Reconciling Race and Class Differences in Self

Reconciling Race and Class Differences in Self-Reported and Official Estimates of Delinquency Author(s): Delbert S. Elliott and Suzanne S. Ageton Source: American Sociological Review, Vol. 45, No. 1 (Feb., 1980), pp. 95-110 Published by: American Sociological Association Stable URL: http://www.jstor.org/stable/2095245 Accessed: 22-03-2017 18:54 UTC JSTOR is a not-for-profit service that helps scholars, researchers, and students discover, use, and build upon a wide range of content in a trusted digital archive. We use information technology and tools to increase productivity and facilitate new forms of scholarship. For more information about JSTOR, please contact [email protected].

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RECONCILING RACE AND CLASS DIFFERENCES IN

SELF-REPORTED AND OFFICIAL ESTIMATES OF DELINQUENCY* DELBERT S. ELLIOTT AND SUZANNE S. AGETON Behavioral Research Institute, Boulder

American Sociological Review 1980, Vol. 45 (February):95-1 10

This paper addresses the general question of whether or not the satisfactory resolution of the methodological criticisms of self-report research will result in greater consistency between self-reported and official data with respect to the race and class distributions of delinquent behavior. We review the specific methodological criticisms of self-report delinquency (SRD) research; discuss the use of a new SRD measure in a national youth study; compare the race/class findings of this study with previous SRD research and with official arrest data; and examine the epidemiological and theoretical implications of these findings. Both class and race differentials are found in this study. It appears likely that the differences between these findings and those in earlier SRD studies are a result of differences in the specific SRD measures used. Additionally, these findings suggest a logical connection between SRD and official measures, and they provide some insight into the mechanism whereby official data produce more extreme race and class (as well as age and sex) differences than do self-report measures. The results of this study also have implications for previous tests of theoretical propositions which used self-report delinquency data. In short, prior self-report measures may not have been sensitive enough to capture the theoretically important differences in delinquency involvement.

Self-report measures of delinquency provide a different picture of the incidence

Problems of conceptualization, definition, and measurement continue to plague

and distribution of delinquent behavior than do official arrest records. Both types of data indicate significant age and sex differentials, but the magnitude of these differences is much smaller with selfreported data than with official arrest data (Williams and Gold, 1972; Gold and Reimer, 1974; Elliott and Voss, 1974; Ilor in the interpretation and analysis of specific delinquency data. This problem is linois Institute for Juvenile Research, clearly illustrated in the current con1973; Bachman et al., 1970; 1971; 1978). At the center of the controversy, howtroversy over the validity of self-reported ever, is the fact that self-report studies (as compared with official) estimates of generally find no differences in delinquent the incidence and distribution of delinbehavior by class or race (Gold and quency in the general adolescent populaReimer, 1974; Elliott and Voss, 1974; tion. Put simply, there are those who Williams and Gold, 1972; Hirschi, 1969; argue that police and arrest records Bachman et al., 1970; 1971; 1978; Illinois provide more accurate and reliable estiInstitute for Juvenile Research, 1973), mates of the social correlates of delinwhile studies relying upon police and quent behavior than do self-report surcourt data report significant differences by veys; others hold the opposite view. both class and race (Wolfgang et al., 1972; Elliott and Voss, 1974; Williams and Gold, * Address all communications to: Delbert S. El1972; Gordon, 1976; West, 1973; Short liott, Director; Behavioral Research Institute; 2305 and Nye, 1957-1958). Canyon Boulevard; Boulder, Colorado 80302. To date, attempts to reconcile this apThis study was supported by the Center for Studies of Crime and Delinquency, NIMH parent discrepancy between official and (MH27552), and the National Institute for Juvenile self-reported findings have taken one of Justice and Delinquency Prevention, LEAA (78two approaches. Most recently, reresearchers interested in the epidemiology and etiology of delinquency. While most would acknowledge the conceptual distinction between delinquent behavior and official responses to delinquent behavior, these distinctions are not clearly maintained in the measurement of delinquency

JN-AX-0003). We gratefully acknowledge the assistance of Judy Beth Berg-Hansen in the preparation of the manuscript.

searchers have challenged the strength of the empirical evidence for the class differ95

