Evidence Evidence is unprocessed pieces of data, material, or information. Proof People will demand proof if you claim anything new or innovative. Difference between proof and evidence: A fact that indicates that something is genuine is known as proof.
The proof is a definitive judgment that eliminates all legal question, whereas evidence simply points to a fact or assertion.
Evidence is data that leads to the conclusion that something is genuine or authentic. Before establishing a claim, each inventor must substantiate their innovation. The proof is complete and irrefutable. The evidence is speculative. If the murder suspect also has a motivation and an opportunity to do the crime, that adds to the evidence. The investigators will have proof of his guilt if they can gather enough evidence.
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Fact is arrived at after investigation or experiment. Evidence begins an investigation. Good article Aron! Straight to the point! This opens up a whole can of worms for science and evidenced-based practices, such as psychology. Science provides continent truths, based on theory and experimental evidence. All scientific facts are open to disproof. Since scientific facts are the strongest facts about nature, all facts about nature are contingent truths. Analytic truths are based on rules plus primitive truths, the latter accepted as given or hypotheticals or assumptions or postulates or axioms: mathematical truths and logical truths.
Analytic truths are not contingent but are true in themselves. The notion that facts are superior to evidence is a legal fiction since evidence is required to give credence to a fact and the more evidence that can be given the more credence is given to a fact as true, even though that truth is contingent on the reliability of the evidence, the methods used to provide that evidence, and the theories that relate one kind of evidence to others.
Your email address will not be published. It has been argued that meeting a legal standard of proof is not merely or fundamentally a matter of adducing evidence to establish a mathematical probability of liability beyond a certain level. Standards of proof should be interpreted in epistemic rather than probabilistic terms. According to one interpretation, the evidence is sufficient to satisfy a standard of proof only if it is capable of justifying full or outright belief in the material facts that constitute legal liability and bare statistical evidence, as in our examples, cannot justify such a belief.
Nelkin ; Smith ; Buchak ; Ho 89— Evidence normically supports a proposition just in case the situation in which the evidence is true and the proposition is false is less normal, in the sense of requiring more explanation, than the situation in which the evidence and the proposition are both true. Where all that we have is statistical evidence, it could just so happen that the material proposition is false it could just so happen that the accident-causing bus was red or that the accused was the one who refused to join in the murder , so no further explanation is needed where the proposition is false than where it is true Smith High probability of liability alone will not suffice.
It is further claimed that the relevant knowledge necessary for a finding of liability cannot be obtained from statistical evidence alone Littlejohn and ; Blome-Tillmann ; Moss and forthcoming.
An alternative argument is that knowledge requires the ruling out of all relevant alternatives and, to take our prison scenario, there is no evidence that addresses the possibility that the defendant was the one who refrained from joining in the attack or the possibility that the defendant is less likely to be guilty than an arbitrary prisoner in the yard. See Moss forthcoming; Moss Gardiner a adapts the relevant alternatives framework to model legal standards of proof in a non-mathematical way while eschewing a knowledge account of those standards.
Another possible explanation for the failure to know relies on the notion of sensitivity. The belief that the defendant is liable is not sensitive to the truth where it is based on bare statistical evidence; in the bus example, evidence of the market share of buses remain the same whether it is true or not that a blue bus caused the accident cf. Enoch, Spectre, and Fisher ; Enoch and Fisher ; Enoch and Spectre — while suggesting that the lack of knowledge has generally to do with the insensitivity of the belief, the authors deny that knowledge should matter to the imposition of legal liability.
Yet another explanation is that it is unsafe to find a person liable on bare statistical evidence. Though safety is sometimes treated as a condition of knowledge in that knowledge requires a true belief that is safe , one can treat safety as a condition for finding the defendant liable without also taking the position that the finding must be based on knowledge of liability.
Safety is commonly understood in terms of whether a belief formed on the same basis would be true in close possible worlds. Roughly, a finding of liability is unsafe where it can easily be wrong in the sense that little in the actual world needs to change for it to be wrong. Whether the requirement of safety can explain why judgment should not entered against the defendant in our two hypothetical cases would depend on whether it can easily happen that the accident-causing bus was red or that the accused is innocent.
