drift in precision are probative. The Court should therefore order the production of the contemporaneous documentation at the time of the inconvenient data.
If forensic purpose quantitative analysis is based on science, then shouldn't lawyers be able to apply a statistical approach to precision, hiring a statistician or other expert to examine field data (and lab data if it is available)? We expect that any mathematical calculation of precision will require data. What data would a statistician use? If analytical chemistry, including toxicology and evidentiary breath testing, is a hard science, then which data would a scientist in a "hard science" use to investigate the truth about ? What data is absolutely necessary for good science? And any "scientific" opinion will need to be consistent with the international standards for good measurement and good laboratory practice.
The ATC and government approach that maintenance records and data are unnecessary to analyze reliability (including significant drift in precision at time of use compared to manufacturer's specifications) implies that forensic "science", is not a "science" at all, but rather, populist bad "science" required for fighting crime. Maybe police "forensic science" is mere technology. It is perhaps faith or policy-based, rather than based in hypothesis and empirical testing. Where, for example, are the compulsory standard operating procedures? Without compulsory standard operating procedures, how can in-the-field results connect with the hard science of the type approval process when the "approved instrument" was originally evaluated? Without compulsory initial inspection of the individual Intoxilyzer or drug tester, as to manufacturer's specifications, to ensure that it connects with the type approval evaluated instrument, the in-the-field results of the individual Intoxilyzer or drug tester can't be considered reliable.
Maybe government experts assume that defence lawyers won't dig deeply enough into their non-empirically based policies and positions. Defence lawyers need to dig into "reliability" issues.
The Motherisk Inquiry Report and other wrongful conviction inquiries have taught us that Defence lawyers need to work a lot harder to expose bad science. The end of getting drunk drivers off the road does not justify the means of bad, non-empirical, science. In the hard science of analytical chemistry, we must pay attention to each of "accuracy", "precision", "specificity", and "reliability". Fortunately, Hodgson (as cited by the SCC in R. St-Onge ) has provided us with well-accepted definitions of these terms.