Indiana Supreme Court on Circumstantial and Direct Evidence

During the past 100 years and more, many judges and courts have taken a turn at trying to explain the difference between direct and circumstantial evidence. The Supreme Court of Indiana recently decided to do so as well. See Hampton v. State, 961 N.E.2d 480 (Ind. 2012). The Indiana Supreme Court was moved to stumble into this thicket because Indiana case law requires (as the Indiana Supreme Court saw it) a trial judge to instruct the jury that if the evidence against the criminal defendant consists of some kind of circumstantial evidence, the jury must find, not only that the defendant is guilty beyond a reasonable doubt, but also that the evidence is "so conclusive and sure as to exclude every reasonable theory of innocence." Id. at 482. In the eyes of the Indiana Supreme Court, the need for such a jury instruction made it necessary for the Court to discuss the difference between direct and circumstantial evidence. It did so. After discussing the (supposed) difference, the Court concluded that the "reasonable theory of innocence" instruction is necessary when "where the conduct of the defendant constituting the commission of a charged offense is proven exclusively by circumstantial evidence." Id. (emphasis added). But the court's attempt to explain the distinction between direct and circumstantial evidence was bound to be as confusing and as murky as it was -- because the court got off on the wrong foot -- because there is in fact no difference between direct and circumstantial evidence.
The Indiana court's opinion not only added to the considerable body of judicial and academic murk about the supposed difference between direct and circumstantial evidence. The opinion also endorsed, in an unfortunately-retrograde way, that circumstantial evidence is weaker than direct evidence and that, for that reason, circumstantial evidence requires special handling -- such as by the giving of the "reasonable theory of innocence" instruction. In my view, consistency requires that the instruction, which probably does no discernible harm, should be given in every criminal trial where the issue is factual guilt or innocence.
Here, for what it is worth (which is not much), is an extract from the Indiana Supreme Court's opinion (but the extract does have a useful survey of authorities):
1. Instructing Juries to Use Caution when Evidence is Circumstantial

A. Need for a Special InstructionThe importance of a "reasonable theory of innocence" instruction is deeply imbedded in Indiana jurisprudence. {PT: string of Indiana citations omitted} "[T]his Court has never departed from the conviction that the ['reasonable theory of innocence'] standard is a proper one to be employed at the trial court and a defendant is entitled to an instruction to that effect." Spears, 272 Ind. at 638, 401 N.E.2d at 335.


We note that a number of more recent American appellate decisions appear to place less emphasis on the need for similar instructions. See Irene Merker Rosenberg & Yale L. Rosenberg, "Perhaps What Ye Say Is Based Only on Conjecture"—Circumstantial Evidence, Then and Now, 31 Hous. L. Rev. 1371, 1400-01 nn.121-22 (1995) (noting that at least twenty-nine states have eliminated a specific jury instruction on circumstantial evidence).2  This trend sprang after the United States Supreme Court's decision in Holland v. United States, 348 U.S. 121, 75 S. Ct. 127, 99 L. Ed. 150, 1954-2 C.B. 215 (1954), in which the Court rejected a claim of reversible error for the refusal "to instruct [the jury] that where the Government's evidence is circumstantial it must be such as to exclude every reasonable hypothesis other than that of guilt." Id. at 139, 75 S. Ct. at 137, 99 L. Ed. at 166. Without extensive explanation, the Court concluded that "the better rule is that where the jury is properly instructed on the standards for reasonable doubt, such an additional instruction on circumstantial evidence is confusing and incorrect." Id. at 139-40, 75 S. Ct. at 137, 99 L. Ed. at 166. We understand Holland to hold that including an additional "reasonable theory of innocence" instruction is not required but not that it is constitutionally erroneous.

[T]he Constitution neither prohibits trial courts from defining reasonable doubt nor requires them to do so as a matter of course. Cf. Hopt v. Utah, 120 U.S. 430, 440-41, 7 S. Ct. 614, 618-20, 30 L. Ed. 708 (1887). Indeed, so long as the court instructs the jury on the necessity that the defendant's guilt be proved beyond a reasonable doubt, see Jackson v. Virginia, 443 U.S. 307, 320, n.14, 99 S. Ct. 2781, 2789, n.14, 61 L. Ed. 2d 560 (1979), the Constitution does not require that any particular form of words be used in advising the jury of the government's burden of proof. Cf. Taylor v. Kentucky, 436 U.S. 478, 485-86, 98 S. Ct. 1930, 1934-35, 56 L. Ed. 2d 468 (1978). Rather, "taken as a whole, the instructions [must] correctly conve[y] the concept of reasonable doubt to the jury." Holland v. United States, 348 U.S. 121, 140, 75 S. Ct. 127, 137, 99 L. Ed. 150, 1954-2 C.B. 215 (1954).

Victor v. Nebraska, 511 U.S. 1, 5, 114 S. Ct. 1239, 1243, 127 L. Ed. 2d 583, 590 (1994) (alteration in original).


Subsequent to Holland, opinions from several states began to conclude that a "reasonable theory of innocence" instruction incorrectly suggests that circumstantial evidence is inherently less reliable.3 See, e.g., State v. Humpherys, 134 Idaho 657, 661-62, 8 P.3d 652 (Idaho 2000); People v. Bryant, 113 Ill. 2d 497, 499 N.E.2d 413, 420-21, 101 Ill. Dec. 825 (Ill. 1986); State v. Wilkins, 215 Kan. 145, 523 P.2d 728, 737 (Kan. 1974); State v. Lewisohn, 379 A.2d 1192, 1210 (Me. 1977); State v. Smith, 92 N.M. 533, 591 P.2d 664, 671-72 (N.M. 1979); State v. Jenks, 61 Ohio St. 3d 259, 574 N.E.2d 492, 502 (Ohio 1991), superseded by state constitutional amendment on other grounds as recognized in State v. Smith, 80 Ohio St. 3d 89, 1997 Ohio 355, 684 N.E.2d 668 (Ohio 1997); Easlick v. State, 2004 OK CR 21, 90 P.3d 556, 559 n.3 (Okla. 2004); State v. Roddy, 401 A.2d 23, 34-35 (R.I. 1979); State v. Gosby, 85 Wn.2d 758, 539 P.2d 680, 684-86 (Wash. 1975). Still other states reversed course by simply citing the Holland decision without any cogent analysis. See State v. Grippon, 327 S.C. 79, 489 S.E.2d 462, 464-67 (S.C. 1997) (Toal, J., concurring) (quoting Rosenberg & Rosenberg, supra, at 1402) ("[T]he widescale abandonment of the special circumstantial evidence charge has resulted  [486]  mostly from a 'bandwagon effect' following Holland, rather than from a reasoned rejection of the longstanding rule.").

