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Criminal Careers and "Career Criminals,": Volume I (1986)

Chapter: Appendix A: Participation in Criminal Careers

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Suggested Citation:"Appendix A: Participation in Criminal Careers." National Research Council. 1986. Criminal Careers and "Career Criminals,": Volume I. Washington, DC: The National Academies Press. doi: 10.17226/922.
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Appendix A Participation in Criminal Careers Christy A. Visher and Jeffrey A. Roth INTRODUCTION This appendix is concerned with those who participate in criminal careers. More specifically, it reviews estimates of the frac- tion of the population that commits at least one crime during some observation penod. This fraction, called the participation [ever, is of interest as an indicator ofthe pervasiveness of delinquents and criminals in society, and many find the estimates some exceeding 60 percent over the lifetime of urban males surprisingly high. But more important from the perspectives of testing theory and devel- oping policy is an understanding of how par- ticipation varies across subpopulations, and of what factors are associated with greater risk of future participation. The authors wish to thank Alfred Blumstein for stimulating the development of this appendix. We are grateful for helpful comments by many partici- pants in the Workshop on Criminal Career Re- search, especially David Farrington and Robert Gordon. Delbert Elliott, Lyle Shannon, Paul Tracy, Neil Weiner, and Marvin Wolfgang helped us by providing special tabulations and interpretations of their data. We also appreciate the skillful editing by Jean Shirhall. We are responsible for any remaining errors in the appendix. Obstacles to the Understanding and Measurement of Pervasiveness Given the importance of measuring par- ticipation, it is unfortunate that, as noted by Gordon (1976), substantial confusion and ambiguity exist in the literature concerning appropriate measures of pervasiveness and their definitions. The student of participa- tion is thus confronted with such terns as "arrest probability" (Christensen, 1967~; "offender rate" or "'real' rate of onset" (Wolfgang, Figlio, and Sellin, 1972: 133~; "probability of committing at least one of- fense" (Wolfgang, Figlio, and Sellin:281~; "prevalence," used in somewhat different senses by Gordon (1976), Blumstein and Graddy (1982), and Elliott et al. (1983~; "incidence," used in two senses by T. Monahan (1960) and in other senses by Gordon (1976), Elliott et al. (1983), and Farrington (1983a); "static prevalence" (Lit- tle, 19651; "delinquency rate" (Hindelang, Hirschi, and Weis, 1981~; "hazard rate" (Gordon and Gleser, 1974~; "age-specific risk" and "age-specific rate," defined di~er- ently but used interchangeably (Ball, Ross, and Simpson, 1964~; and "criminality" (Hutchings and Mednick, 1975~. While each of these tens reflects some 277

