What is the best conceptual analysis of 'onus probandi'?
To what extent is the conceptual analysis of the ordinary language and
legalese 'proof' rooted on what the Romans had behind the 'probandi'? How
'diachronic' should 'conceptual analysis' of "legal proof" be?
In a recent post, re: Grice v Grice, McEvoy was considering 'proof',
'provable', and 'provability', which may be a good occasion to see if we can
analyse this, since he is assuming a problem-solving approach that may leave,
for a Griceian, certain items 'unclarified'.
McEvoy was approaching legal proof from a problem-solving perspective; but
surely this perspective 'presupposes' a constellation of a conceptual
analysis (to echo Collingwood). Consider the proof for murder and the proof
for
theft (I'm simplifying legalese). It may be argued that since the
conceptual analysis of theft includes more elements (or necessary and
sufficient
conditions) than that of murder, the standard of proof would vary. Some legal
philosophers see this as a paradox but not one that rejects conceptual
analysis.
There are different conceptual analysis of proof'. The more philosophically
sound (qua legal philosophy) is the one more akin to the conceptual
analysis of proof in general. But we shall see.
Problem-solving does not feature much in what analytic legal philosophers
have considered about legal proof; instead, alternative conceptual analysis,
and rejection of alleged counter-examples have. So one has to proceed
carefully.
First we should start with a bit of an axiom.
i. Senses should not be multiplied beyond necessity.
ii. "Proof" has only one sense.
The idea that there is 'legal proof' and other types of proof would then
be judged spurious or tendentious.
LEGALESE has a further item of cognate vocabulary -- since we should start
with 'linguistic botanising': "probative". Thus, In reaching the verdict,
the trier of fact has to assess the so-called "probative value" (or
"probative force") of each individual item of evidence which has been received
at
the trial.
An analysis of the concept of "probative value" may play a role at a prior
stage when the judge has to make a ruling on whether to receive the
evidence
In many legal systems, if the judge finds this "probative value"
(concerning a proposed item of evidence) to be low and substantially
outweighed by
countervailing considerations, such as the risk of causing unfair prejudice
or confusion, the judge can refuse to let the jury consider the evidence.
The concept of "probative value" is sometimes confusingly referred to in
legalese (there is legalese and there is legalese) "probative force" -- M.
A. E. Dummett would be delighted: he loved force! The concept of "probative
value" has been analysed in terms of a likelihood ratio. Evidence
(including hearsay evidence) can be more or less PROBATIVE depending on the
value of
the likelihood ratio. The probative value of a blood type match may be
1.0:0.5 (or 2:1) as 50% of the suspect population may have the same blood type
as the accused. But if the blood type is less common and only 25% of the
suspect population has it, the probative value of the evidence is now
1.0:0.25 (or 4:1). The probative value is greater in the latter than in the
former scenario.
There may be an alternative conceptual analysis for "probative value". The
probative value of an item of evidence is assessed contextually. The
probative value of E may be low given one state of the other evidence and
substantial given a different body of other evidence. If some evidence shows
that
a woman has died from falling down an escalator at a mall while she was
out shopping, her husband’s history of spousal battery is unlikely to have
any probative value in proving that he was responsible for her death. But if
the other evidence shows that the wife had died of injuries in the
matrimonial home, the question is whether the injuries were sustained from an
accidental fall from the stairs or inflicted by the husband. The same evidence
of spousal battery will now have significant probative value. On this
alternative conceptual analysis, the "probative value" of an item of evidence
E
is NOT measured simply by the objective context-free likelihood ratio. The
concept of "probative value" is, now, rather, analysed as the degree to
which E increases (or decreases) the probability of the proposition or
hypothesis H in support of or against which E is led. The probative value of E
is
defined, conceptually, as any difference between the probability of H given
E (the posterior probability) and the probability of H absent E (the prior
probability). The probative value of E = P(H|E)−P(H)P(H|E) (the posterior
probability) is derived by applying Bayes’ theorem — that is, by
multiplying the prior probability by the likelihood ratio.