In contrast, however, numerous jurisdictions uphold the requirement of a "reasonable theory of innocence" instruction. For example, New York's high court explained:

[T]he rule [requiring the instruction] draws attention to the fact that proof by circumstantial evidence may require careful reasoning by the trier of facts. By highlighting this aspect, the rule hopefully forecloses a danger legitimately associated with circumstantial evidence—that the trier of facts may leap logical gaps in the proof offered and draw unwarranted conclusions based on probabilities of low degree.

People v. Ford, 66 N.Y.2d 428, 488 N.E.2d 458, 465, 497 N.Y.S.2d 637 (N.Y. 1985) (citation omitted). Other jurisdictions continue to instruct that juries should consider whether circumstantial evidence excludes every reasonable hypothesis, explanation, or theory of innocence. See, e.g., People v. Bacon, 50 Cal. 4th 1082, 116 Cal. Rptr. 3d 723, 240 P.3d 204, 225-26 (Cal. 2010); Davis v. State, 285 Ga. 176, 674 S.E.2d 879, 880-84 (Ga. 2009); State v. Percy, 822 So. 2d 823, 828 (La. Ct. App. 2002); People v. DeWitt, 173 Mich. App. 261, 433 N.W.2d 325, 329 (Mich. Ct. App. 1988); McInnis v. State, 61 So. 3d 872, 875-76 (Miss. 2011); State v. Steele, 211 N.W.2d 855, 867 (N.D. 1973); State v. Teague, 680 S.W.2d 785, 790 (Tenn. 1984).

We believe that discarding the "reasonable theory of innocence" jury instruction is unwise. HN1 While a criminal conviction may properly rest entirely upon circumstantial evidence, there is a qualitative difference between direct and circumstantial evidence with respect to the degree of reliability and certainty they provide as proof of guilt. Such a supplemental instruction is a safeguard urging jurors to carefully examine the inferences they draw from the evidence presented, thereby helping to assure that the jury's reasoning is sound. Additionally, it serves to "reiterat[e] the magnitude of the ['proof beyond a reasonable doubt'] standard to juries when the evidence before them is purely circumstantial." Nichols, 591 N.E.2d at 136. In this regard, the "reasonable theory of innocence" instruction informs the jury that if a reasonable theory of innocence can be made of the circumstantial evidence, then there exists a reasonable doubt, and the defendant is entitled to the benefit of that doubt.

Such a "reasonable theory of innocence" instruction, when appropriate, is not satisfied by the instruction on reasonable doubt. The State argues that our statement in Nichols—that the "reasonable theory of innocence" instruction is a way of restating "proof beyond a reasonable doubt"—renders the instruction "duplicitous."4 Appellee's Br. at 12. To the contrary, providing the jury with an additional cautionary instruction in evaluating circumstantial evidence not only supports but further enhances the concept of requiring proof beyond a reasonable doubt. It admonishes the jury to tread lightly where the evidentiary gap between logical certainty and guilt is more tenuous. For these reasons, we find it altogether appropriate that juries receive, where appropriate, a "reasonable theory of innocence" instruction in addition to the standard reasonable doubt instruction.


B. Language of the Instruction
This special advisement has traditionally been accomplished in Indiana by an instruction like the one rejected by the trial court in the present case. Language within Indiana Pattern Jury Instruction 12.01 provides: "Where proof of guilt is by circumstantial evidence only, it must be so conclusive in character and point so surely and unerringly to the guilt of the accused as to exclude every reasonable theory of innocence." Ind. Pattern Jury Instruction—Criminal 12.01 (emphasis added). Effective juror comprehension and application, however, are compromised by impediments in the instruction's language—especially the uncertainties embedded in the phrases "proof of guilt" and "by circumstantial evidence only."

First, the instruction's language—that it applies where proof of "guilt" is "circumstantial only"—is potentially confusing. "Proof of guilt" could require that any evidence which supports an individual element of the charged offense be circumstantial, or it could require that all the evidence related to all elements of a charge be circumstantial. Compare Spears, 272 Ind. at 636-40, 401 N.E.2d at 334-35 (finding sufficient absence of direct evidence to warrant "reasonable theory of innocence" instruction despite direct evidence that the defendant and the victim were fighting earlier in the evening and that the victim was later found unconscious in the hallway, and that he died from skull fractures likely caused when his head hit the floor), with Davenport v. State, 749 N.E.2d 1144, 1149-50 (Ind. 2001) (affirming refusal of "reasonable theory of innocence" instruction where victim died of strangulation and had thirty-nine injuries and witness observed defendant beating on the victim several hours earlier). In most criminal prosecutions, there is some direct evidence that the charged crime was committed by someone. Thus, if the phrase "by circumstantial evidence only" is construed to not require jurors to consider whether there exist reasonable alternative theories of innocence whenever the occurrence of a criminal offense is shown in part by direct evidence, then the instruction would rarely, if ever, be used. On the other hand, the mens rea element for a criminal offense is almost inevitably, absent a defendant's confession or admission, a matter of circumstantial proof. Thus, requiring jurors to consider the possible existence of an alternate reasonable theory of innocence whenever proof of the mens rea element is circumstantial would lead to use of the instruction in most all criminal cases. See Spears, 272 Ind. at 639-40, 401 N.E.2d at 335 (requiring the "reasonable theory of innocence" instruction when circumstantial evidence is the exclusive proof of the actus reus5 but not when used to  [488]  prove the mens rea: "To hold otherwise would require a circumstantial evidence instruction in every case involving a crime containing the element of intent. Unnecessary confusion would result from such a course.").

From our review of jurisdictions employing an instruction similar to our "reasonable theory of innocence" instruction, we find no consistent approach to resolving these issues. Mississippi requires an instruction requiring the "exclusion of all reasonable hypotheses consistent with innocence" whenever there is any "direct evidence" such as "an admission or confession by the defendant to a significant element of the offense, or eyewitness testimony to the gravamen of the offense charged." McInnis, 61 So. 3d at 876 (emphasis omitted) (quoting Kirkwood v. State, 52 So. 3d 1184, 1187 (Miss. 2011)) (internal quotation marks omitted). In Michigan, juries are instructed that "[i]f the direct and circumstantial evidence, taken together, is open to two reasonable constructions, one indicating guilt and the other innocence, it is your duty to accept the construction indicating innocence." DeWitt, 433 N.W.2d at 329 (emphasis added). But Tennessee calls for the instruction only when "the evidence is entirely circumstantial."6 State v. Knight, 969 S.W.2d 939, 941-42 (Tenn. Crim. App. 1997) (emphasis added); see also Teague, 680 S.W.2d at 790.


