Abstract
The Federal Jury Selection and Service Act was passed in 1968 guaranteeing that “all litigants in Federal courts entitled to trial by jury shall have the right to grand and petit juries selected at random from a fair cross-section of the community” (U.S., 1968, Section 1861).2 Current federal law attempts to insure this goal by specifying two key concepts in forming the jury venire. During panel selection procedures, there must be (1) “a random” selection of jurors and (2) selection from an area that includes special geographic districts in which a particular court convenes (U.S., 1968, Section 1861).3 At the state level, a similar standard applies.4
An earlier version of this chapter appeared in the Journal of Criminal Justice. We appreciate the comments of Jo-Elian Huebner-Dimitrius at California State University at Los Angeles, Ray Jessen at the University of California at Los Angeles, and anonymous reviewers of the journal for their helpful comments and suggestions in completing the section on the application to jury selection of cluster sampling with the probability proportionate to size.
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Notes
For more information, see Thiel v. Southern Pacific Co. (328 U.S. 217 1946); State v. Holstrom (43 Wis. 465, 168 N.W. 2d 574 (1969); and State v. Cage (337 So. 2d 1123 La. 1976). The Federal Act requires that selection procedures “ensure that each county, parish or similar political subdivision within the district or division is substantially proportionally represented in the master jury wheel for that judicial district, division, or combination of divisions” [U.S., 1968, Section 1863(b)(3)].
In the U.S., the historical footing for a panel of jurors drawn from the community is known. The first provision for a jury trial in a vicinage can be found in Article III, Section 2, of the Constitution: “The Trial of all Crimes, except in Cases of Impeachment, shall be by Jury; and such Trial shall be held in the State where the said Crimes shall have been committed; but when not committed within any State, the Trial shall be at such Place or Places as the Congress may by Law have directed.”
For example, California law specifically states that persons listed for service in the court “shall be fairly representative of the population in the area served by the court and shall be selected upon a random basis” (Section 9, 203). For more detailed discussions, see People v. White (43 Cal. 3d 740 1954); People v. King (49 Cal. Rptr. 562 1966); People v. Sirhan (7 Cal. 3d 258 1978); People v. Wheeler (148 Cal. Rptr. 890 1978); People v. Estrada (155 Cal. Rptr. 731 1979); People v. Graham (160 Cal. Rptr. 10 1979); and People v. Harris (36 Cal. 3d 36, 201 Cal. Rptr. 782 679 P.2d 433 1984). For the U.S. Supreme Court, see Alexander v. Louisiana (405 U.S. 625 1972); Peters v. Kiff (407 U.S. 493 1972); Taylor v. Louisiana (419 U.S. 522 1975); Duren v. Missouri (439 U.S. 357 1979); and City of Mobile, Ala. v. Bolden (466 U.S. 55 1980).
For further discussion, see Alker and Barnard (1978); Alker et al. (1976); Benokraitis and Griffin-Keene (1982); Butler (1980a, b, 1981); Chevigny (1975); De Cani (1974); Fukurai (1985); Fukurai and Butler (1991a, b); Fukurai et al. (1987, 1991a); Hans and Vidmar (1986); Heyns (1979); Kairys et al. (1977); Staples (1975); Wishman (1986); and “The case for black juries” (1970).
See People v. Harris (36 Cal. 3d 36 201 Cal. Rptr. 782 679 P.2d 433 1984). Empirical analyses of People v. Harris were performed at the University of California at Riverside. In People v. Harris, the motion of the respondent for leave to proceed in forma pauperis was granted; however, a writ of certiorari by the prosecution to the U.S. Supreme Court was denied on October 29, 1984, effectively requiring a retrial in California.
Two indices, delta and rho, are calculated in the following equations.
Table 7-1 is identical to Table 2-7. This chapter attempts to examine the feasibility of applying cluster sampling with probability proportionate to size (PPS) to jury selection procedures. This chapter also introduces the new duster-sampling strategy in order to rectify the discriminatory systematic selection of white-dominated census tracts and the arbitrary elimination of minority-dominated areas from the defined boundaries of the judicial district, that is, the gerrymandering of the judicial district.
The variables, XI through X5, represent the proportion of the cognizable groups in given census tracts. We created gender and racial variables by dividing the absolute number of respective groups by the total population. The percentage of college graduates was computed by the total number of college graduates divided by the population over 25 years of age. The percentage of poverty was judged by the number of poverty households divided by the total number of households in given census tracts.
Unique-factor correlations generally arise from a number of factors related to the nature of the data. The two most common factors are data collection procedures and the sharing of the same denominator in the indices for statistical analyses (Fukurai, 1991; Hayduk, 1987, p. 188). The survey technique used by the U.S. Census Bureau is generally a mixture of several data collection methods, including telephone and person-to-person interviews and mail surveys. It is possible that the mixture of these data collection methods had some-effect on the variables included in our analysis. A second factor in possible residual correlations is the use of the same denominator to construct the three variables X1, X2, and X3. In fact, two unique-factor correlations (X1-X2 and X1-X3) suggested by the partial derivatives from LISREL are attributed to the use of the same denominator in the measurement constructions. Similarly, three additional residual correlations are allowed by the evaluation of the partial derivatives. We are aware of the post hoc freeing of error covariances and the danger of such heuristic model fittings. Nevertheless, the freeing of the unique-factor correlations was performed only for exogenous indicators, and the path coefficients did not significantly change. We thus believe that the above procedures would not pose serious problems in the interpretation of the theoretical substance on the causal relationship between a set of exogenous factors and an endogenous factor in the covariance structural model.
Those 10 individual simulations (N = 1,250) were conducted to correspond to the actual 10 impanelments as previously analyzed and used in the Harris retrial. This procedure assumed that each juror had (1) an equal probability of being selected and (2) an identification number that corresponded to an assigned number of a particular census tract in the district.
The r represents the correlation coefficient between the Z score and a chi-square value. The coefficient is merely used as an index to show the relationship between the discrepancies in expected and observed Hispanic representation in the census tract and the direction of the Hispanic representation (over-and/or underrepresentation) in the jurisdiction. The coefficient, however, does not offer a test statistic.
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Fukurai, H., Butler, E.W., Krooth, R. (1993). The Optimal Design to Obtain a Racially Representative Jury. In: Race and the Jury. The Plenum Series in Crime and Justice. Springer, Boston, MA. https://doi.org/10.1007/978-1-4899-1127-8_7
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DOI: https://doi.org/10.1007/978-1-4899-1127-8_7
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