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96 AMERICAN SOCIOLOGICAL REVIEW ential in official data. Tittle and Villemez (1977) and Tittle et al. (1978) reviewed earlier published research findings and concluded that the class differences in official data are not clearly established and that the widespread belief in an inverse relationship between class and crime is not based upon sound empirical research findings. Hindelang et al. (1978) have also concluded that police records of juvenile offenses are not strongly or even moderately related to socioeconomic status.1 On the other hand, the race differential in official data has not been seriously challenged, to our knowledge. The second and most frequent approach has been to challenge the methodological

adequacy of the self-report technique and the adequacy of self-report research. Specifically, critics of self-report research contend:

(1) There are problems inherent in the method itself which make it inaccurate and unreliable. These problems include deliberate falsification, inaccurate recall, and forward and backward telescoping. (2) There are problems with the construction of measures used in selfreport research and with the procedures for administering the measures. These problems concern the lack of representativity in items, item overlapping, imprecise response sets, and the lack of anonymity of respondents. (3) There are problems with generalizing from self-report studies, due to the almost exclusive reliance upon small, unrepresentative samples. This paper is concerned with this second approach to reconciling official and self-reported findings with respect to class and race. We will not deal with those problems inherent in the self-report method itself, except to note that available research seems to support both the validity and reliability of the method (Nye and Short, 1956; Erickson and Empey, 1963;

I Hindelang et al. (1978) have also recently studied the extent to which sex and race are differentially related to self-reported and official records of delinquency, and some of their conclusions with regard to the race discrepancy will be cited later.

Hirschi, 1969; Gold, 1966; Dentler and Monroe, 1961; Hardt and Bodine, 1965; Hardt and Hardt, 1977; Farrington, 1973; Elliott and Voss, 1974; Clark and Tifft, 1966). Instead, we will deal with the correctable problems, i.e., the construction of measures and their administration, as well as representativity and sample size. The general question we will address here is whether or not the satisfactory resolution of these methodological issues in the construction and administration of selfreport measures will result in greater consistency between self-reported and official data. More specifically, will the satisfactory resolution of these problems produce race and class differentials in self-reported estimates of delinquent behavior? The discussion that follows will focus on: (1) the methodological criticisms of previous self-report delinquency (SRD) research; (2) the use of a new SRD measure in a national youth study; (3) a comparison of the race/class findings of this study with previous SRD research and with official arrest data; and (4) the epidemiological and theoretical implications of these findings. PROBLEMS WITH SRD RESEARCH

Instrument Construction

Much of the controversy over self-

report measures involves problems with instrument construction. Primarily, criticism centers on three issues: (1) the question of the representativeness of items employed in SRD measures; (2) problems

of item overlap; and (3) limited or ambiguous response sets.

The major criticism concerns the unrepresentativity of the items selected (Hindelang et al., 1975; Nettler, 1974; Far-

rington, 1973). Trivial and nonserious offenses (e.g., cutting classes and disobeying parents) are often overrepresented, while serious violations of the criminal

code (e.g., burglary, robbery, and sexual assault) are frequently omitted. In addition, many SRD measures tend to overrepresent certain behavioral dimensions (e.g., theft) to the exclusion of other relevant delinquent acts. As a result of such selection processes, most existing SRD measures have a restricted focus and do

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RECONCILING DIFFERENCES IN ESTIMATES OF DELINQUENCY 97

not represent the full range of delinquent acts; this limits the appropriateness of these scales as general measures of delinquent behavior.

Another problem is the overlapping nature of items often included in SRD measures, which results in inaccurate estimates of frequency due to duplicate counts of certain events. For example, many SRD measures include a "shoplifting" item, a "theft under $5" item, and a "theft $5-50" item. A single theft event could logically be reported on two of these items. The presence of both a "cutting school" and a "cutting class" item represents another form of measurement redundancy since cutting school necessarily involves cutting classes. This problem is not easily overcome, since a given behavioral event in fact may involve more than a single offense. Nevertheless, item overlapping creates a potential source of error in estimating the volume of delinquent behavior from SRD measures. The type of response sets typically employed with SRD measures has been another source of criticism. One major concern has been the frequent use of normative response categories such as "often," "sometimes," and "occasionally." This type of response set is open to wide variations in interpretation by respondents, and precludes any precise count of the actual number of acts committed. Other response sets used to estimate the number of behaviors (e.g., "never," "once or twice," and "three times or more") have been challenged on the grounds that they are not precise categories for numerical estimation, and that numerical estimates based upon such categories may severely truncate the true distribution of responses. With the above set, for example, any number of behaviors in excess of two is collapsed into a single "high" category. While this procedure may allow for some discrimination between youth at the low end of the frequency distribution, it clearly precludes any discrimination at the high end. Thus, a youth involved in three shoplifting offenses during the specified period receives the same "score" as a youth involved in 50 or 100 shoplifting events during the period. This limited set of categorical re-

sponses appears particularly problematic when the reporting period involves a year or more and when such items as using marijuana; drinking beer, wine or liquor; and carrying a concealed weapon are included in the SRD measure. Administration Procedures