Notwithstanding the strong support in Indiana case law for the concept of a "reasonable theory of innocence" instruction, in actual fact, the refusal of such instruction has rarely been found to be error, often based on the presence of evidence liberally deemed to be "direct" rather than "circumstantial." See, e.g., Davenport, 749 N.E.2d at 1149-50 (finding direct evidence where son observed his mother being beaten by the defendant, sought to intervene but was struck by defendant and went to bed, and the next day the mother was found murdered by strangulation, which was not witnessed by the son); Clemens v. State, 610 N.E.2d 236, 243-44 (Ind. 1993) (finding direct evidence from the defendant's admission that he was present when the victim sustained his mortal injuries and the pathologist testified that those injuries must have been inflicted intentionally); Chapman v. State, 556 N.E.2d 927, 931 (Ind. 1990) (finding direct evidence from testimony of bank teller who identified defendant as person standing outside bank before the robbery, but who could not see the facial features to identify the hooded robber who perpetrated the robbery). While this Court in Spears, which reversed a murder conviction, evaluated the necessity of giving a "reasonable theory of innocence" instruction by considering whether there was any direct evidence showing the actus reus of a charged crime, rather than just direct evidence of any element of the crime, 272 Ind. at 636-40, 401 N.E.2d at 334-35, this distinction has not yet been applied in any of our ensuing cases. Other than Spears, we find no case from this Court since 1928 that reversed a conviction due to a trial court's refusal to give a "reasonable theory of innocence" instruction. Landess v. State, 200 Ind. 440, 164 N.E. 267 (1928).7
These issues are not clarified by the present pattern instruction, which fails to clearly inform jurors whether the requirement of heightened scrutiny of circumstantial evidence applies only when there is a complete absence of direct evidence on every element of an offense, or when there is an absence of direct evidence with respect to a significant element or crucial component of guilt, or when there is an absence of direct evidence proving any single element of the charged statutory offense, or otherwise.

Second, the instruction unnecessarily calls upon the jury to determine whether evidence of guilt is "circumstantial." Such an evaluation is already the province of the trial judge in deciding whether such instruction is required in light of the nature of the evidence presented. Distinguishing between direct and circumstantial evidence as proof of a particular fact is a legal determination appropriate for judicial evaluation. It may require intricate legal analysis.

Direct evidence is "[e]vidence that is based on personal knowledge or observation and that, if true, proves a fact without inference or presumption." Black's Law Dictionary 636 (9th ed. 2009). Conversely, circumstantial evidence is "[e]vidence based on inference and not on personal knowledge or observation." Id. Indiana case law has expressed it thusly: "Direct evidence means evidence that directly proves a fact, without an inference, and which in itself, if true, conclusively establishes that fact. Circumstantial evidence means evidence that proves a fact from which an inference of the existence of another fact may be drawn." Gambill, 675 N.E.2d at 675. And to explain the meaning of "inference," the jury in Gambill was further instructed: "An inference is a deduction of fact that may logically and reasonably be drawn from another fact or group of facts." Id. But every evidentiary assertion at trial is "direct evidence" of something. That is, it is a fact offered as true and if accepted by the jury as such, conclusively establishes that fact.

In the grouping of circumstantial evidence, difficulty has arisen from not keeping in mind that most circumstantial evidentiary facts must ultimately in turn become themselves a proposition and be proved by "direct" evidence and also from confining the latter term to assertions of some main fact in issue. For example, the finding of a bloody knife upon the accused after a secret killing is a circumstance from which an important inference may be drawn; yet this fact of the finding must be proved by some person's assertion.

IA John Henry Wigmore, Evidence § 25, at 955 (Tillers rev. 1983) (footnote omitted). Thus, as another example, footprints  [490]  or fingerprints that place an accused at the scene of a crime may be direct evidence of the accused's presence at some point in time but only circumstantial proof that the accused committed the charged offense.8


C. Reformulating the Use and Language of the Instruction
To preserve our historic recognition that juries in criminal cases should be reminded to use particular caution when considering whether to find guilt based solely on crucial circumstantial evidence, we conclude that a special instruction is appropriate, but we reformulate the manner of use and language of the instruction. First, we find it inappropriate to include language burdening the jury with the task of deciding whether to apply the reasonable theory of innocence standard. Whether an instruction is supported by the evidence is a matter for the trial court to determine, and it need not be reevaluated by the jury. Second, because Indiana jurisprudence recognizes the importance of such an instruction in certain cases involving circumstantial evidence but our case law reveals a reluctance to find reversible error for failure to give the instruction if there is substantial direct evidence of guilt, we elect to apply the approach taken in Spears and direct that the "reasonable theory of innocence" instruction is appropriate only where the trial court finds that the evidence showing that the conduct of the defendant constituting the commission of a charged offense, the actus reus, is proven exclusively by circumstantial evidence. As discussed above, to deny the availability of a "reasonable theory of innocence" instruction whenever there is any direct evidence of the fact that a criminal offense has occurred, however, could render the instruction unlikely ever to be used, but requiring the instruction whenever there is no direct evidence of any single element would compel its use in almost all criminal  cases because mens rea is often shown only by circumstantial evidence.

We thus hold that, when the trial court determines that the defendant's conduct required for the commission of a charged offense, the actus reus, is established exclusively by circumstantial evidence, the jury should be instructed as follows: In determining whether the guilt of the accused is proven beyond a reasonable doubt, you should require that the proof be so conclusive and sure as to exclude every reasonable theory of innocence.
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The underlying flaw in the Indiana Supreme Court's attempted solution is that it did not see that the evidence in every criminal case (and, indeed, in every type of case) is "exclusively circumstantial" because in no instance are any of the facts at issue in judicial proceedings established by "direct evidence," i.e., without the intervention of inferences.

• It is true that testimonial evidence has characteristics that distinguish it from from non-testimonial evidence. But testimonial evidence, like non-testimonial evidence, requires the use of inferences if testimonial evidence is to ever do its job, which is to serve as proof (to some degree) of some fact.

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My 1983 Comments on Circumstantial Evidence and "Inference-on-Inference"

For the most part I stand by the comments I made in 1983 on circumstantial evidence and the supposed but largely-nonexistent prohibition against inference on inference:

1A Wigmore on Evidence Section 41 (P. Tillers rev. 1983):

The following well-reasoned opinion [Wigmore wrote] shows a correct way to avoid the fallacy of rejecting an inference upon an inference and yet to give effect to the underlying distrust of inferences that rest upon too many intervening inferences:

New York Life Ins. Co. v. McNeely, 5 Ariz. 181, 79 P.2d 948, 953 (1938) ....