On this second conceptual analysis, the likelihood ratio does not itself
constitute the probative value of E, even it is nevertheless a crucial
component -- a necessary condition -- in the analysis of the concept. A major
difficulty with both analysis of probative value is that for most evidence,
obtaining the figures necessary for computing the likelihood ratio is
problematic (Grice's example, "When did you last see your father?").
Exceptionally, quantitative base rates data exist, as in human blood types.
Where
objective data is unavailable, the fact-finder has to draw on background
experience and knowledge to come up with subjective values. With blood types,
a
critical factor in computing the likelihood ratio is the percentage of the “
suspect population” who has the same blood type as the accused. "Reference
class" is the general statistical term (as "most grices are extinct,
statistically") for the role that the suspect population plays in this
conceptual analysis. But how should the reference class of “suspect
population” be
defined? Should we look at the population of the country -- say, of
Ruritania -- as a whole? Or of the town or the street where the palace is
situated
and the the alleged murder of the King of Ruritania occurred? What if it
occurred at an international airport where most the people around are
foreign visitors? Or what if it is shown that both the accused and the victim
were at the time of the alleged murder inmates of the same prison? Should we
then take the prison population as the reference class? The distribution of
blood types may differ according to which reference class is selected.
Sceptics of mathematical modelling of probative value emphasise that data
from different reference classes will have different explanatory power and
the choice of the reference class is open to — and should be subjected to —
contextual argument and requires the exercise of judgment. There would
be, contra H. L. A. Hart, no a-priori, purely analytic, way of determining
the correct reference class. Some legal philosophers have proposed
quantifiable ways of selecting, or assisting in the selection, of the
appropriate
reference class. On one suggestion, the court does not HAVE to search for the
OPTIMAL reference class. A general characteristic of an adversarial system
of trial is that the judge plays a passive role. It is up to the parties
to come up with the arguments on which they want to rely and to produce
evidence in support of their respective arguments. The adversarial setting
makes the "reference class" problem more manageable as the court need only to
decide which of the reference classes relied upon by the parties is to be
preferred. And this can be done by applying one of a variety of technical
criteria that statisticians have developed for comparing and selecting
statistical models.
Another suggestion is to use the statistical method of "feature selection"
instead. The ideal reference class is thus conceptually analysed as the
intersection of all relevant features of the case, and a feature is relevant
if it is correlated to the matter under enquiry. E.g. if the amount of drug
likely to be smuggled is reasonably believed to co-vary with the airport
through which it is smuggled, the country of origin and the time period, and
there is no evidence that any other feature is relevant on which data is
available, the ideal reference class is the class of drug smugglers passing
through that airport originating from that country and during that time
period. Both suggestions have self-acknowledged limitations: not least, they
depend on the availability of suitable data. Now, while statistical methods
have advice to offer on how courts should judge quantitative evidence, they
do so “in a way that supplements normal intuitive legal argument rather
than replacing it by a formula.
The "reference class" problem is not confined to the probabilistic
assessment of the probative value of individual items of evidence. It is a
general
difficulty with a mathematical approach to legal PROOF, and that's why it
is of particular interest to the analytic legal philosopher. The same
problem arises on a probabilistic interpretation of the standard of legal
proof
when a court has to determine whether the standard is met based on all the
evidence adduced in the case. How does the "reference-class" problem can
arises in this connection? Let it be that the plaintiff sues Blue Bus Company
to recover compensation for injuries sustained in an accident. The
plaintiff testifies and the court believes on the basis of the plaintiff's
testimony, that the plaintiff was run down by a recklessly-driven bus. It was,
alas, dark and the plaintiff can NOT really tell whether the bus belonged to
The Blue Bus Company. Assume that there is evidence which establishes that
The Blue Bus Company owns 75% of the buses in the capital of Ruritania, where
the accident occurred, and the remaining 25% is owned by The Red Bus
Company. To use the data as the basis for inferring that there is p = 0.75
that
the bus involved in the accident was owned by The Blue Bus Company would
seem to privilege the "reference class" of "buses operating in the capital of
Ruritania" over other possible reference classes such as "buses plying the
street in the capital of Ruritania where the accident occurred" or "buses
operating at the time in question". I.e. A different "reference class" may
produce a very different likelihood ratio. It is crucial how the "reference
class" is CHOSEN and this is ultimately a matter of argument and judgment.