The manner in which the measures are administered is also a problematic area for self-report delinquency research. Here the issue concerns: (1) anonymous vs. identified respondents, and (2) question-

naire vs. interview formats. Many researchers have argued that

anonymity has to be guaranteed or youth will not admit certain offenses-probably the more serious, stigmatizing ones. Research on this question suggests that there is slightly more reporting of offenses under conditions of anonymity, but that anonymous/identified differences are slight and statistically insignificant (Corey, 1937; Christie, 1965; Kulik et al., 1968). These findings have led Dentler (as cited in Hardt and Bodine, 1965) to comment that the necessity for anonymity is overemphasized, and that it may in fact lead to reduced involvement by respondents and careless or facetious answers. On the matter of interview vs. questionnaire formats, the discussion again involves the issue of anonymity, and the belief that self-administered questionnaires are more likely to produce accurate responses than personal interviews. One recent self-report delinquency research study compared results from structured interviews and self-administered check lists, where anonymity was guaranteed under both conditions (Krohn et al., 1974). While seven of the eight offenses were admitted more often under check-list

conditions than under interview conditions, none of the differences was significant at the .05 level. Even when education, sex, class, and IQ were controlled, no significant differences were obtained. Some researchers, most notably Gold (1966), have argued that the interview format has significant advantages for delinquency research in that it permits clarification of specific behaviors and, consequently, the ability to more cor-

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98 AMERICAN SOCIOLOGICAL REVIEW rectly classify illegal acts. In general, however, there is still controversy over the effects of specific administration procedures when the research is directed toward illegal or socially disapproved behaviors. Sampling Design and Generality Another problematic area for self-report delinquency research is that of the generality of findings. Here the question focuses primarily on the adequacy of the sampling designs for: (1) inferences to the adolescent population, and (2) comparisons with official data. In most cases, SRD measures have

been administered to small, select samples of youth, such as high school students in a particular local community or adolescents processed by a local juvenile court. The samples are rarely probability samples, and generalizations (about the adolescent populations sampled) cannot be made with any known degree of accuracy. Only two published studies involve national probability samples.2 A further concern is that few cohort studies using normal populations have incorporated a self-report measure in their instruments. This means that the age and sex gradients of SRD measures are not known, a critical fact if this measurement approach is to become more refined and useful. Furthermore, since the studies using self-report measures have almost always been cross-sectional ones, little is known about the dynamics of selfreported behavior over time. Finally, Empey (1978) notes that national self-report studies have not been conducted on an annual basis and, as a result, it is not possible to discern trends

across time or to make direct comparisons with other standard delinquency data such as the Uniform Crime Reports (UCR) or the National Crime Panel (NCP).

2 These are Gold's 1967 and 1972 National Surveys of Youth and the Youth in Transition Study (Bachman et al., 1970; 1971; 1978). Both studies are limited by a restricted set of SRD items and truncated response sets. The Youth in Transition Study also has problems associated with overlapping reporting periods for its reported SRD measures.

THE NATIONAL YOUTH SURVEY

We will now report on a national youth

study in which we have attempted to deal with the previously noted methodological

criticisms of self-report delinquency research. Our aim will be to see if these improvements in the quality of self-report research have any impact on self-report findings relative to findings from official data. The National Youth Survey involves a five-year panel design with a national probability sample of 1,726 adolescents aged 11-17 in 1976.3 The total youth sam-

ple was selected and initially interviewed between January and March, 1977, concerning their involvement in delinquent behavior during the calendar year 1976. The second survey was completed between January and March, 1978, to obtain delinquency estimates for the calendar year 1977. The third, fourth, and fifth surveys will also be conducted between each January and March of the years 1979, 1980, and 1981.

The data reported herein are taken from the first survey, completed in 1977. The estimates presented are thus for delinquent behavior during the calendar year 1976.