See Pritchard and ; Pardo ; cf. Gardiner While theorizing of standards of proof in epistemic terms has gathered pace in recent years, it is criticised for relying on unrealistic hypotheticals that fail to attend to the actual operation of legal systems and for making impossible epistemological demands Allen There is another paradox in the mathematical interpretation of the standard of proof.
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. For the sake of simplicity, let A and B be mutually independent events. Suppose the evidence establishes A to a probability of 0. On the mathematical interpretation of the civil standard of proof, the plaintiff should succeed in his claim since the probability with respect to each of the elements exceeds 0. 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, it is only 0.
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. So, in our example, the plaintiff should lose since the overall probability is below 0.
But this suggested solution is unsatisfactory. 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 two commentators noted, the legal definition of theft contains more elements than that for murder. Criminal law is not the same in all countries. We may take the following as a convenient approximation of what the law is in some countries: murder is 1 an act that caused the death of a person 2 that was done with the intention of causing the death, and to constitute theft, there must be 1 an intention to take property, 2 dishonesty in taking the property, 3 removal of the property from the possession of another person, and 4 lack of consent by that person.
Since the offence of theft contains twice the number of elements as compared to murder, the individual elements for theft would have to be proved to a much higher level of probability in order for the probability of their conjunction to cross the overall threshold than the individual elements for the much more serious crime of murder Allen and Leiter —5.
This is intuitively unacceptable. Another proposal for resolving the conjunction paradox is move away from thinking of the standard of proof as a quantified threshold of absolute probability and to construe it, instead, as a probability ratio.
One criticism of this interpretation of the standard of 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 Allen and Stein There is a deeper problem with the probabilistic conception of the standard of proof.
There does not seem to be a satisfactory interpretation of probability that suits the forensic context. The only plausible candidate is the subjective meaning of probability according to which probability is construed as the strength of 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.
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. Fifty percent of the population has this blood type.
On the Bayesian approach, the posterior odds are calculated by multiplying the prior odds by the likelihood ratio which, as we saw in section 2. The subjectivist Bayesian theory of legal fact-finding has come under attack see generally Amaya 82—93; Pardo First, as we already saw in section 3. Secondly, the Bayesian theory is not sensitive to the weight of evidence which, roughly put, is the amount of evidence that is available.
This criticism and the concept of weight are further explored in section 3. Thirdly, while the Bayesian 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.
Tribe —; cf. Posner , suggesting starting the trial with prior odds of , criticized by Friedman The problem of fixing the prior probability is said to disappear if we base fact-finding simply on likelihood ratios: Sullivan, 45— Fourthly, 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 Callen 10— The impossibility of complying with the Bayesian model undermines its prescriptive value. Fifthly, according to Haack, the Bayesian theory has it the wrong way round. 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 that is, the comprehensiveness of the evidence—see further discussion in section 3.
Haack is 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. For her general theory of epistemology, see Haack ch. Sixthly, 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 Amaya —5.
The holistic nature of evidential reasoning as revealed by these studies has inspired alternative theories that are of a non-mathematical nature.
Nance , Friedman 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 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.
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 Pardo and Allen —; Pardo — The relative plausibility theory itself is perceived to have a number of shortcomings.
However, the theory is sketchy on the meaning of plausibility and the criteria for evaluating plausibility are left largely unanalyzed. 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 Amaya The third criticism is targeted at holistic theories of evidential reasoning in general and not specifically at the relative plausibility theory.
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 Twining ; Simon , ; Griffin 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.
As the relevant evidence at our disposal increases, the magnitude of the probability of the argument may either decrease or increase, according as the new knowledge strengthens the unfavourable or the favourable evidence; but something seems to have increased in either case,—we have a more substantial basis upon which to rest our conclusion.
I express this by saying that an accession of new evidence increases the weight of an argument. This idea of evidential weight has been applied by some legal scholars in assessing the sufficiency of evidence in satisfying legal standards of proof.
Weight is distinguishable from probability. The weight of evidence may be high and the mathematical probability low, as in the situation where the prosecution adduces a great deal of evidence tending to incriminate the accused but the defence has an unshakeable alibi Cohen Conversely, the state of evidence adduced in a case might establish a sufficient degree of probability—high enough to cross the supposed threshold of proof on the mathematical conception of the standard of proof—and yet lack adequate weight.