[I wrote:] A number of courts have used an approach similar to that found in _McNeely_; while allowing inferences to be based on inferences, they have said, variously, that the underlying inference must be shown as a "fact" or that the underlying inference must be the most plausible or reasonable of the inferences available.[fn5] Arizona itself, however, seems to have abandoned any requirement that the underlying inference be shown beyond a reasonable doubt.[fn6]

Wigmore's praise of the approach taken in McNeely should not be taken too literally. The briefest examination of Wigmore's Science of Judicial Proof (3d ed. 1937) shows that Wigmore did not for a moment believe that each underlying inference must be shown beyond a reasonable doubt (much less to a certainty). Wigmore's entire analysis in Science of Judicial Proof and in Sections 24 through 36 of this Treatise rests on the premise that single inferences, though weak when taken individually, may be substantial and powerful when added together (see Section 9, Section 10, Section12, Section 26, and Section 39 supra; but cf. Section 28 supra). The elaborate "chart method" used by Wigmore in Science of Judicial Proof clearly shows Wigmore's understanding that the probative strength of an underlying inference is a factor that affects the strength of the final factum probandum but that no mechanical rule can be laid down concerning how strong any underlying inference must be. The question is not whether any given inference in a chain is too weak but is always whether, in view of all patterns of corroborating and contradicting evidence at all levels of all inferential chains, the final factum probandum has been shown to the degree of likelihood required by the applicable standard of persuasion, whatever that standard may be. To make the sufficiency of any case depend on the strength of any single inference commits again the fallacy of "legal relevancy," so recently roundly condemned (see Section 37 supra) by the proponents of the now-popular and now-dominant theory of "logical relevancy." ...

[fn3] ...

[I wrote:] The supposed rule [against an inference on an inference] is incisively discussed in Bishin & Stone, Law, Language, and Ethics 289-291 (1972). See also Morgan, Basic Problems of Evidence 188 (1961) (in accord with Treatise); Cohen, The Probable and the Provable 68-73 (1977) (short chapter entitled The Difficulty about Inference upon Inference; Wigmore's views discussed; Cohen believes that the law requires that the initial factum probandum in a chain of inferences be established beyond a reasonable doubt; in fact, however, most legal authority does not expressly assert any such requirement).

Today most students of the problem of inference recognize that any single vision about the world or conclusion of fact rests on a multitude of inferences, premises, and beliefs, on a large complex of assumptions, and on a body of implicit or explicit principles by which the human organism perceives, organizes, structures, and understands experience; thus it is generally conceded that it is meaningless to denounce multistaged or cascaded inferences. See generally Section 37 supra, and see also the reviser's comments, with citations, in Section 24 supra. A belief in the ability to reach conclusions on the basis of a single inference merely reflects a lack of imagination and insight. Furthermore, the implicit character of many inferential steps does not render them invulnerable to attack. We cannot be sure that implicit inferential steps are reliable merely because they are made unself-consciously.

While it is now regarded as practically indubitable that the drawing of inferences from inferences is the natural and inevitable course of things -- without which the drawing of any inference is a practical impossibility -- it is very difficult to describe the precise kinds of processes involved in the cascading of inferences.

The usual analysis of catenate inference assumes that the top of the inferential chain, the final factum probandum, is always weaker than the bottom of the chain. See Section 37 supra. This view implicitly assumes the existence of what has been called the "transitivity of doubt"; it is assumed that the measure of doubt at the lower levels of the inferential chain is transferred to the upper levels of that chain (since it is assumed that the superstructure can never be stronger than its foundation and, indeed, must always be weaker by some measure that is directly related to the strength of the foundational inference). (This view, of course, disregards independent corroborative chains of evidence that intersect inferences at the level of the superstructure rather than at the level of the foundation.)

The sort of imagery used above is very powerful. However, it is not entirely clear that the assumption of transitivity should always apply.

Whether the assumption should apply depends to some degree on our willingness to assume that we can consciously discern the foundations of our ultimate inference. If one supposes, as we do (see Section 37 supra), that the premises of our inferences are not always apparent to us and that their explicit formulation may lead to an unwarranted discounting of their force, it is of course apparent that it is not always appropriate to discount "subsidiary" facta probanda by some factor related to the degree of doubt we entertain with respect to the validity of the foundational inferences we have formulated. (In part, we mean to assert that it is questionable whether we are in fact capable of stating the foundations of our pyramided inferences.)

It is also possible that the imagery of pyramided inferences may draw a false picture of the fashion in which we shape inferences from inferences. The image of tiered inferences, each inference resting on another inference, seems to disregard the possibility that all inferences to some degree rest on holistic thinking of some sort, in the sense that no inferential chain is completely independent of any other inferential chain (just as no inference can be independent of any other inference with respect to the same factum probandum). This reciprocal relationship among chains of inferences may amount to more than just the usual notion of the convergence of corroborative chains of evidence toward a common factum probandum (whether intermediate or final); it is possible that a supposedly distinct inferential chain works backward, as it were, by making us rethink the character of the other inferential chain and the nature of the probability relations between the original evidence and the first inference or between intermediate inferences and successive inferences. (The picture painted by another inferential chain, in short, may make us redefine the very nature of a particular inferential chain.)

The theory of catenate inferences, if accepted as legitimate, poses other intricate problems within the terms of the theory itself. Even if we assume the transitivity of doubt, it is far from clear — indeed, it is almost certainly not true — that the right way to compute the degree of the uncertainty (viz., the probability) of a derivative inference is to multiply the prior probability of the derivative inference (viz., the assumed probability of the derivative inference, given the assumption that the foundational inference exists) by the probability of the foundational inference. (This sort of multiplication was apparently advocated by Morgan in his analysis of tiered inferences. See Section 37.4 supra.) In fact, it is quite possible that an intermediate foundational inference having a probability of less than .5 (but more than zero) will add nothing to the probability of the final factum probandum. See Section 14.1 infra. Conversely, the measure of uncertainty present when one link in an inferential chain has the high probability value of, for example, .95 may become greatly magnified under certain conditions, so that the decrease in the probability of the final probandum is far greater than that which would be obtained by the simple process of multiplying the probability values all along the chain of inferences. See generally, Schum, A Bayesian Account of Transitivity and Other Order-Related Effects in Chains of Inferential Reasoning, Rice University Research Report No. 79-04 (Dec. 30, 1979) (thus, for example, Schum argues that small reductions in the credibility of a witness have large negative effects on the probability of the event being testified to when the witness is testifying about the occurrence of a rare event). The formal analysis of the effects of tiered inference becomes substantially more complex when one considers the common problem of separate inferential chains that converge (to some measure) toward a common factum probandum. See generally Schum, A Problem in Cascaded Inference: Determining the Inferential Impact of Confirming and Conflicting Reports from Several Unreliable Sources, 10 Organizational Beh. & Hum. Performance 404 (1973). There are many reasons we are not always free to assume that there is an additive relationship between the probability statements for the same factum probandum established by independent inferential chains, and a variety of factors may affect how the probative worth of the two chains should be added together if there is in fact an additive relationship. For example, consider a situation in which it is not permissible to assume that if independent pieces of evidence separately make some final and common factum probandum more probable that, taken together, these separate and independent chains make the final factum probandum even more probable. The relationship of additivity may be destroyed by the logical relationships between elements of the two chains. Thus, for example, one inferential chain may have probative force only on the assumption that the accident in question occurred at one time and the other inferential chain has probative force only on the assumption that the accident occurred at a different time in a very different manner. If so, it clearly will not do to simply add these inferential chains together; instead, it seems, one is compelled to make a choice between them. Even if this peculiar relationship between elements of two inferential chains does not exist, the formal analysis of the effects of corroborating chains of inference involves a number of other complications, and these complications may have a powerful effect on the degree of the additivity of two separate chains. Thus, for example, it is of course evident that if we think there is some chance that the testimony of one witness to event A is affected in some measure by the testimony of another witness to event A and the question is how much the testimony of both witnesses should count on the question of the existence of event A, it will not do to simply add together (in some appropriate way; see this note infra) the probative force the testimony of each witness has when considered separately; one must take into account the extent to which the testimony of the one witness is conditioned by the fact of or the tenor of the testimony of the other witness.