Any choice of a "reference class" other than the class that shares every
feature of the particular incident, which is, in effect, the unique incident
itself, is in principle contestable.
Critics of the mathematisation of legal "proof" raise this point of the
arbitrariness of the 'reference class' as an example of inherent limitations
to the axiomatic modelling of probative value. But there is an alternative:
an explanatory analysis of legal "proof". This explanatory analysis of
'legal proof' has the advantage of avoiding the "reference class" problem
because it does not attempt to quantify probative value. Suppose a man is
accused of killing his wife. Evidence is produced of the man's extra-marital
affair. The unique "probative value" of the accused’s infidelity can NOT be
mathematically computed from statistical base rates of infidelity and
uxoricides. In assessing its "probative value", the court looks instead at how
strongly the evidence of infidelity supports the explanation of the events put
forward by the side adducing the evidence and how strongly it challenges
the explanation offered by the opponent. The prosecution may be producing the
evidence to buttress its case that the accused wanted to get rid of his
wife so that he could marry his mistress. The defence may be advancing the
hypothesis that the couple was unusual in that they condoned extra-marital
affairs and had never let it affect their marriage. How much "probative
value" the evidence of infidelity has depends on the strength of the
explanatory
connections between it and the competing hypotheses and this is not
something that can be quantified.
But the disagreement in this debate is not as wide as it might appear. The
critics concede that axiomatic models for evaluating evidence in law may
be useful. What they object to is scholarship arguing that such models
establish the correct or accurate probative value of evidence, and thus
implying
that any deviations from such models lead to inaccurate or irrational
outcomes. On the other side, it is acknowledged that there are limits to
mathematical formalisation of evidential reasoning in law and that context,
argument and judgment do play a role in identifying the "reference class".
We have thus far concentrated on "probative value" of an individual item
of evidence. But the conceptual analysis should extend to the TOTAL body of
evidence presented at the trial. The law assigns the legal "onus probandi"
between parties to a dispute. E.g. at a criminal trial, the accused is
presumed innocent; "onus probandi" is on the prosecution to prove that the
accused is guilty as charged. To secure a conviction, the body of evidence
presented at the trial must be sufficient to meet the standard of "proof". A
verdict will be given in favour of the side bearing the "onus probandi" iff,
having considered all of the evidence, the fact-finder is satisfied that the
applicable standard of "proof" is met.
Now, the standard of "proof" may receive different conceptual analyses. On
one such analysis, the standard of "proof" is a probabilistic threshold.
In civil cases, the standard is the "balance of probabilities" or, the
"preponderance of evidence". The plaintiff may satisfy this standard and
succeed
in his claim only if there is, on all the evidence adduced in the case,
more than 0.5 probability of his claim being true. At a criminal trial, the
standard for a guilty verdict is -- to use a very 'dogmatic' or rather
anti-sceptical turn of phrase which is SO LEGALESE it hurts: "legal proof
beyond
a reasonable doubt". Here the probabilistic threshold is thought to be
much HIGHER than 0.5, but courts have eschewed any attempt at authoritative
quantification. Typically a notional value such as 0.9 or 0.95 is assumed by
the legal philosopher for the sake of his analysis. For the prosecution to
secure a guilty verdict, the evidence adduced at the trial must establish
the criminal charge to a degree of probability that crosses this threshold.
Where there is an intermediate standard of “clear and convincing evidence”
which is reserved for special cases, the probabilistic threshold is said
to lie somewhere between 0.5 and the threshold for "proof beyond reasonable
doubt".
