Criminal Psychology, Hans Gross [motivational books for students .txt] 📗

all these indices are in themselves established only as highly probable, they give under certain circumstances, when taken together, complete certainty, because the coincidence of so many high probabilities must be declared impossible if X were not the criminal.

In all other cases, as we have already pointed out, assumption and probability have only a heuristic value for us lawyers. With the assumption, we must of course count; many cases can not be begun without the assistance of assumption. Every only half-confused case, the process of which is unknown, requires first of all and as early as possible the application of some assumption to its material. As soon as the account is inconsistent the assumption must be abandoned and a fresh one and yet again a fresh one assumed, until finally one holds its own and may be established as probable. It then remains the center of operation, until it becomes of itself a proof or, as we have explained, until so many high probabilities in various directions have been gathered, that, taken in their order, they serve evidentially. A very high degree of probability is sufficient in making complaints; but sentencing requires “certainty,” and in most cases the struggle between the prosecution and the defense, and the doubt of the judge, turns upon the question of probability as against proof.[143]

That probability is in this way and in a number of relations, of great value to the criminalist can not appear doubtful. Mittermaier defines its significance briefly: “Probability naturally can never lead to sentence. It is, however, important as a guide for the conduct of the examiner, as authorizing him to take certain measures; it shows how to attach certain legal processes in various directions.”

Suppose that we review the history of the development of the theory of probability. The first to have attempted a sharp distinction between demonstrable and probable knowledge was Locke. Leibnitz was the first to recognize the importance of the theory of probability for inductive logic. He was succeeded by the mathematician Bernoulli and the revolutionist Condorcet. The theory in its modern form was studied by Laplace, Quetelet, Herschel, von Kirchmann, J. von Kries, Venn, Cournot, Fick, von Bortkiewicz, etc. The concept that is called probability varies with different authorities. Locke[144] divides all fundamentals into demonstrative and probable. According to this classification it is probable that “all men are mortal,” and that “the sun will rise to-morrow.” But to be consistent with ordinary speech the fundamentals must be classified as evidence, certainties, and probabilities. By certainties I understand such fundamentals as are supported by experience and leave no room for doubt or consideration—everything else, especially as it permits of further proof, is more or less probable.

Laplace[145] spoke move definitely—“Probability depends in part on our ignorance, in part on our knowledge....

“The theory of probability consists in the reduction of doubts of the same class of a definite number of equally possible cases in such a way that we are equally undetermined with regard to their existence, and it further consists in the determination of the number of those cases which are favorable to the result the probability of which is sought. The relation of this number to the number of all possible cases is the measure of the probability. It is therefore a fraction the numerator of which is derived from the number of cases favorable to the result and the denominator from the number of all possible cases.” Laplace, therefore, with J. S. Mill, takes probability to be a low degree of certainty, while Venn[146] gives it an objective support like truth. The last view has a great deal of plausibility inasmuch as there is considerable doubt whether an appearance is to be taken as certain or as only probable. If this question is explained, the assertor of certainty has assumed some objective foundation which is indubitable at least subjectively. Fick represents the establishment of probability as a fraction as follows: “The probability of an incompletely expressed hypothetical judgment is a real fraction proved as a part of the whole universe of conditions upon which the realization of the required result necessarily depends.

“According to this it is hardly proper to speak of the probability of any result. Every individual event is either absolutely necessary or impossible. The probability is a quality which can pertain only to a hypothetical judgment.”[147]