Construction of New SRD Measure In constructing the SRD measure for this study, we attempted to obtain a representative set of offenses. Given our interest in comparing SRD and UCR estimates, we began by listing offenses included in the UCR. Any specific act (with the exception of traffic violations) involving more than 1% of the reported juvenile arrests for 1972-1974 is included in the SRD measure.

In addition to the list of specific offenses, the UCR contains a general category, "all other offenses," which often

I The National Youth Survey is funded by the Center for Studies of Crime and Delinquency, NIMH (MH27552), and the National Institute for Juvenile Justice and Delinquency Prevention, LEAA (78JN-AX-0003). Current funding covers the first three of the five projected annual surveys. The first survey was funded solely by NIMH, the second and third by NIMH and LEAA jointly.

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RECONCILING DIFFERENCES IN ESTIMATES OF DELINQUENCY 99

accounts for a high proportion of the total juvenile arrests. To cover the types of acts likely to fall within this general category, and to increase the comprehensiveness of the measure, two general selection criteria were used to choose additional items. First, items which were theoretically relevant to a delinquent lifestyle or subculture

as discussed in the literature were selected for inclusion in this measure (Cohen, 1955; Cloward and Ohlin, 1960; Miller, 1958; 1966; Yablonsky, 1962; Short and

Strodtbeck, 1965). Thus, additional items-such as gang fighting, sexual

intercourse, and carrying a hidden weapon-are included. Second, a systematic review of existing SRD measures was undertaken to locate items that tap-

ped specific dimensions of delinquent behavior not previously included. We believe the resulting set of 47 items to be both more comprehensive and more representative of the conceptual universe of delinquent acts then found in prior SRD measures used in major, largescale studies. The item set includes all but one of the UCR Part I offenses (homicide is excluded); 60% of Part II offenses; and a wide range of "other" offenses-such as delinquent lifestyle items, misdemeanors, and some status offenses. The vast majority of items involve a violation of criminal statutes. (See Appendix A.) Two separate response sets are being used. Respondents initially are asked to indicate how many times during the past year they committed each act. If an individual's response to this open-ended question involves a frequency of 10 or more, interviewers then ask the youth to select one of the following categorical responses: (1) once a month, (2) once every 2-3 weeks, (3) once a week, (4) 2-3 times a week, (5) once a day, or (6) 2-3 times a day.4 A comparison of the two response sets indicates high agreement between frequency estimates given in -direct response to the open-ended question and

frequency estimates based upon the implied frequency associated with the midpoint of the category selected.5 A specific attempt was also made to eliminate as much overlap in items as possible. None of the items contains a necessary overlap as in "cutting school" and "cutting class." Although some possible overlap remains, we do not feel it constitutes a serious problem with this SRD measure.

The SRD measure asks respondents to indicate how many times, "from Christmas a year ago to the Christmas just past," they committed each offense. The recall period is thus a year, anchored by a specific reference point relevant to most youth. The use of a one-year period which coincides almost precisely with the calendar year allows for direct comparison with UCR data, NCP victimization data, and some prior SRD data. It also avoids the need to adjust for seasonal variations, which would be necessary if a shorter time period were involved. Administration Procedures

For the present study, the research design (a longitudinal panel design) precludes a guarantee of anonymity. Therefore, our major concern is to guarantee respondents that their answers will be confidential. This assurance is given verbally as well as being contained in the written consent form signed by all youth and their parents. In addition, a Certificate of Confidentiality from the Department of Health, Education, and Welfare guarantees all respondents that the data and the interviewers will be protected from legal subpoena.

The interview format was selected over the self-administered questionnaire format for several reasons. First, we share Gold's belief that the interview situation (if 5The only exception involves the last two (high frequency) categories. At this end of the frequency

continuum, estimates based upon the midpoint of the 4 The categorical response set has led to the idencategory are substantially higher than the frequency tification of some highly episodic events, e.g., 20 response given directly. The open-ended frequency shoplifting offenses, all occurring within a twomonth period during the summer (an initial responsemeasure thus appears to provide a more conservative estimate of number of delinquent acts, and the of 20; a categorical response 2-3 times a week, and estimates reported here are based upon this rean interviewer probe revealing that the offenses all

occurred during the summer).

sponse.

