Speranza

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".

## Saturday, December 12, 2015

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