212 aspect of pervasiveness, standardization is lacking across authors with respect to the base (e.g., a cohort, a population, surviving cohort members, surviving cohort members not already offenders) and the observation period (e.g., lifetime, lifetime through a stated age, preceding year, time between record updates, time not incarcerated be- tween record updates). Even when the measures are standardized with respect to these variables, their values depend on the domain of"crime" in which participation occurs (e.g., all offenses, index crimes, felo- nies, specific crime types) and on the par- ticipation threshold (self-reported commis- sion, sel£reported police contact, recorded police contact, court referral, conviction). Therefore, comparison of estimated values across studies is not at all straightforward. As explained by Gordon (1976), the root of some of the confusion is imprecise adap- tation of the epidemiological concepts of `d ,, ~ do. . ~ ,, ~ preva hence ancl 1nclaence. AS le ex- plains, prevalence is generally intended to refer to the fraction of a group currently experiencing a condition, such as heart dis- ease. Incidence describes the group's expe- rience over an interval of time, and the incidence of heart disease during a year is the number of contractions of heart disease divided by the size of the population. Thus, "prevalence" is a concept counting persons, ad. . ,. . Inch ence IS a concept counting occur- rences, and both concepts use the popula- tion as a base. Following Gordon (1976:209), "choosing a verbal label for the kind of rate that is of main interest here is a matter of discretion." However, choosing a consistent set of labels that permits comparisons across studies is important for understanding. To avoid mis- understandings, we refer to the concept as participation. The study of participation would be straightforward if individuals maintained and made available accurate diaries oftheir legal and illegal activities, including pre- cise dates. By using the diaries, it would be easy to measure the fraction participating in robbery, or the larger fraction participating in a broader category of crime, such as "FBI index offenses," or the still larger fraction CRIMINAL CAREERS AND CAREER CRIMINALS that has ever committed a nontragic offense. At the aggregate level, the participation fraction could be tabulated across subpop- ulations of interest. At the individual level, a binary indicator of participation-nonpar- ticipation could be analyzed using sophisti- cated statistical techniques to identify fac- tors associated with a higher probability of participation. Unfortunately, accurate diaries for repre- sentative samples of individuals do not ex- ist. In their place two imperfect devices are commonly used to measure participation- criminal justice agency records of arrests, court referrals, or convictions and the self- reports of survey respondents. Official rec- ords cover only offenders whose participa- tion comes to police or court attention at least once. Presumably, therefore, those of- fenders commit more serious crimes than other offenders, and they may be unrep- resentative in other ways as well (e.g., less adept at avoiding detection, more often un- der the influence of drugs or alcohol, more often from neighborhoods under intensive police patrol). Also, because official records are maintained for operational rather than research purposes, special efforts are needed to augment them with other perti- nent information beyond the demographic data used in police identification. Self- reports of participation, on the other hand, may be sought from more representative samples and may easily be augmented with information on other variables that are hy- pothesized to be risk factors. But the results from the sample that actually responds to the survey may be biased (e.g., if serious offenders are less likely than nonoffenders to cooperate with interviewers). Also, the self-reports may be distorted by the respon- dents' failure to recall events accurately, by their misunderstanding of instructions, and by their intentional deception. These and other problems with official- record and self-report participation mea- sures are discussed by Weis (Volume II). As explained in this appendix, however, many findings obtained by using one of the ap- proaches can be reconciled with findings obtained by using the other. Before report- ing findings, we first discuss the importance

APPENDIX A: PARTICIPATION IN CRIMINAL CAREERS of understanding participation and then specify a conceptual framework for analyz- ing it. Importance of Participation Studies of participation have long been recognized as valuable for both intellectual understanding and policy development (T. Monahan, 1960; Ball, Ross, and Simpson, 1964~. Intellectually, as noted by Blumstein and Graddy (1982), specific attention to of- fender participation is a first step in improv- ing the understanding of the "causes of crime." Many studies ofthe causes of crime have analyzed aggregate crime rates. How- ever, the aggregate crime rate may mask variation in participation levels, in individ- ual offending frequencies, or in the average duration of criminal careers. There is no a priori reason to assume that a common set of causes influences individ- uals' offending participation, frequency, and duration. Thus, disaggregating crime rates into those dimensions is an essential preliminary step if multiple causal struc- tures are to be discovered or confirmed empirically. For example, only by partition- ing the aggregate crime rate into its multi- ple dimensions can one design studies that allow for the possibility that one set of factors (e.g., peer influences, family stress, and school problems) is associated with participation, a second (e.g., economic needs, situational stress, opportunity) with the frequency of serious offending, and a third (e.g., effects of aging, the assumption of legitimate adult activities) with termina- tion of the criminal career. While the sepa- ration of these dimensions by no means rules out the possibility that some factors influence all three dimensions, the analyti- cal separation facilitates testing the hy- pothesis that different forces are operative at the three career stages. If different sets of individual characteris- tics are associated with the respective ca- reer dimensions or stages, identifying them could improve the efficiency and equity of resource allocations within the criminal jus- tice system and elsewhere. For example, subject to ethical constraints, knowledge of 2~3 patterns in participation could suggest strat- egies for designing community-based pre- ventive programs that reduce criminal par- ticipation and for giving high-risk groups of children special priority in admissions to the programs. Similarly, if factors that dis- tinguish offenders from nonoffenders, such as demographic characteristics, were found not to distinguish among offenders in terms of their frequency of serious offending, the effectiveness of criminal justice decisions about arrested offenders could be im- proved. Consideration of policies aimed at spe- cific criminal career dimensions rather than broad-based "crime control" may have dif- ferential implications for the acceptability of various policy alternatives. It has been suggested that correlates of frequency and duration are more neutral in terms of race or socioeconomic status than correlates of par- ticipation (Blumstein and Graddy, 1982~. In that event, strategies based on career mod- ification or the incapacitation of high-rate serious offenders may become more wiclely accepted than early preventive intervention strategies. Thus, greater unclerstancling of the pervasiveness of offenders, their clesis- tance patterns, and their individual offend- ing frequencies as separate components of "the crime problem" is important from both intellectual and policy standpoints. A Conceptual Framework for Offender Participation This discussion draws on the conceptual framework of Gordon and Gleser (1974) and defines terms that are used throughout the rest of this appendix. For simplicity, the terminology is introduced with respect to a single birth cohort. Suppose that a cohort of N individuals was born in a single year, and that It of the cohort members initiate criminal careers by committing their first crimes at age t. Al- though 1~ could theoretically be computed for any age between birth and the age by which all cohort members have died, only a negligible number of criminal careers begin before age 6 or after age 45. One approach to computing cumulative participation in