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100 AMERICAN SOCIOLOGICAL REVIEW properly structured to protect confidentiality) can insure more accurate, reliable data. Second, the necessity of securing informed consents from all subjects and the complexity of the present research require, in our judgment, a personal contact

United States as established by the U.S.

with the respondents. Once this contact is made, it seems logical to use the interviewer to facilitate the data collection process and to improve the quality of the data obtained. Finally, some of our previous research suggests that the differences in responding to SRD items in a questionnaire as opposed to an interview format are not significant (Elliott et al., 1976).

dresses many of the central criticisms of prior SRD measures.7 It is more repre-

The Sample

The 1977 National Youth Survey employed a probability sample of households in the continental United States based upon a multistage, cluster sampling de-

sign. The sample contained 2,375 eligible youth aged 11-17 in 1976. Of these, 1,726 (73%) agreed to participate in the study and completed interviews in the 1977 survey.6 A comparison of the age, sex, and race of eligible youth not interviewed with participating youth indicates that the loss rate from any particular age, sex, or racial group appears to be proportional to that group's representation in the population. Further, with respect to these characteristics, participating youth appear to be representative of the total 11 through 17-year-old youth population in the

6 At each stage, the probabilities of selection were established to provide a self-weighting sample. Seventy-six primary sampling units were selected, with probability of selection being proportional to

size. This sampling procedure resulted in the listing of 67,266 households, of which approximately 8,000 were selected for inclusion in the sample. All 11through 17-year-old youth living in the selected

Census Bureau (Huizinga, 1978). Summary of New Measure In sum, the current SRD measure ad-

sentative of the full range of delinquent acts than were prior SRD measures and involves fewer overlapping items; it also employs a response set which provides better discrimination at the high end of the frequency continuum and is more suited to estimating the actual number of behaviors committed. The choice of a

one-year time frame with a panel design involving a one-year time lag is based upon both conceptual and practical concerns. Compared with the other SRD measures, the measure involves a moderate recall period, captures seasonal variations, and permits a direct comparison with other self-report and official measures which are reported annually. And, finally, the study involves a national prob-

ability sample of youth aged 11-17. ANALYSIS OF DATA

Subscales

An earlier paper (Ageton and Elliott, 1978) presented design effects and estimates of the frequency of each specific item on the SRD measure with .95 confidence intervals for the total sample and by age, sex, race, and class. The analysis in this paper focuses upon the total SRD measure and a set of specific subscales. The frequency estimates are based upon the open-ended response set, which provides slightly more conservative frequency estimates than does the categorical response set.

households were eligible respondents for the study.

The selected households generated a total of 2,375 eligible youth. Of these, 649 (27%) did not participate in the study due to (1) parental refusal, (2) youth

7While we are concerned with the issues of valid-

ity and reliability of the self-report method, we will

refusal, or (3) the youth being considered inappropri-

not deal with these issues here beyond reporting

ate for inclusion in the study (e.g., severely mentally retarded). In general, based upon a comparison with

that: (1) we are obtaining data on official police contacts for each respondent and intend to compare

1976 U.S. Census Bureau estimates, the resulting

self-reports of delinquent behavior with official rec-

sample of participating youth does appear represen-

ords of police contact and arrest; and (2) the reliability (internal consistency) of the new SRD measure is quite high (Alpha = .91) for the 1977 survey. We are

tative of American youth with respect to age, sex, and race (U.S. Bureau of the Census, 1977). For a detailed description of the sample, see Huizinga, 1978, and Ageton and Elliott, 1978.

planning further validity tests with these data, but have nothing to report, yet.

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RECONCILING DIFFERENCES IN ESTIMATES OF DELINQUENCY 101 The subscales are based upon Glaser's (1967) offense typology. This particular classification scheme was selected because it offers a logical categorization of offense types while permitting a clear distinction between serious and nonserious crimes.

concealed weapon, hitchhiking, disorderly conduct, drunkenness, panhandling, making obscene phone calls, and marijuana use); (5) status crimes (runaway, sexual intercourse, alcohol use, and truancy);

Glaser' s typology encompasses four major types of crime: (1) predatory crimes, (2) illegal service crimes, (3) public disorder crimes, and (4) crimes of negligence. With the exception of category four, all Glaser's types were used.8 Furthermore, Glaser acknowledges an additional category called status crimes to encompass those behaviors which at special times and/or for particular classes of people have been illegal. The status crimes category in this national youth study includes all behaviors in the SRD measure which are illegal only when the individual involved is a minor. In addition, a separate category entitled hard drug use was created to distinguish this type of drug involvement from that of alcohol and/or marijuana use, which are subsumed within the status crimes category and public disorder crimes category,

(6) hard drug use (amphetamines, barbiturates, hallucinogens, heroin, and cocaine). Table 1 presents the mean frequency of self-reported delinquency by race9 and class10 for the total SRD measure and for each of the subscales. The statistical tests involve a one-way analysis of variance on these means.II

respectively.