Some conceptual-analytic legal philosophers employ decision-theory to
develop a framework for setting the probabilistic threshold that represents
the
standard of legal proof. Since the attention in this area of the law tends
to be on the avoidance of errors and their undesirable consequences, it is
convenient to focus on disutility. The expected DISutility of an outcome
is the product of the DISutility -- the social costs -- of that outcome and
the probability of that outcome. Only two options are generally available
to the court. In criminal cases, it must either convict or acquit the
accused; in civil cases it has to give judgment either for the plaintiff or for
the defendant. At a criminal trial the decision should be made to convict
where the expected DISutility of a decision to acquit is greater than the
expected DISutility of a decision to convict. This is so as to minimize the
expected DISutilities. If we formulate the conceptual analysis axiomatically,
we have:
pDag>(1−P)Dci -- where "p" is the probability that the accused is guilty
on the basis of all the evidence adduced in the case; "Dag" is the
DISutility of acquitting a guilty person and Dci" is the DISsutility of
convicting
an innocent person. A similar conceptual analysis applies to civil cases:
the defendant should be found liable where the expected DISutility of finding
him NOT liable when he is in fact liable exceeds the expected DISutility
of finding him liable when he is in fact not liable. On this conceptual
analysis, a person should be convicted of a crime only where p is greater than:
11+DagDci. A similar conceptual analysis applies in civil cases, except
that the two DISutilities (Dag and Dci) are replaced by their civil
equivalents, framed in terms of the DISutility of awarding the judgment to a
plaintiff who in fact does not deserve it and the DISutility of awarding the
judgment to a defendant who in fact does not deserve it. On this conceptual
analysis, the crucial determinant of the standard of "legal proof" becomes the
ratio of the two DISutilities. In the civil context, the DISutility of an
error in one direction is deemed equal to the DISutility of an error in the
other direction. Hence, a probability of liability of greater than 0.5 would
suffice for a decision to enter judgment against the defendant. The
situation is somewhat different at a criminal trial: Dci, the DISutility of
convicting an innocent person is considered far greater than Dag, the
disutility
of acquitting a guilty person. Hence, the probability threshold for a
conviction should be much higher than 0.5.
An objection to this conceptual analysis may be that it is incomplete, and
that it allows for alleged counter-examples, as Grice would put it. Thus,
it is not enough to compare the costs of erroneous verdicts. The utility of
an accurate conviction and the utility of an accurate acquittal should
also be considered and factored into the equation. This results in the
following modification of the conceptual analysis for setting the standard of
legal "proof":
11+Ucg−UagUai−Uci -- where "Ucg" is the utility of convicting the guilty,
"Uag" is the utility of acquitting the guilty, "Uai" is the utility of
acquitting the innocent and "Uci" the utility of convicting the innocent.
Since the relevant utilities depend on the individual circumstances, such as
the seriousness of the crime and the severity of the punishment, this
decision-theoretic conceptual analysis of the standard of legal "proof" leads
to
the conclusion that the probabilistic threshold should vary from case to case
-- which should not please all legal philosophers (it pleased H. L. A.
Hart). In other words, the standard of "legal proof" is flexible or as Hart
has it, "floating". This conceptual analysis is perceived by some to be
problematic. First, the conceptual analysis falls short descriptively. The law
is alleged to require the court to apply a FIXED standard of "legal proof"
for ALL cases within the relevant category. All criminal cases are governed
by the same high standard; all civil cases are governed by the same lower
standard. That said, it is unclear whether fact-finders in reality adhere
strictly to a FIXED standard of "legal proof" (but this does not mean that
'proof' now has two senses!).
The conceptual analysis includes a valuational component: it advances a
claim about what the law OUGHT to be, is DEEMED to be, and not what it
perhaps alas is. The standard of "legal proof" ought to vary from case to
case.
But this conceptual analysisl faces a second objection. In principle, civil
litigants have the same two rights that we shall identify. Moral harm
arises as an objective moral FACT when a person is erroneously convicted of a
crime. Moral harm is distinguished from, to use McEvoy's favourite adjective,
"mere" harm (in the form of pain, frustration, deprivation of liberty and
so forth) that is suffered by a wrongfully convicted and punished person.