Professor Morgan's theory of "catenate inference" (Wigmore's phrase) or "cascaded inference" (Schum's phrase) is by and large still the most common theory espoused by judges and by writers of treatises and text-books. Closer inspection of that theory is therefore warranted. A theory of catenate inference affects a wide variety of problems, including matters such as conditional relevancy (see Section 14.1 supra), the appropriate treatment of real evidence, and the methods to be employed for determining the probative force of evidence (a determination required, for example, to decide whether evidence is unduly prejudicial; see Section 10a supra).

A fair assessment of the strengths and weaknesses of Morgan's theory of catenate inference first requires that an important modification of that theory be made. That modification (to be described below) is consistent with the general tenor of Morgan's theory; without that modification, Morgan's theory is not even plausible.

Morgan and his followers have assumed that the probability of a final inference that stands at the end of a chain of inferences (a derivative inference) is exactly equal to the multiplicative product of the existence of the immediately preceding inference (the supporting inference) and of the probability of the existence of the derivative inference on the assumption that the existence of the supporting inference is certain. (It also follows, on his view, that any supporting inference that is itself derived from an earlier supporting inference has a probability value that is obtained by the same type of computation.) As plausible as this theory sounds, however, it is almost surely wrong if one takes the view that the probative force of any item of evidence amounts to a measurement of the extent to which that item of evidence increases or decreases the probability of some fact in issue. If one takes the latter view, the key question is not how often A occurs when B occurs but rather how much more often does B occur when A occurs that it does when A does not occur. It is this comparison that permits us to determine whether the occurrence of B increases the probability of the occurrence of A. If one takes this (Bayesian) view of the manner in which the probative force of a piece of evidence is measured, however, the manner in which the probative force of any piece of evidence (whether or not it belongs to an inferential chain) is significantly altered, for on this view it is a gross fallacy to assume that the probability of A, given B, is simply the ratio of As to Bs. Instead, the comparison of the frequency of Bs, given As, and the frequency of Bs, given that As do not exist, produces a "likelihood ratio" (see Section 37 supra) that measures the extent to which our prior estimate of the odds of the existence of A are increased or decreased by the evidence in question (here, B). (As it happens, this likelihood ratio is described by the formula P(B|A) over the denominator P(B|-A); thus, precisely phrased, the comparison to be made is between (1) our estimate of the frequency of the occurrence of B when A is thought to exist and (2) the frequency of the occurrence of B when A is not thought to exist. See Section 37.6 supra.) If one accepts this basic Bayesian view that the probative force of evidence is a measure of its incremental probative force on some fact in issue, some interesting and surprising results eventuate, all of which significantly diverge from Morgan's central assumption that the probability of A, given B, is simply a matter of computing how often A occurs when we know that B occurs. Most pertinent to the present point, it turns out, as Schum has shown, that uncertainties with regard to the existence of B have an effect on the likelihood ratio with regard to the odds of the existence of A (the fact in issue) in a way that is not at all described by multiplying the frequency of As, given Bs, times the frequency of Bs, given Cs (where C is the initial evidence in the inferential chain that leads to B).

Instead, it turns out that very small uncertainties with regard to the existence of B — what Schum calls "source uncertainties" — can have a large impact on the likelihood ratio, viz., can diminish to a large extent the (incremental) probative value of any evidence whose existence is not itself certain but whose existence is itself probable and is inferred to some degree of probability from evidence found earlier in this chain of inferences. As it happens, a small measure of uncertainty about the existence of a penultimate inference — in our terms, a measure of uncertainty about the existence of an inference because of its derivation from a prior inference — has this seemingly inordinate impact on the probative force of the penultimate fact or inference, B, when B, in the absence of any such uncertainty about its existence, would produce a very substantial likelihood ratio, viz., would have great probative force. In other words, very slight doubts about the existence of what would be extremely probative evidence can diminish its value to a tremendous degree. See Schum & Du Charme, Comments on the Relationship between the Impact and the Reliability of Evidence, 6 Organizational Beh. & Hum. Performance 111 (1971). Schum shows that various types of uncertainties in what he calls the "source" may have various effects on the probative force of evidence; and, as it happens, none of these effects is accurately described by Morgan's simple multiplicative method.

Whether or not one accepts the Bayesian modification of Morgan's analysis of inference upon inference, it is at least evident that Morgan's views about how probabilities along a chain of inferences are to be combined are problematic. However, even if one accepts the need for a Bayesian modification of Morgan's thesis (which seems to presuppose some sort of a frequentist theory of probability; see Section 37 supra), the heart of Morgan's theory remains intact since under either approach there is agreement about the need for some type of discounting of the probative force of evidence by the use of some formula that takes into account the uncertainties that are found to exist in the chain of inferences that ultimately leads to the evidence bearing on the fact in issue.

Nonetheless, Morgan's thesis, even when taken in its most general sense, has other difficulties. While it is hardly doubtful that any assessment of evidence and its probative force must take into account in some way whatever uncertainty happens to pertain to the assumptions, inferences, beliefs, and so on that seem to be involved in the assessment of the value of any given item of evidence, it is not equally clear that the image of a chain of inferences, with each inference depending in some way on the strength of a prior inference, is an image that accurately portrays the manner in which the inferential process works. Although it would be rash to say that no series of inferences ever takes the form of a chain, it may be that the chain metaphor is applicable far less often than is usually supposed, and it also may be that efforts to portray the inferential process in this way are almost invariably intrinsically bound to produce serious distortions in our understanding of the inferential process and thus perhaps may impair our ability to assess the probative force of evidence in a proper fashion. The basic reason we suspect that the metaphor of a chain is misleading is that it tends to neglect what we believe to be almost universal relations of interdependence that exist between any so-called independent inferential chain and various ... things apart from that chain that necessarily have a bearing on the probative force of the chain. We believe that these relations of interdependence are so pervasive that it is misleading to describe any series of inferences as an independent chain of inferences that may be considered in isolation.