Finally, within the predatory crimes category, a distinction was made between crimes against persons and crimes against property. This differentiation separates violent crimes against people from other serious offenses which do not involve confrontation with another person. Thus, the final offense typology is composed of the following six subscales: (1) predatory crimes against persons (sexual assault, aggravated assault, simple assault, and robbery); (2) predatory crimes against property (vandalism, burglary, auto theft, larceny, stolen goods, fraud, and joyriding); (3) illegal service crimes (prostitution, selling drugs, and buying/providing liquor for minors); (4) public disorder crimes (carrying a

9 Because of the small number of MexicanAmerican respondents (N = 72) and some obvious clustering effects for this ethnic group, the accuracy of the estimates of variances is questionable, and we have not included this group in the analysis. The same situation holds for the residual "other" cate-

gory (N = 32). Comparisons are, thus, limited to whites (Anglos) and blacks. 10 The social class measure employed in this analysis is the Hollingshead two-factor index (Hollingshead and Redlich, 1958) as applied to the principal wage earner in each youth's family. Hollingshead

Classes I and II-involving primarily professional managerial occupations and college level educations-are collapsed to make the "middle" class category. Class III-primarily owners of small businesses, clerical workers, and persons in sales occupations and skilled manual occupations, with high school or some college work completedconstitutes the "working" class category. Classes IV and V-primarily semiskilled persons

and those in unskilled manual occupations with high school or lower levels of education-make up the "lower" class category. 11 It should also be noted that the statistical tests are based upon a simple random sample design. The effect of our departure from this design is probably in the direction of inflating the F values. However, the

design effects are small, suggesting that the effect of this departure is not a serious one. For example, the average design effects on items in the total SRD measure are as follows: Males = 1.13; Females = 1.12; 11-12-year-olds 1.14; 13-15-year-olds 1.08; 16-17-year-olds 1.05; Middle Class = 1.05;

Working Class = 1.22; Lower Class = 1.09; Whites = 1. 14 and Blacks = 1. 15. Further, unless otherwise

specified, statistical significance refers to probabilities - .05. Because of our sample sizes, the 8 Category Four, crimes of negligence, was excluded because it contains predominantly automobile infractions which were not included in' the SRD measure.

statistical tests employed are rather powerful. An examination of Table 1 indicates very large variances and, even when significant differences in means are found, it is clear that the distributions being compared overlap substantially.

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102 AMERICAN SOCIOLOGICAL REVIEW Race and Class Differentials

Unlike most previous self-report studies, we find significant race differences for total SRD and for predatory crimes against property. Blacks report significantly higher frequencies than do whites on each of these measures. In both

I- m z Iz

cases, the differences in means are substantial. With respect to total offenses, blacks report three offenses for every two reported by whites. For crimes against property, blacks report more than two offenses for every offense reported by whites. While there is a substantial difference in mean scores on the crimes against persons scale, it is not statistically significant. The difference in the total SRD score appears to be primarily the result of the very high level of property crimes reported by blacks.

We also observe a class differential for total SRD and for predatory crimes against persons. For total SRD scores, the difference is between lower socioeconomic status youth and others; i.e., there does not appear to be any difference between working- and middle-class group

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The differences are greater, and the trend is more linear, for the crimes against persons scale means than for total SRD. 00r1r~ ~ Lower-class youth report nearly four Cr 00 0 times as many offenses as do middle-class - Eo : 'Zyouth and one-and-one-half times as many as working-class youth. There is also a substantial class difference in the mean number of crimes against persons, but this 0 ~ ~~~ > Cl o difference is not statistically significant. There are clearly no substantial dif0' X mo )O r' : ferences in means for any of the remaining subscales. 0 e] b0 A two-way analysis of variance (race x class) was also completed with the total SRD measure and each of the subscales. In '0~~ X every case, the direct effects observed in Cr1 3 -N or:3 the one-way analysis of variance were ,~~rl 0 replicated and no significant interaction effects were observed. '0~~~~~~~~~~~~~~~~~~~~~Z

COMPARISONS WITH PRIOR STUDIES

Our basic concern in this analysis, will now be to ascertain: (1) the comparability

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RECONCILING DIFFERENCES IN ESTIMATES OF DELINQUENCY 103 of the general findings reported here with other SRD findings, and (2) the extent to which these findings might offer some insight into the discrepancy between selfreport and official measures of delinquency.