While an accused person does have a right not to be convicted if innocent, an
accused person does NOT have the right to the most accurate procedure
possible for ascertaining their guilt or innocence. However, an accused person
does have the right that a certain weight or importance be attached to the
risk of moral harm in the design of procedural and evidential rules that
affect the level of accuracy. An accused person has, further, the right to a
consistent weighting of the importance of moral harm and this further right
stems from their right to equal concern and respect. Such a conceptual
analysis carries an implication. It is arguable that to adopt a "floating"
standard of "legal proof" offends the second right insofar as it means
treating an accused person differently with respect to the evaluation of the
importance of avoiding moral harm. This difference in treatment is reflected
in
the different level of the risk of moral harm to which an accused person is
exposed.
There is a still another objection to the "floating" standard of legal
"proof". Fact-finding is a theoretical exercise that engages the question of
what to believe about the disputed facts. What counts as "reasonable" for
the purpose of applying the standard of legal "proof beyond reasonable doubt"
is, accordingly a matter for theoretical (or as Grice prefers, 'alethic'),
not practical, reasoning. Only reasons for BELIEF are germane in "alethic"
reasoning. While considerations that bear on the assessment of utility and
disutility provide rather "practical" reasons for action, and thus,
analytically, not a reason TO BELIEVE in the accused’s guilt. Thus, it is
alleged, a decision-theoretical conceptual analysis cannot therefore be used
to
support a variable application of the standard of legal "proof beyond
reasonable doubt".
Another criticism of a conceptual analysis of a flexible standard of
"legal proof" is that it would seem that the maximisation of expected utility
is
a criterion for selecting the appropriate probabilistic threshold to apply
but that it should play no further role in deciding whether that
threshold, once selected, is met on the evidence adduced in the particular
case. It
is not incompatible with the decision-theoretic analysis to insist that the
question of whether the selected threshold is met should be governed
wholly by "alethic" reasons. However, it is arguable that what counts as good
or
strong enough theoretical reason for judging, and hence alethically
BELIEVING, that something is true is dependent on the context, such as what is
at
stake in believing that it is true. Intuitively, as far as ordinary
language goes (to stick with Grice's methodology), more is at stake at a trial
involving the death penalty than in a case of petty shop-lifting.
Accordingly, there should be stronger "alethic" justification for a finding of
guilt
in a trial involving the death penalty (Grice is killed) than in a case of
petty shop-lifting (a grice, an extinct Scottish pig, is stolen). The
conceptual-analytic literature on alethic contextualism and on
interest-relative
accounts of knowledge sd justified true belief can thus be drawn upon to
support a variant standard of legal "proof".
Behind this criticism to this type of conceptual analysis is that the
trier of fact has to make a finding on a disputed factual proposition based on
his alethic BELIEF in the proposition. This is contentious. It may be
argued that, as far as ordinary language goes, some beliefs are involuntary.
It
would seem that we cannot believe something by simply DECIDING to believe
it. The dominant view is that beliefs are context-independent. At any given
moment, we cannot believe something in one context and not believe it in
another. On the other hand, legal fact-finding involves choice and decision
making and it is dependent on the context. E.g. evidence that is strong
enough to justify a finding of fact in a civil case may not be strong enough
to
justify the same finding in a criminal case where the standard of "legal
proof" is higher. The fact-finder has to base his findings, allegedly, not
on what he believes but what he accepts. Belief and acceptance are what
Grice calls 'psychological attitudes". They are different psychological
attitudes that one can have in relation to a proposition. To *accept* that p is
to
have or adopt a policy of deeming, positing or postulating that p, i.e. of
including that proposition or rule among one’s premises for deciding what
to do or think in a particular context.
So perhaps we should go back to an axiomatic conceptual analysis of 'legal
proof'. Alas, understanding standards of "legal proof" in terms of
mathematical probabilities has been found to be controversial. It is said to
raise
a number of paradoxes. E.g. The defendant, Blue Bus Company, owns 75% of
the buses in the capital of Ruritania where the plaintiff was injured by a
recklessly driven bus and the remaining 25% is owned by The Red Bus Company.
No other evidence is presented. Leaving aside the reference class problem
there is a p = 0.75 that the accident was caused by a bus owned by the
defendant. On the probabilistic interpretation of the applicable standard of
"legal proof", i.e. the balance of probabilities, the evidence should be
sufficient to justify a verdict in the plaintiff’s favour. But lawyers seem to
think that the evidence is insufficient. The puzzle is why this is so.