Before we turn to a brief examination of our general thesis concerning the problematic character of the chain metaphor, we shall first attempt to substantiate our thesis by indirection, by showing that there may be relations of interdependence within a chain, not at first apparent, that may make the chain metaphor inappropriate. The illustration we offer is meant to suggest the general lesson that what appears to be a chain will often, on closer inspection, turn out to be something quite different. After discussion of this specific illustration, we will turn to more general considerations that suggest why the metaphor of a chain, and the methods of analysis and computation that that metaphor suggests, are ordinarily, if not always, misleading and dangerous.

To the extent that it is presented above, the Bayesian modification of Professor Morgan's analysis of an inferential chain does not challenge his central thesis that there is a continuous relationship (if not a one-to-one correspondence) between the strength of any evidence standing at the top of a chain and the strength of inferences falling below the apex, supporting it. Even if that relationship is not linear, it is continuous and the probative force of any evidence derived from prior inferences may be mathematically conceived as a function of the strength of those prior inferences. In some cases, however, we may discover, perhaps counterintuitively, that the probative force of a derivative inference is not continuously related to the probative force of its supporting inferences, even though the probative force of the ultimate derivative inference is related in some fashion to its supporting inferences and even though, in a real sense, the exact probative force of the final inference is genuinely dependent on the strength of preceding inferences in the chain. For the sake of convenience, let us call the penultimate inference in the chain FP-2. Let us say that the fact in issue, toward which the chain is eventually directed and of which FP-2 is evidence, is called A. Let us also say that the proposition or inference that gives rise to FP-2 is called FP-1. And let us say that the evidence giving rise to FP-1, the supporting inference, is called F. Using this terminology, we say that it may happen that as we increase our estimate of the probability of FP-1, the probability of FP-2 will not always continuously increase (or decrease) as FP-1 increases, even though the probability of FP-2 is a derivative of the probability value attached to FP-1.

If we adopt the Bayesian modification of Morgan's analysis of inference upon inference (as described above in this note), it is easy enough to visualize examples of the sort of inferential chain Morgan had in mind. Thus, for example, suppose that we believe that when A thinks it will rain he takes his umbrella to work 80 percent of the time and that he takes his umbrella to work 40 percent of the time when he believes that it more likely than not will not rain. If the fact is shown that A thought it will rain, the evidence of this fact — viz., the fact itself — clearly has probative value for the question of whether A took his umbrella to work. Morgan's claim, however, is that in many cases we cannot know whether the actor (for example) thought it would rain and that in many cases we are uncertain whether this is so. In these cases, then, we must discount the probative force of the evidence by taking into account that the evidence only shows that it is likely that the actor had such a belief and by taking into account that the evidence does not show for certain that the actor had such a belief. How much do we discount the evidence because of this sequence of inferences (evidence belief it will rain taking of umbrella) from the evidence? Morgan's answer, as modified here, is that there is a direct and continuous relationship between the probability that A took his umbrella and the ratio of the relative frequency with which a belief of the probability of rain is present when certain evidence is present and the frequency with which a belief of the probability of rain is present when such evidence is not present. Thus, for example, if the evidence shows that the actor told his wife, "It will rain" and we believe that such statements are made in 40 percent of the cases in which the actor does in fact believe it will rain and that the actor makes such statements in only 1 percent of the cases in which in fact he does not believe it will rain, the evidence of the statement clearly has probative value for the question of whether the actor took his umbrella with him. Morgan's thesis, as modified here, is that the likelihood of the taking of the umbrella is directly and continuously related to this ratio. For example, the probative force of the statement "It will rain" with respect to FP-2 becomes exactly half of what it was before if we revise our estimate of the ratio with which the actor makes such statements, so that we now assert that he makes such statements in only 20 percent (and not 40 percent) of the cases in which he in fact believes it will rain. In short, as we revise our generalizations in a way that tends toward the conclusion that the actor says "It will rain" with equal frequency when he believes it will rain and when he believes it will not rain, the evidence of the making of the statement "It will rain" loses probative force for the question of his belief and, thus, revision of generalizations in this direction has a direct and continuous impact on the likelihood that the actor took his umbrella with him.

This example of evidence of rain and the assessment of its impact on the question of the taking of an umbrella seems to offer persuasive support for Morgan's general thesis. In fact, however, the example only illustrates that in some cases a Morgan-like analysis may be right; it falls far short of showing that a Morgan-like analysis is always right.

Suppose that the matter in issue, the final matter, is whether X will take his gun to work. The final factum probandum, therefore, is "X will take his gun to work." Call this FP-2. We wish to know the probability of FP-2. What is the likelihood X will take his gun to work? The hypothetical we pose, however, is curious because, as we imagine the situation, our estimate of the likelihood that X will take the gun to work will be affected by our estimate of the ways in which X usually acts when we make another estimate (as well as the way he acts when we do not make that other estimate). In short, we have created a situation in which that person's behavior (we believe, to a certain probability) is altered by what we, the factfinder, estimate about something else, viz., the probability estimate we make of something else. In doing so, we have established a relation of dependence between one estimate (our estimate of the probability that X will take the gun to work) and another estimate (of the likelihood of something else, that "something else" to be described momentarily). By hypothesis, then, our estimate of the probability of FP-2 is "derivative" from the probability of FP-1. However, as we choose to construct our hypothetical, there is no direct or continuous relationship between the likelihood of FP-2 and the likelihood of FP-1. This we do simply by saying that the actor's behavior (most frequently) is altered when and only when the odds of FP-1 reach a certain value, say fifty-fifty, and that otherwise (we estimate, by some generalization) the actor (probably) does not alter his behavior, viz., he does not permit our estimate of FP-1 to alter (we think) the frequency with which he takes the gun to work under various conditions. Therefore (we conclude, because of what we believe his behavior is likely to be in response to our estimates) many variations in the likelihood of FP-1 have no effect on the likelihood of FP-2. To make this example concrete, suppose that we suppose that X (we believe), will not take his gun to work in 90 percent of the cases in which we inform him of our previously private estimate that he will take the gun to work. (X's aim you see, may be to avoid the possibility of being caught.) We assume, for the sake of simplicity of description (though, for present purposes, it makes no difference in principle), that we, the factfinder, feel bound (for ethical reasons, let us say) to disclose to X our original private estimate of whether he will or will not take the gun to work. This estimate (by the reviser's stipulation) does not concern (what we believe) are X's probable responses to our original estimate but relates solely to what we think he probably would do if we made no disclosure of our private estimate of his probable behavior. Now to complete our hypothetical and our demonstration, all we have to do is to suppose that X, to a certain likelihood, probably will not vary his behavior in response to our original estimates in any way unless and until our estimate of probability crosses the fifty-fifty threshold, viz., X will act as we describe above only when we make the statement that it is more probable than not that he will take his gun to work. In addition, assume the factfinder estimates that X will not further alter his behavior if the fact-finder states (for example) that it is very likely that X will take his gun to work.