While we have not reported findings from this study relative to the age and sex distribution of delinquent behavior, they are generally consistent with those from other large-scale self-report studies (Hirschi, 1969; Williams and Gold, 1972; Illinois Institute for Juvenile Research, 1973; Gold and Reimer, 1974; Elliott and Voss, 1974). However, the findings relative to the distribution by race and class are not consistent with these earlier studies, none of which report significant differences in the mean frequencies of self-reported offenses by race or class.12 In this study, the black/white differential in total offenses is nearly 2:1; and for predatory crimes, over 2:1. Class differences in total offenses are significant and, while the differences are not large, they are in the traditionally expected direction, with lower-class youth reporting higher frequencies. The trend in the

previously referenced self-report studies is generally in the opposite direction. In this study, class differences are clearer on the predatory crimes against persons scale than for total SRD scores; the trend is more linear, in the expected direction, and of greater magnitude (lower:middle = 3: 1). In an effort to determine if this basic difference in findings is due to the differences in the SRD measures employed, we undertook several additional analyses. We "re-scored" the frequency estimates in two ways to approximate the frequency ranges used in the earlier studies. Since our focus is upon those scales where sig-

nificant class and race differences are observed, our discussion will be limited to the total self-report measure and the two predatory subscales.

First, a comparison of the proportions of youth reporting one or more offenses on each of these scales reveals no statistically significant class or racial differences. Second, all frequencies of three and above on each item in the SRD measure were re-scored as a 3 to approximate the frequency ranges used in the Richmond Youth Study (Hirschi, 1969), the Delinquency and Dropout Study (Elliott and Voss, 1974), and the 1967 and 1972 National Surveys of Youth (Williams and Gold, 1972; and Gold and Reimer, 1974). Frequency scores on items were then summed across items to generate new scale frequencies and means. With one exception, an analysis of race and class differences on these frequency scores reveals no significant differences. The one

exception involves a small (but significant) class difference on the predatory crimes against persons scale.13 The class differential in this case is in the same direction but substantially smaller than that observed with the original scoring. These two analyses indicate that the extended frequency range used in this study does, in fact, contribute to the difference in findings relative to race and class. Had we used the proportion of youth committing one or more offenses, or a 0-3 range similar to that used in the 1967 and 1972 National Surveys of Youth, our conclusions relative to class and race differences would have been similar to those reported for the earlier self-report studies. High-Frequency Offenders

Since the above analyses indicate that differences were not occurring at the low 12 Williams and Gold (1972) report a white/black end of the frequency distribution (with race differential for seriousness of self-reported one de- exception), we examined race and linquency behavior, but no difference in frequency. class differences at several points along They also report a significantly higher seriousness the original frequency distribution, with a for higher socioeconomic status (SES) boys, but no differences in frequency by SES. We have not conparticular interest in the high end of the sidered seriousness here but, to the extent that our predatory crime subscales reflect the more serious

offenses, our data would support the race differential 1' Mean frequencies were as follows: Lower = and contradict the direction of the class differential

in seriousness as reported by Williams and Gold.2.02;

Working = 1.74; Middle = 1.38.

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104 AMERICAN SOCIOLOGICAL REVIEW Table 2. Percentage of Respondents Reporting Specific Levels of Delinquency by Race and Class

against persons scale, lower-class youth in Total Self-Reported Delinquency

Number of Race Class

Offenses White Black Lower Working Middle Reported % % % % % 0-24 71.8 67.6 71.7 72.3 70.9 25-49 11.0 8.1 10.6 9.4 11.5

50-199 13.1 15.4 11.4 14.4 14.4

200+

4.1

9.8

6.3

3.9

3.2

Predatory

Crimes Against Predatory Crimes Property Against Persons

Number of Race Class

Offenses White Black Lower Working Middle Reported

%

%

%

%

%

0-4 70.6 70.7 77.3 80.0 84.6 5-29 24.1 22.7 18.2 16.1 13.8 30-54 55+

many offenses as do middle-class youth in this category. On the predatory crimes

3.4

1.9

2.4

4.2

1.7

2.8

2.1 1.8

.8 .8

frequency continuum. The results of this analysis are presented in Table 2. The data in Table 2 indicate that the original differences, by both race and class, are due in large part to the relative differences at the high end of the frequency continuum. For example, at the low end of the frequency distribution, the white/black ratios are close to 1:1; but at the high end of the continuum the ratios

are greater than 1:2.14 For class, the lower-class to middle-class ratios at the

low end are again close to 1:1; but at the high end the ratio is 2:1 for total SRD and over 3:1 for predatory crimes against persons.