Various attempts have been made to solve this puzzle. On one solution, the
statistical evidence -- the 75% ownership of buses -- is not CAUSALLY
CONNECTED
with the fact sought to be proved (the accident) and as such cannot
justify belief in or knowledge of the fact (vide Grice "The Causal Theory of
Perception"). But it is questionable that the court should aim at knowledge of
the disputed fact and not simply at accuracy in its finding. Another paradox
in the mathematical interpretation of the standard of "legal proof" is the
"conjunction paradox". To succeed in a civil claim or a criminal
prosecution, the plaintiff or the prosecution will have to PROVE the facts --
or
"elements," as legalese goes (legalese can be corpuscularianistic) -- that
constitute the civil claim or criminal charge that is before the court.
Imagine a claim under the law of negligence that rests on two elements: a
breach
of duty of care by the defendant (element A) and causation of harm to the
plaintiff (element B). To win the case, the plaintiff is legally required to
PROVE "A and B". Let "A and B" be mutually independent events. Suppose the
evidence establishes "A" to a p = 0.6 and "B" to a p = 0.7. On the
mathematical interpretation of the standard of "legal proof", the plaintiff
should
succeed in his claim since the probability with respect to each of the
elements exceeds 0.5. However, according to the multiplication rule of
conventional probability calculus, the probability that "A and B" are both
true is
the product of their respective probabilities. In this example, p s only
0.42 (= 0.6 x 0.7). Thus, the overall probability is greater that the
defendant deserves to win than that the plaintiff deserves to win and yet the
verdict is awarded in favour of the plaintiff. One way of avoiding this
"conjunction" paradox is to take the position that it should not be enough for
each "element" to cross the probabilistic threshold. The plaintiff or the
prosecution should win iff the probability of the plaintiff’s or prosecution’
s case as a whole exceeds the applicable probabilistic threshold. So, the
plaintiff should lose since the overall p < 0.5. But this suggested solution
may not satisfy all. The required level of overall probability would then
turn on how many "elements" the civil claim or criminal charge happens to
have. The greater the number of elements, the higher the level of probability
to which, on average, each of them must be PROVED. This is thought to be
arbitrary and hence objectionable. As commentators have noted, the legal
conceptual anaysis of "theft" contains more "elements" than the legal
conceptual analysis of "murder". Criminal law is not the same in all countries
--
never mind Ruritania. We may take the following as a convenient
approximation of what the law is in some countries, including Ruritania.
"X has murdered Y" iff (i) X's act caused the death of Y & (ii) that was
done with the intention of causing the death.
"X has robbed Y" iff (i) X intends to take Y's property & (ii) X is
dishones in taking the Y's property & (iii) X removes Y's property from Y's
possession & (iv) Y lacks consent
Since the conceptual analysis of the offence of theft contains twice the
number of "elements" (or necessary and sufficient conditions, or 'throngs',
to use Grice's jargon) as compared to the conceptual analysis of the offence
of murder, the individual elements for theft would have to be PROVED to a
much higher level of probability, in order for the probability of the
"conjunction" of (i) & (ii) & (iii) & (iv) to cross the overall threshold than
the individual elements for the much more serious crime of murder. This is
intuitively unacceptable, even for a thief, if not a murderer!
Fortunately, there is another conceptual analysis we can bring in to
resolve the "conjunction" paradox, which, admittedly, moves away from thinking
of the standard of "legal proof" as a quantified threshold of absolute
probability. We may analyse it, instead, as a probability ratio. The
fact-finder
has to compare the probability of the evidence adduced at the trial under
the plaintiff’s theory of the case with the probability of the evidence
under the defendant’s theory of the case (the two need not add to 1), and
award
the verdict to the side with a higher probability. One criticism of this
interpretation of the standard of "legal proof" is that it ignores, and does
not provide a basis for ignoring, the margin by which one probability
exceeds the other, and the difference in probability may vary significantly
for
different elements of the case.
