An admirable dissent

On rare occasions you read a dissenting judgment that is reasoned with such brilliant clarity that you may bruise your hands in applauding.

So it is with S (CA377/2017) v R [2018] NZCA 101 (19 April 2018).

Counsel had not told the defendant that there was the option of having a judge alone trial (JAT) and, without consulting the client on the matter elected jury trial on his behalf.

After being convicted at trial the client became aware that he could have had a JAT, and deposed that he would have chosen that mode of trial if the matter had been discussed with him.

What was the status of the error? Under s 232 of the Criminal Procedure Act 2011, if it rendered the trial unfair it would be unnecessary to show that it had affected the outcome of the trial.

The majority two judges of the Court of Appeal held that the error did not render the trial unfair, and this was the point on which one judge dissented.

In the absence of local case law, the majority were guided by the Supreme Court of Canada in R v Turpin [1989] 1 SCR 1296, the Supreme Court of the United States in Singer v United States 380 US 24 (1965), and the High Court of Australia in Brown v R (1986) 160 CLR 171.

This led to the position that, as there was no “right” to a JAT, but only a right to elect jury trial (with JAT being the default position – what one might think of as the factory setting), the trial was not unfair in terms of s 232(4)(b). Patience with subtlety is necessary to follow the reasoning.

Nor, said the majority, was the error fundamental because it had not been included in a list of fundamental errors compiled in an earlier decision of the Court. (But, as the dissenter observed, neither had it been specifically excluded.)

And there was nothing to indicate that the error had affected the outcome of the trial.

It would be wrong for counsel to rely on the majority judgment as permission to avoid taking instructions on election of jury trial whenever there is a choice to be made, pending resolution of the issue in the Supreme Court (in this or a similar case). The Court certainly did not intend to give permission to make errors.

The dissent essentially takes the position that, just as it would be a fundamental error to fail to inform a defendant of the right to elect jury trial, so too is it a fundamental error to fail to inform a client of the option of judge alone trial. It fits with other fundamental errors identified in Hall v R [2015] NZCA 403 at [65]: decisions as to plea, giving evidence, and presenting a defence, and with the duty referred to at [71].

There was no doubt that the jury trial that happened in this case was in its substance fair. What s 232(4) relevantly requires, to amount to a miscarriage of justice, is an error in relation to the trial that resulted in an unfair trial. An “unfair trial” is not defined, but there could be two types of unfairness: substantive and procedural. Is a trial procedurally fair if it proceeds in a mode that was not, when there was a choice, chosen by the defendant?

Another, and probably better, way of looking at this is to ask whether the error rendered the jury trial a nullity. Is the defendant's decision a jurisdiction-creating act? The default mode of trial, judge-alone, occurs without a decision from the defendant, and the jury mode is only activated by the defendant's election. This legislative scheme is consistent with jurisdiction to have a jury trial being created by the defendant's act, and such a trial being a nullity in the absence of such act. At this point you may well be asking, "But Don, what about the Kable case you discussed here on 7 June 2013?"

Update: on 30 July 2018 the Supreme Court granted leave to appeal on the question whether the Court of Appeal was right to dismiss the appeal on the mode of trial point: [2018] NZSC 64, and on 20 December 2018 the Court dismissed the appeal: S (SC 36/2018) v R [2018] NZSC 124, noted here.

Coming to law from science

“Chief Justice French’s background in science has been useful in expressing ideas. He has suggested that identifying elements of administrative justice is “a little like the identification of ‘fundamental’ particles in physics. When pressed, they can transform one into another or cascade into one or more of the traditional grounds of review developed at common law”. [Robert French “The Rule of Law as a Many Coloured Dream Coat” (Singapore Academy of Law 20th Annual Lecture, Singapore, 18 September 2013) at 18.] It has also come in handy when cases before the Court have dealt with scientific concerns, such as D’Arcy v Myriad Genetics Inc, [[2015] HCA 35, (2015) 325 ALR 100] a case about the patentability of DNA. But I wonder whether the real insight to be obtained from what his scientific background has brought to the Chief Justice’s work is to be picked up from his reference to his gratitude that he was exposed to a “culture” of science. That may give some insight into a style of leadership that, to an outside view, seems more collaborative and cooperative, less competitive than is sometime encountered in appellate courts, perhaps because their members are often drawn from a section of the profession with a very different, more competitive culture.” (footnotes from original, inserted in square brackets)

Sian Elias, Address On The Occasion Of The Supreme And Federal Courts Judges’ Conference Retirement Function For The Hon Robert French, Chief Justice Of Australia, Perth, Western Australia, 23 January 2017, at [13].