That it is improper to speak of the probability of a result admits of no doubt, nor will anybody assert that the circumstance of to-morrow’s rain is in itself probable or improbable—the form of expression is only a matter of usage. It is, however, necessary to distinguish between conditioned and unconditioned probability. If I to-day consider the conditions which are attached to the ensuing change of weather, if I study the temperature, the barometer, the cloud formation, the amount of sunlight, etc., as conditions which are related to to-morrow’s weather as its forerunners, then I must say that to-morrow’s rain is probable to such or such a degree. And the correctness of my statement depends upon whether I know the conditions under which rain must appear, more or less accurately and completely, and whether I relate those conditions properly. With regard to unconditioned probabilities which have nothing to do with the conditions of to-day’s weather as affecting to-morrow’s, but are simply observations statistically made concerning the number of rainy days, the case is quite different. The distinction between these two cases is of importance to the criminalist because the substitution of one for the other, or the confusion of one with the other, will cause him to confuse and falsely to interpret the probability before him. Suppose, e.g., that a murder has happened in Vienna, and suppose that I declare immediately after the crime and in full knowledge of the facts, that according to the facts, i.e., according to the conditions which lead to the discovery of the criminal, there is such and such a degree of probability for this discovery. Such a declaration means that I have calculated a conditioned probability. Suppose that on the other hand, I declare that of the murders occurring in Vienna in the course of ten years, so and so many are unexplained with regard to the personality of the criminal, so and so many were explained within such and such a time,—and consequently the probability of a discovery in the case before us is so and so great. In the latter case I have spoken of unconditioned probability. Unconditioned probability may be studied by itself and the event compared with it, but it must never be counted on, for the positive cases have already been reckoned with in the unconditioned percentage, and therefore should not be counted another time. Naturally, in practice, neither form of probability is frequently calculated in figures; only an approximate interpretation of both is made. Suppose that I hear of a certain crime and the fact that a footprint has been found. If without knowing further details, I cry out: “Oh! Footprints bring little to light!” I have thereby asserted that the statistical verdict in such cases shows an unfavorable percentage of unconditional probability with regard to positive results. But suppose that I have examined the footprint and have tested it with regard to the other circumstances, and then declared: “Under the conditions before us it is to be expected that the footprint will lead to results”—then I have declared, “According to the conditions the conditioned probability of a positive result is great.” Both assertions may be correct, but it would be false to unite them and to say, “The conditions for results are very favorable in the case before us, but generally hardly anything is gained by means of footprints, and hence the probability in this case is small.” This would be false because the few favorable results as against the many unfavorable ones have already been considered, and have already determined the percentage, so that they should not again be used.

Such mistakes are made particularly when determining the complicity of the accused. Suppose we say that the manner of the crime makes it highly probable that the criminal should be a skilful, frequently-punished thief, i.e., our probability is conditioned. Now we proceed to unconditioned probability by saying: “It is a well-known fact that frequently-punished thieves often steal again, and we have therefore two reasons for the assumption that X, of whom both circumstances are true, was the criminal.” But as a matter of fact we are dealing with only one identical probability which has merely been counted in two ways. Such inferences are not altogether dangerous because their incorrectness is open to view; but where they are more concealed great harm may be done in this way.

A further subdivision of probability is made by Kirchmann.[148] He distinguished:

(1) General probability, which depends upon the causes or consequences of some single uncertain result, and derives its character from them. An example of the dependence on causes is the collective weather prophecy, and of dependence on consequences is Aristotle’s dictum, that because we see the stars turn the earth must stand still. Two sciences especially depend upon such probabilities: history and law, more properly the practice and use of criminal law. Information imparted by men is used in both sciences; this information is made up of effects and hence the occurrence is inferred from as cause.

(2) Inductive probability. Single events which must be true, form the foundation, and the result passes to a valid universal. (Especially made use of in the natural sciences, e.g., in diseases caused by bacilli; in case X we find the appearance A and in diseases of like cause Y and Z, we also find the appearance A. It is therefore probable that all diseases caused by bacilli will manifest the symptom A.)

(3) Mathematical Probability. This infers that A is connected either with B or C or D, and asks the degree of probability. I. e.: A woman is brought to bed either with a boy or a girl: therefore the probability that a boy will be born is one-half.

Of these forms of probability the first two are of equal importance to us, the third rarely of value, because we lack arithmetical cases and because probability of that kind is only of transitory worth and has always to be so studied as to lead to an actual counting of cases. It is of this form of probability that Mill advises to know, before applying a calculation of probability, the necessary facts, i.e., the relative frequency with which the various events occur, and to understand clearly the causes of these events. If statistical tables show that five of every hundred men reach, on an average, seventy years, the inference is valid because it expresses the existent relation between the causes which prolong or shorten life.

A further comparatively self-evident division is made by Cournot, who separates subjective probability from the possible probability pertaining to the events as such. The latter is objectively defined by Kries[149] in the following example:

“The throw of a regular die will reveal, in the great majority of cases, the same relation, and that will lead the mind to suppose it objectively valid. It hence follows, that the relation is changed if the shape of the die is changed.” But how “this objectively valid relation,” i.e., substantiation of probability, is to be thought of, remains as unclear as the regular results of statistics do anyway. It is hence a question whether anything is gained when the form of calculation is known.

Kries says, “Mathematicians, in determining the laws of probability, have subordinated every series of similar cases which take one course or another as if the constancy of general conditions, the independence and chance equivalence of