But one may allege there is a deeper problem with the probabilistic
conception of the standard of "legal proof", and it is that there does not
seem
to be a satisfactory interpretation of probability that suits the forensic
context. The only plausible candidate is the subjective probability
according to which probability is construed as the strength of alethic belief.
The
evidence is sufficient to satisfy the legal standard of proof on a disputed
question of fact—for example, it is sufficient to justify the positive
finding of fact that the accused killed the victim—only if the fact-finder,
having considered the evidence, forms a sufficiently strong belief that the
accused killed the victim. Guidance on how to process evidence and form
beliefs can be found in a mathematical theorem known as Bayes’ theorem; it is
the method by which an ideal rational fact-finder would revise or update his
beliefs in the light of new evidence. To return to our earlier hypothetical
scenario, suppose the fact-finder initially believes the odds of the
accused being guilty is 1:1 (prior odds) or, putting this differently, that
there is a 0.5 probability of guilt. The fact-finder then receives evidence
that blood of type A was found at the scene of the crime and that the accused
has type A blood. 50% of the population has this blood type. On the
Bayesian approach, the posterior odds are calculated by multiplying the prior
odds
(1:1) by the likelihood ratio which is 2:1. The fact-finder’s belief in
the odds of guilt should now be revised to 2:1. The probability of guilt is
now increased to 0.67. The subjectivist Bayesian theory of legal
fact-finding has come under attack.
1) ascertainment of the likelihood ratios is highly problematic.
2) Bayesi's theory is not sensitive to the weight of evidence which,
roughly put, is the amount of evidence that is available.
3) While Bayes's theorem offers a method for updating probabilities in the
light of new evidence, it is silent on what the initial probability should
be. In a trial setting, the initial probability cannot be set at zero
since this means certainty in the innocence of the accused. No new evidence
can
then make any difference. Whatever the likelihood ratio of the evidence,
multiplying it by zero (the prior probability) will still end up with a
posterior probability of zero. On the other hand, starting with an initial
probability is also problematic. This is especially so in a criminal case. To
start a trial with some probability of guilt is to have the fact-finder
harbouring some initial belief that the accused is guilty and this is not easy
to reconcile with the presumption of innocence.The suggestion of starting
the trial with prior odds of 50:50 can and has be criticised.
4) we have thus far relied for ease of illustration on highly simplified—
and therefore unrealistic—examples. In real cases, there are normally
multiple and dependent items of evidence and the probabilities of all possible
conjunctions of these items, which are numerous, will have to be computed.
These computations are far too complex to be undertaken by human beings. The
impossibility of complying with the Bayesian model undermines its
prescriptive value.
5) Bayes's theory has it the wrong way round. What matters is not the
strength of the fact-finder’s belief itself. The standard of proof should be
understood instead in terms of what it is reasonable for the fact-finder to
believe in the light of the evidence presented, and this is a matter of the
degree to which the belief is warranted by the evidence. Evidence is
legally sufficient where it warrants the contested factual claim to the degree
required by law. Whether a factual claim is warranted by the evidence turns
on how strongly the evidence supports the claim, on how independently
secure the evidence is, and on how much of the relevant evidence is available
to
the fact-finder, i.e. , the comprehensiveness of the evidence. Some are
against identifying degrees of warrant with mathematical probabilities.
Degrees of warrant do not conform to the axioms of the standard probability
calculus. For instance, where the evidence is weak, neither p nor not-p may be
warranted; in contrast, the probability of p and the probability of not-p
must add up to 1. Further, where the probability of p and the probability of
q are both less than 1, the probability of p and q, being the product of
the probability of p and the probability of q, is less than the probability
of either. On the other hand, the degree of warrant for the conjunction of
p and q may be higher than the warrant for either. We can have a legal
application of a general theory of epistemology.
6) Research in experimental psychology suggests that fact-finders do not
evaluate pieces of evidence one-by-one and in the unidirectional manner
required under the mathematical model. A holistic approach is taken instead
where the discrete items of evidence are integrated into large cognitive
structures variously labelled as mental models, stories, narratives and
theories
of the case, and they are assessed globally against the legal definition
of the crime or civil claim that is in dispute. The reasoning -- vide Grice,
"Aspects of reason" -- does not progress linearly from evidence to a
conclusion; it is bi-directional, going forward and backward: as the
fact-finder’
s consideration of the evidence inclines him towards a particular verdict,
his leaning towards that conclusion will often produce a revision of his
original perception and his assessment of the evidence.