In the above example we maintain that the probability of FP-2 is in a very real sense dependent on the probability we attach to FP-1 (a person's taking his gun to work when certain evidence is present and when the person is not informed of FP-1), and yet it is evident that the likelihood of FP-2 is not continuously related to changes in FP-1. Hence, we have given the lie to any Morgan-like thesis about the nature of the relationships between the probabilities of facta probanda in an inferential chain. It is of course true that one may avoid this result by using the semantic trick of saying that our example is not a "true" example of an inferential chain since — so the argument goes — the only evidence of any pertinence is evidence showing whether the factfinder said he probably would take the gun to work and by saying that in this situation any chain would arise only insofar as there is a measure of uncertainty as to the making of any such statement, in which event the FP-2 should be discounted by the usual Morgan-like rules described above. But, we maintain, to take such a course is nothing more than a semantic trick, for in fact a descriptive account of how any real factfinder would in the end assess the probability of FP-2 would have to say (under the constraints we have established on the factfinder's behavior) that the factfinder does think that the likelihood of FP-2 is affected by (though not determined in all instances by) the likelihood of FP-1 (because the fact-finder, by our stipulation, feels bound to express that estimate, in every case, as he believes it). Thus, in this factfinder's mind, in this situation, the likelihood of FP-2 really is dependent (in his mind) on his estimate of the likelihood of FP-1 (in his mind), and it is therefore appropriate to speak of an inferential "chain." And yet, of course, it is clear that not every increase or decrease in the likelihood of FP-1 is continuously or directly related to increases or decreases in the likelihood of FP-2.

This problem is peculiar, to be sure, but perhaps not as peculiar as it seems, since, in fact it may and often does happen that persons about whom predictions are made will alter their behavior in some way that is related to the kinds of predictions made; and in a society governed by various truth-constraints, it may be that in a certain percentage of cases a person's predictions about the behavior of others will reflect the true beliefs of the person making the predictions, which are based on the available evidence. (It may be noted that examples of the sort of perverse behavior shown by the actor in the example are not unique.

Consider the field of intelligence work, in which opposing sides attempt to deceive each other and in which each side attempts to determine the rules of deception the other side presumably follows. This sort of problem is the subject of "signal theory.") However, whether or not the problem is peculiar, it suffices to lend credence to our general thesis, which is that close inspection of an inferential chain may show that there are relations of interdependence among the links of the chain, so that it cannot be said that a final inference is continuously related (whether positively or negatively) to increases in the probability of a supporting inference. Thus we believe the example lends some credence to the even more general hypothesis that in many situations involving putative inferential chains there may be relations of interdependence which either make the nature of the chain far more complex than it may appear at first glance or which, at certain extremes — if only because of the complexity of calculation required to maintain the image of the chain — may render the chain metaphor almost entirely worthless. Worst of all, the complexity of the relations of interdependence are so great that the effort to portray a series of inferences as a chain will lead to serious distortions in understanding and evaluation. It may also be the case that the very complexity of the description required to maintain the chain metaphor and to make it tenable, either descriptively or prescriptively, suggests that, practically speaking, there is no good reason to hang on to the metaphysical or epistemological assumptions that lend force to the chain metaphor.

The example of the perversely behaving gunslinger is useful because it suggests, quite rightly, that Morgan-like analysis of inferential chains applies only if inferential chains can somehow be held separate from lateral relations of interdependence, as well as from (in our hypothetical) vertical relations of interdependence, that may exist along (so to spjeak) the length of the chain. The Morgan-like analysis holds only if we can prevent the links of a chain from interacting with one another. Similarly, that analysis holds only if separate inferential chains can be kept apart. If that cannot be done, the Morgan-like analysis fails, or at least becomes so attenuated and complex that there is no reason to suppose either that any factfinder could actually use Morgan-like reasoning in any conscious fashion (see Section 37 supra) or that any factfinder somehow uses such a complex process implicitly, without knowing that he is doing so (see again Section 37 supra).

Returning for a moment to the more technical aspects of Morgan's analysis, it is worth remarking that a Bayesian modification of Morgan's analysis inexorably leads to the conclusion that the existence of corroborating inferential chains with regard to a fact in issue entirely eliminates the propriety of supposing that every increase in the probability of FP-1 has anything like a direct impact on the probability of FP-2. In this situation, involving corroborative chains of evidence, odd-shaped curves and graphs may have to be constructed to depict the eventual impact of FP-1 on FP-2. See Schum, A Problem in Cascaded Inference: Determining the Inferential Impact of Confirming and Conflicting Reports from Several Unreliable Sources, 10 Organizational Beh. & Hum. Performance 404 (1973). The complexities of analysis grow apace if one considers in addition to the problem of corroboration, the problem, already discussed, of measuring the impact of "source uncertainties" on the probability of FP-2. The complexities of analysis further increase (as shown in Section 37.6 supra) when it is supposed that one piece of evidence bearing on a fact in issue to some degree duplicates information by another piece of evidence bearing on the same fact in issue. (In the parlance of probability theory, this is the problem of dependent conditional probability.) When this happens, the force of one piece of evidence must be discounted to some degree to account for the extent of the duplication involved. We can only imagine (faintly) the further difficulties of analysis and description that may arise if one also supposes that the evidence presented in one inferential chain simultaneously happens to affect the force of generalizations that are pertinent to the assessment of the force of an inference in one link of another inferential chain. Suppose, for example, in a negligence action the issue is whether the floor in a supermarket was wet. The first piece of evidence offered is that it was quite warm in the supermarket. The factfinder believes that this tends to show that the floor was wet because he believes that floors are generally more likely to be wet when the air is warm than when it is dry. The plaintiff, however, offers evidence that shows that ten other people fell at the spot in question in the supermarket within a ten day period; the theory on which such evidence is offered is that falls in such frequency are unlikely to occur in the absence of some negligence or malfeasance on the part of the supermarket. The proponent asks the factfinder to also infer that water was probably the cause of the accident on which the suit is based since he offers evidence that in those prior accidents there was water on the floor. As it happens, however, those prior falls took place on warm days. The factfinder therefore discounts his earlier hypothesis about the relationship between warm weather and wet floors, and thus the force of the earlier evidence is diminished. In short, the probative force of separate inferential chains may depend on logical relations and implications of the theories that support the separate inferential chains and on the way those implications relate to other generalizations and theories involved in the analysis of other inferential chains.