214 valves the distribution of the age-specific initiation rate, a`, which is defined by a'= IJN for each age.i Thus, a' is simply the propor- tion of the cohort that initiates a criminal career by committing a first offense at age t. Aclding up the initiation rates from zero to any age of interest t* (18, for example), one can calculate the cumulative participation rate, D'*, defined by t*-1 D'*= ~ a'. '=o (2) Perhaps the most common participation measure in the literature reviewed here is Die, cumulative participation by age 18. Another common measure is cumulative lifetime participation, obtained by setting t* to about 45, since few individuals commit their first crime after that age. While at is useful in calculating cumula- tive participation, it does not present a clear picture of the relationship between initia- tion of offending and age. The reason is that a cohort member who began offending by age 15 is no longer at risk of becoming an offender at age 16. Thus, a falling-off of initiation rates at later ages reflects both - iAs defined in Equation 1, a~ is the fraction of the original cohort that commits a first offense at age t. Because some of the original cohort members will have died before age t, al understates the probabil- ity that a surviving cohort member will initiate a criminal career at age t. That probability is given by: I' N - Xt where Xe is the number of cohort members who have died before age t. Over the age range of interest in most studies, say, 16 to 30, X' is negligi- bly small, and so no mortality adjustment is made. Of potentially greater importance is sample attri- tion because of cohort members who refuse to be interviewed or who leave the jurisdiction. Until the cohort reaches middle age, attrition from these causes reduces the denominator more than does mortality. But because those who refuse or leave may commit crimes of which the researcher is un- aware, the numerator is also erroneously reduced, leaving the net effect on a' uncertain. CRIMINAL CAREERS AND CAREER CRIMINALS behavioral patterns of interest to the re- searcher and artifacts of the declining pop 1 ulation at risk of becoming a first offender. To isolate the behavioral relationship, it is common to compute and analyze the age-specific hazard rate, hi, the conditional probability of becoming an offender given that one has not already done so. For age t, hi is defined by It (3) N - Z t-~ ' s=o where Z is the number of cohort members who became offenders before some age, and s and t are indices of age. The term "hazard rate" is borrowed from reliability analysis in operations research, in which, for example. one wants to ignore already- burnt-out light bulbs in computing the probability that a bulb will fail in the next hour of a test. The hazard rate is identical to the "offender rate" or "real rate of onset" reported by Wolfgang, Figlio, and Sellin (1972:132-133, 282~. Because the concept isolates behavioral patterns from mathemat- ical artifacts (also see the discussion in Gor- don and Gleser, 1974), its use in analyses of criminal career initiation is becoming in- creasingly common. Age-specific participation may be com- puted from hazard rates, according to the following formulae t-1 t-1 5-1 Dt= ~ as = ~ he ~ (1 - hr.)' s=0 s=0 r=0 (4) where r is an index of age. Equations 1 Trough 4 are operational only if the age at the first offense is known- 2Gordon and Gleser (1974) first corrected an error made by T. Monahan (1960) in simply summing hazard rates to compute prevalence rates. However, the "correct" equation (9) of Gordon and Gleser itself contains a typographical error. The Monahan error was repeated by Wolfgang, Figlio, and Sellin (1972) in summing their first-index-offense proba- bilities (p. 282) to calculate age-specific index- o~ense probabilities (p. 126), but the magnitude of the error is negligible.