The holistic nature of evidential reasoning as revealed by these studies
has inspired alternative conceptual analyses that are of a non-mathematical
nature. One alternative, already mentioned, is the explanatory or relative
plausibility one. This analysis contends that fact-finders do not reason in
the fashion portrayed by the Bayesian model. Instead, they engage in
generating explanations or hypotheses on the available evidence by a process
of
abductive reasoning or drawing “inferences to the best explanation”, and
these competing explanations or hypotheses are compared in the light of the
evidence. The comparison is not of a hypothesis with the negation of that
hypothesis, where the probability of a hypothesis is compared with the
probability of its negation. Instead, the comparison is of one hypothesis with
one or more particular alternative hypotheses as advocated by a party or as
constructed by the fact-finder himself. On this approach, the plausibility
of X, the factual account of the case that establishes the accused’s guilt
or defendant’s liability, is compared with the plausibility of a hypothesis
Y, a specific alternative account that points to the accused’s innocence
or the defendant’s non-liability, and there may be more than one such
specific alternative account.
On this theory, the evidence is sufficient to satisfy the preponderance of
proof standard when the best-available hypothesis that explains the
evidence and the underlying events include all of the elements of the claim.
Thus, in a negligence case, the best-available hypothesis would have to
include
a breach of duty of care by the plaintiff and causation of harm to the
defendant as these are the elements that must be proved to succeed in the
legal claim. For the intermediate clear-and-convincing standard of legal
proof,
the best-available explanation must be substantially better than the
alternatives.To establish the standard of proof beyond reasonable doubt, there
must be a plausible explanation of the evidence that includes all of the
elements of the crime and, in addition, there must be no plausible explanation
that is consistent with innocence. Now, the relative plausibility theory
itself is perceived to have a number of shortcomings.
1) the theory portrays the assessment of plausibility as an exercise of
judgment that involves employment of various criteria such as coherence,
consistency, simplicity, consilience and more. However, the theory is sketchy
on the meaning of plausibility and the criteria for evaluating plausibility
are left largely unanalyzed.
2) Despite the purported utilisation of “inference to the best explanation”
reasoning, the verdict is not controlled by the best explanation. For
instance, even if the prosecution’s hypothesis is better than the defence’s
hypothesis, neither may be very good. In these circumstances, the court must
reject the prosecution’s hypothesis even though it is the best of
alternatives. One suggested mitigation of this criticism is to place some
demand on
the epistemic effort that the trier of fact must take (for example, by
being sufficiently diligent and thorough) in constructing the set of
hypotheses from which the best is to be chosen
3) While it may be descriptively true that fact-finders decide verdicts by
holistic evaluation of the plausibility of competing explanations,
hypotheses, narratives or factual theories that are generated from the
evidence,
such forms of reasoning may conceal bias and prejudice that stand greater
chances of exposure under a systematic approach such as Bayesian analysis. A
hypothesis constructed by the fact-finder may be shaped subconsciously by a
prejudicial generalisation or background belief about the accused based on
a certain feature, say, his race or sexual history. Individuating this
feature and subjecting it to Bayesian scrutiny has the desirable effect of
putting the generalisation or background belief under the spotlight and
forcing the fact-finder to confront the problem of prejudice.
But problems are fine, if legal philosophy's problems were all solved,
legal philosophy, understood as the conceptual analysis of legalese -- as this
legalese is akin to ordinary language (alla Grice or Hart) -- would be
dead!
Cheers,
Speranza
REFERENCES:
Grice, The causal theory of perception, Aristotelian Society.
Grice, Way of Words
Grice, Aspects of Reason: the John Locke Lectures, Oxford: Clarendon
Hart, The concept of law
Toulmin, Probability, in Flew, "Conceptual Analysis".
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