The defendant is sued by the show organiser for gate-crashing. The mathematical probability that the defendant was a gate-crasher is 0. But, according to the negation principle of mathematical probability, there is probability of 0. In these circumstances, it is intuitively unjust to find him liable Cohen A possible explanation for not finding him liable is that the evidence is too flimsy or of insufficient weight.
Proponents of the mathematical conception of the standard of proof have stood their ground even while acknowledging that weight has a role to play in the Bayesian analysis of probative value and the sufficiency of evidence. If a party does not produce relevant evidence that is in his possession, resulting in the court facing an evidential deficiency, it may draw an adverse inference against him when computing the posterior probability Kaye b: ; Friedman One criticism of this approach is that, in the absence of information about the missing evidence, the drawing of the adverse inference is open to the objection of arbitrariness Nance What a judge may do to optimize evidential weight is to impose a burden of producing evidence on a party and to make the party suffer an adverse finding of fact if he fails to produce the evidence.
This will serve as an incentive for the party to act in a manner that promotes the interest in evidential completeness Nance , , Cohen suggests that the standard of proof should be conceived entirely as a matter of evidential weight which, on his theory, is a matter of the number of tests or challenges to which a factual hypothesis is subjected to in court. He offers an account of legal fact-finding in terms of an account of inductive probability that was inspired by the work of writers such as Francis Bacon and J.
Inductive probability operates differently from the classical calculus of probability. It is based on inductive support for the common-sense generalisation that licences the drawing of the relevant inference. Inductive support for a generalisation is graded according to the number of tests that it has passed, or, putting this in another way, by the degree of its resistance to falsification by relevant variables. The inductive probability of an argument is equal to the reliability grade of the inductive support for the generalisation which covers the argument.
Proof beyond reasonable doubt represents the maximum level of inductive probability. This inference is licensed by the generalisation that normally if a stranger is found immediately after a burglary in possession of the stolen object, he intentionally removed it himself. The defence may try to defeat the inference by showing that the generalization does not apply in the particular case, for example, by presenting evidence to show that the accused had found the object on the street.
As a counter-move, it may produce evidence to establish that the object could not have been lying in the street as alleged. Cohen , ; cf.
Schum But usually this is not the case. In our example, we may not be entirely convinced that the accused found or did not find the object on the street, and our evaluation would involve the exercise of judgment that is no less subjective as the sort of judgments required when applying the standard probabilistic conception of proof Nance —6; Schum Strength of Evidence 3.
Hence, this statement of Bentham : [ 6 ] To say that testimony is not pertinent, is to say that it is foreign to the case, has no connection with it, and does not serve to prove the fact in question; in a word, it is to say, that it is not evidence. Wigmore a: Wigmore cites in support the judgment of Cushing C. Strength of Evidence The decision whether to allow a party to adduce a particular item of evidence is one that the judge has to make and arises in the course of a trial.
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. Allen and Pardo b: On the other side, it is acknowledged that there are limits to mathematical formalisation of evidential reasoning in law Franklin —9 and that context, argument and judgment do play a role in identifying the reference class Nance b.
As Cohen 4 explains: to accept that p is to have or adopt a policy of deeming, positing or postulating that p —i. Bibliography Abimbola, A. Aitken, C. Roberts, and G. Allen, R. Roberts eds. Amaya, A. Kaptein, H. Prakken, and B. Verheij eds. Anderson, T. Schum, and W. Ball, V. Bartels, R. Bentham, J. Dumont ed. Mill ed. Blackstone, W. Blome-Tillmann, M. Carter, E. Gordon, and B. Jarvis eds. Buchak, L. Callen, C.
Cheng, E. Cohen, L. Colyvan, M. Regan, and S. Cullison, A. Davis, D. Dawid, P. Twining, and M. Duff, A. Dworkin, R. Tapper ed. Eggleston, R. Enoch, D. Spectre, and T. Finkelstein, M. Franklin, J. Friedman, R. Gardiner, G. Coady and J. Chase eds. Lasonen-Aarnio and C. Littlejohn eds. Goldman, A. Goldring and W.
Edmundson eds. Griffin, L. Haack, S. Ho, H. Jackson, J. Patterson ed. James, G. Josephson, J. Kaplan, J. Kaplow, L. Kaye, D. Keynes, J. Laudan, L. Lawson, G. Leiter, B. Lempert, R. Lillquist, E. Littlejohn, C. Hoskins and J. Robson eds. MacCrimmon, M. McCormick, C.
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