Not only are the relative proportions of blacks and lower-class youth higher at the high end of the frequency continuum but also, within the high category, blacks and lower-class youth report substantially higher frequencies than do whites and middle-class youth. Lower-class youth in the high category

on the total SRD measures (scores : 200) report over one-and-one-half times as 14 For purposes of discussion, the low end of the frequency distribution refers to total SRD scores S

24 and predatory crime against persons and property scores S 4. The high end refers to total SRD scores - 200 and predatory crimes against persons and property scores ? 55.

the high category (scores ? 55) report nearly three times as many offenses as do middle-class youth in this category. Among those in the high category on the predatory property scale, blacks report over one-and-one-half times as many offenses as do whites. The one exception to the above gener-

alization is that blacks and whites within the high category on the total SRD measure have approximately the same mean frequencies. The black/white differential on this measure thus appears to be more simply the result of differences in proportions of blacks and whites in the high category. In any case, blacks and lower-class

youth are found disproportionately among high frequency offenders. Prior selfreport measures were unable to detect this differential involvement because they used response sets which are sensitive to differences only at the low end of the frequency continuum. We thus conclude that the use of open-ended frequency responses does, in fact, contribute to our finding both class and race differentials. Range of Offenses in SRD Measure

We also believe that the broader range of offenses included in our SRD measure has some effect on these findings. An item-by-item analysis indicates that the particular set of items included in a measure can have a major impact on observed ethnic and class differentials. For example, the predatory crimes against persons scale includes four types of offenses: sexual assault, aggravated assault, simple assault, and robbery. Mean frequencies, by race, on the three types of assault offenses are as follows: Offense Type Whites Blacks Ratio Sexual Assault .03 .15 1:5 Aggravated Assault .12 .50 1:4 Simple Assault 2.07 1.05 2:1 Total Assault 2.22 1.70 1:1

With respect to all three types of assault, these data indicate a major dif-

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RECONCILING DIFFERENCES IN ESTIMATES OF DELINQUENCY 105 ference in frequency, by race. They suggest that measures which include only simple assault items do not have a proper representation of assault items. Given the

Table 3. Mean Standardized Scores for Selected Scales by Race and Class Total Predatory Predatory Self- Crimes Crimes Reported Against Against Delinquency Persons Property

tendency of prior self-report studies to ex-

clude the more serious assault items, findings from such studies are likely to minimize the racial differences regarding assaultive behavior. Even when all three types of assault are represented, an analysis involving a summary assault measure would obscure, in this case, important differences by type of assault. For example, the magnitude of sexual and aggravated assault offenses is so small, compared with that of simple assault offenses, that the inclusion of the latter in a summary measure conceals major differences in the other items and even reverses the direction of the differential. While assault items have been used for illustrative purposes, we believe the problem to be a general one. The inclusion

of both very high and very low frequency items in a single measure may obscure important differences, often differences in seriousness. This is because nonserious offenses tend to be reported frequently, while serious offenses are reported infrequently.

Weighting SRD Items

For some purposes, it may be instructive to weight each item so that its potential contribution to the total score is the same as that of any other item. In this

case, no single high frequency item can dominate the overall score. One procedure for accomplishing this weighting is to transform item frequency scores into standard scores and then add them into a total scale score. This transformation was

performed, and the results are presented in Table 3.

With respect to class differences, this transformation confirms the earlier findings observed with raw frequencies. Significant class differences are observed for total SRD scores and predatory crimes against persons scores, but not for predatory crimes against property scores. In. both cases, the significance levels are

RACE

White - .2452 - .0860 - .0072 Black 1.5317 .4038 -.0117 F 3.870 8.179 .001 Probability ?05 ?005 NS CLASS

Lower .7375 .2194 - .0905 Working .1131 - .0746 .1501 Middle - 1.3341 -.2486 -.080 F 3.771 5.159 1.975 Probability