Science is about finding out what happens, theorising about why it happens, and using that to predict what will happen. Observations usually involve measurement and consequently mathematics. From observations theories can be formulated, again they are usually mathematical. The mathematics should suggest what future observations will be. Predicting observations using mathematics is not always accurate, in which case refinements of the theory are needed. Refinements are prompted by unexpected observations.

For example, looking at magnets and wires, inconsistencies between the predictions of classical mechanics and Maxwell's equations about the forces impelling a current in a conductor, depending on whether the conductor or the magnet is moved, prompted Einstein - at least according to the way he wrote his paper - to develop what later came to be known as the special theory of relativity. The paper announcing this was called (in English translation), On the Electrodynamics of Moving Bodies. Measurements of an event made from different frames of reference (here, in the special case of reference frames moving in straight lines at constant velocities) depend on the point of view, and this in turn has implications for measurements within a single frame of reference. Using observations on the constancy of the speed of light in a vacuum, and theorising that the laws of physics are the same everywhere, Einstein borrowed mathematical techniques developed by Lorentz and showed that some refinements - albeit extremely small ones for the events we normally observe - must be made to Newton’s laws of motion. In a later addendum he showed that the same mathematics he had used also predicted how the energy in matter is proportionate to its mass.

While that sort of mathematics has proved to have great predictive value where observations are made at the macroscopic level, it is not so useful at the sub-atomic level. It seems that the smaller something is, the greater the need for a mathematics incorporating probability. At the sub-atomic level, mathematics is a less accurate predictive tool than it is for events at a larger scale. To compensate for the reduced usefulness of basic mathematics at the sub-atomic level, new forms of mathematics are devised, starting with quantum mechanics. Specialists develop new forms of mathematics to meet the needs of inquiry; Descartes combined algebra and geometry, Newton and Leibniz independently developed calculus (these are all from the Western point of view, in the East these things occurred much earlier), and today there are many forms of specialised mathematics, taking their topics far beyond a lay-person’s understanding.

Unless a mathematical refinement has predictive value for those who must use it, it is worthless to science. The same need for predictive value applies to theories that are not mathematical.But having predictive value is not the same as identifying what is real. The correct interpretation of reality using quantum mechanics has yet to be achieved. A theory may predict observations while not necessarily saying what is real.

Law is like science in that in considering a legal problem a lawyer will try to predict what a court would decide the answer should be. The facts of the legal problem are like measurements in science. But they also claim to speak of reality. Deciding what should be the legal consequence of the forensically decided reality can be like using a scientific theory to predict the result of an experiment. Where a judge has a discretion, or where judgment must be exercised by a court, there is room for a predictive theory to be developed. Those areas of law, where there are discretions to be exercised and evaluations to be made, are different from other areas where the answer to a legal problem can simply be looked up. Discretion and judicial evaluation invite analysis and development of predictive theory.

Two areas of judicial decision-making that have particularly interested me both involve evaluative judgments: deciding whether improperly obtained evidence should be ruled inadmissible, and deciding whether the evidence in a case is sufficient proof of guilt.

My study of the decision whether a court should rule improperly obtained evidence inadmissible is available at https://www.tinyurl.com/dbmadmissibility . There is a method behind my theory which has mathematical analogues: the Cartesian plane, a diagrammatic representation of results of cases, a boundary curve reflecting the rationality of the decision process. It provides a pictorial representation of results, and a method for identifying wrong decisions. Wrong decisions are like inaccurate scientific observations; they do not require rejection of an inconsistent theory unless they build up in number and have consistency among themselves to the point where it is no longer useful to call them wrong.

The sufficiency of evidence as proof of guilt is an inherently probabilistic question. Reasoning with conditional probabilities is something we all do instinctively, but mathematical analysis can reveal fallacies in intuitive thinking. Analogies from mathematical theory can indicate the probative value of items of evidence and the effect of those on the probability that a defendant is guilty. Law does not require mathematical precision, but mathematical method can be a useful tool. I illustrate this in my draft paper (draft because I like to have the opportunity to keep these papers up to date) available at https://tinyurl.com/dbmpropensity .

 Those are illustrations of some of the ways in which a background in science can be of assistance to a lawyer.