It is not useful to multiply examples of the complexities that are occasioned by efforts to employ a Morgan-like analysis of inferential chains. To do so might give the impression that we believe that something like a Bayesian perspective on inference and probability assessments is the correct one. We do not take such a view of either Bayesian analysis or of Morgan-like analysis, at least not insofar as either of those methods purports to constitute a description of the general character of all inferential processes. We have seen that the use of such methods of analysis leads to enormous complexities, which prevent any facile conclusions about the appropriate methods to be used for combining inferences and probability assessments from various types of evidence in various circumstances. The moral we draw from our story in this note is not that we as yet have an inadequate understanding of analytical techniques of a Bayesian sort; rather, we draw a different moral, a moral that explains why we have discussed Morgan and Bayesian analysis in one breath. Our moral is that any method of analysis that pretends to yield a prescriptive account of inferential processes will fail entirely if that analysis demands that all conditions of dependence among various items of evidence and between evidence and other things (such as beliefs) be exhaustively, systematically, and precisely described. There are simply too many potential relations of interdependence to allow for the possibility of any such comprehensive account. Thus, for example, as already argued in Sections 37.6 and 37.7 supra, it is highly doubtful that it is ever possible, in principle, to state fully or exactly all the generalizations and "background information" (including general and specific hypotheses about how the world works) that are pertinent to any particular inference. If we are right, the view that a probability assessment at any step in the inferential chain is a direct function of a stated generalization necessarily misstates (to some necessarily indeterminate degree) the force of the inference that is warranted at any particular stage of the inferential chain; and, of course, if we are right, it is patently wrong to quantify the level of uncertainty that is generated by the stated generalization alone and to combine it in some computational fashion with similarly infirm (and distorted) probability assessments found to hold (as a result of some stated generalization) at some later point in the inferential chain.

In response to what we say about Morgan-like analysis of evidence — a mode of analysis that relies heavily on the dissection of evidence into pieces in an effort to discern interrelationships — it might be said, by way of confession and avoidance, that there are, to be sure, limitations on the capacity of analysis, but it is still worthwhile to be as systematic and as precise as we can be. And there is no doubt, of course, that this is a powerful rejoinder. But whether it is an entirely adequate rejoinder seems doubtful to us, for if the limitations on our analytical capacities mentioned above are assumed, it seems to us that neither the Morgan-like nor the Bayesian analytical technique can offer a basis for asserting that the method by which it organizes data and evidence is superior to any other systematic method that similarly requires that we pay attention to detail. (One may examine evidence systematically by attentively reading, in order, all the testimony given at a trial.) Our ruminations on the complexities generated by Morgan-like and Bayesian analysis suggest that, in some cases, care should be taken to examine evidence in ways that keep in the forefront, rather than in the background, the question of the manner in which the various pieces of evidence relate to each other and the kinds of general visions or beliefs that shape and should shape our interpretations of a mass of evidence. (The danger, to revise James's dictum, is that we will overstate or overestimate the degree to which our minute analytical analyses support the inferences we reach.) The importance of looking at the parts and the generalizations that relate to each of those parts must not overshadow the importance of looking at the whole and at the kind of general notions that we may use to tie the parts together in a meaningful way. Various parts of a whole can be put together in quite different ways to tell quite different stories. Consider, for example, a case of libel in which the evidence largely centers on the actions of the defendant and the motives and purposes he sought to achieve by uttering the various things he is said to have uttered and the things he might have uttered. At question in this trial is why the defendant uttered what he did and the question of what he did utter and just how he uttered whatever he did utter. In this sort of trial, the various bits of evidence presented will in subtle ways serve to establish a certain kind of general image of the alleged malfeasor, and we will use this image to evaluate much of the evidence submitted and its force. As the evidence is submitted, piecemeal, we may find that we, the factfinders, are constantly revising our image of the defendant and, as we do so, are constantly returning to the evidence earlier presented in order to see, first, whether it fits the image we have and, second, to see whether we have properly interpreted just what that man "did do" (did he sneer or smile?). This examination, in turn, will make us review the general image we have of that man and will make us revise that image, so that it somehow better fits the image we now (tentatively) have of the type of man involved. In this kind of trial, the interpenetration of theory and fact is almost complete and the separateness of different inferential chains, as well as the composition of the links in the inferential chains, is as much a product of our theorizing as it is of our examination of what we (initially) take to be separate pieces of evidence. In this kind of process, it is most difficult to give overweening significance to separate pieces of fact, and there is no reason we should do so. In reality, it seems that the facts somehow manage to generate in us certain general images and theories and that these general images and theories are then used to review the facts, in order to reconstruct them and interpret them in some sensible fashion. We may suppose that this sort of interaction between fact and theory, in this sort of trial, continues until, at some indefinable point, the factfinder feels that he has reached the limits of his imagination and understanding. For our own part, we have no reason to suppose that this sort of process is not well designed to produce reasonable estimates about what probably really happened, and we are inclined to think that this process is a good one. Hence, for all the reasons discussed here and in Sections 37.6 and 37.7 supra, we think it is important to discard all analytical efforts that somehow serve to deflect people from this most natural, and possibly most rational, method of getting at the truth about those sometimes-elusive "facts." We wonder why it was ever thought that factual questions have "hard edges"; the imagery quite belies the reality.

The result of this rather extensive discussion is a relatively modest conclusion. Perhaps it is useful in some way to see inferences as belonging in chains and to think of them as chains and to analyze them in that fashion, but it we do use some sort of a "chain" analysis to think about some problems of evidence, we should of course recall that the reasoning we use depends, in great measure, on oversimplification and that when we see a chain before us we are presupposing an enormous number of matters and disregarding the possibility of a great many interrelationships with other matters, both evidentiary and conceptual. Accordingly, we should keep in mind that any analysis using the chain metaphor is highly provisional and tentative; perhaps the chain metaphor, at best, should constitute a kind of visual or mental aid, and little more. Furthermore, we think it equally important to remember that from time to time it is wise to sit back and take a "holistic" or impressionistic approach to the evidence in an attempt to see how the various pieces fit together given the kind of general theory or story that those various pieces, as we see them, seem to presuppose. Then, through a series of reciprocal interactions, we can do what we usually do: We try to somehow make the various pieces of evidence and the general stories we have devised fit together to make a plausible and consistent whole.

In connection with this discussion of the problem of catenate inference, we note that a prominent logician has taken the view that, at least in some contexts, it is rational — and perhaps desirable, — to require that foundational inferences (inferences supporting later inferences in the chain) be established as practically certain and that only when this is done is it legitimate to rest subsequent inferences upon the prior inference. Compare discussion in the text infra. While that author draws support for this view from what he views as conventional legal treatment of catenate inference and from a reading of this section in the third edition of the Treatise, his approach does not entirely depend on the law; he also offers independent grounds (which he describes as being founded in "Baconian" logic) for his point of view. See generally Cohen, The Probable and the Provable (1977) (especially § 22, § 23, and § 72).

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The dynamic evidence page

It's here: the law of evidence on Spindle Law. See also this post and this post.