APPENDIX A: PARTICIPATION lN CRIMINAL CAREERS an unusual circumstance. More commonly, D! iS measured through the self-reports of t-year-old respondents when asked if they have ever committed a crime. If arrest rather than commission is used as the par- ticipation threshold, however, the equa- tions can be applied to official arrest records recorded by date. To distinguish between the two thresholds, participation measures based on committing crimes ("doing" crime) are denoted D; measures based on arrests ("busts") are denoted B. For many purposes, attention is focused on the frac- tion of a cohort or other sample that is currently participating in crime, i.e., that commits at least one crime during an obser- vation period. This fraction, the current participation level, is denoted d. Current participation is related to crimes per capita, C, through the parameter, A, the individual offending frequency (i.e., crimes committed per year). The relationship is given by: C = do. An important implication of Equation 5 is that variations in aggregate crime measures can be due to variations in either current participation, cI, or offending frequency, A. Research on A is reviewed by Cohen (Ap- pendix B). The remainder of this appendix is di- vided into three sections. The next section draws on a variety of studies to develop ranges of estimates for cumulative partici- pation by age 18, cumulative lifetime par- ticipation, and current participation. Then, based on other analyses in the same body of literature, the second section reviews find- ings concerning factors associated with participation. The final section presents conclusions and suggestions for further re- search. ESTIMATES OF CRIMINAL PARTICIPATION This section draws on previous research to provide estimates of participation in of- fending, according to the measures just de- fined. The review is organized by type of participation estimate: participation in of 215 fending by age 18 (D18 and B18), lifetime participation (BJ ), participation by high school age (DHS and BHS), and crime- specific current participation (CI).3 We report the values associated with each study as they were reported in published results or, in some cases, as they were derived from data presented. Before summarizing the empirical estimates, we briefly review the history of attention to participation in of- fending. We also discuss the scope of our research review and present an overview of the types of studies and data sources that are commonly used in estimating participation in offending. Background Scholarly attention to participation in of- fending (or "prevalence") became promi- nent in the 1940s and 1950s with the first self-report studies of criminal behavior, which used small local samples (e.g., Porterfield, 1946; Wallerstein and Wyle, 1947; Nye, 1958~. As reported by T. Monahan (1960:67), in the late 1950s, the Senate Committee on Juvenile Delin- quency stated that "probably up to 20 per- cent of the male population coming of age could easily be expected to have a juvenile court record if the 1955 rate remains con- stant" and a member of Me committee (Thomas C. Hennings) noted that addi- tional delinquents would have avoided court contact. As Monahan also noted (1960:67), the estimation procedure that the Senate committee used was very approxi- mate and tenuous, resting on unverified assumptions about the fraction of adjudi- cated delinquents who were repeaters. Af- ter the Senate report was released, Monahan attempted to calculate precisely the estimate in which the Senate was inter- ested, denoted here as Bit. An employee of the Municipal Court of Philadelphia, 3An arrest-based measure of current participa- tion, b, could be defined analogously to d, and crime-based measures for participation by age 18 (Dis) and lifetime participation (D~) are also possi- ble. However, values for Die, Din, and b do not generally appear in the published literature.

216 Monahan used 1957 data on the age distri- bution of first offenders referred to Philadel- phia Juvenile Court, to estimate that about 27 percent of all Philadelphia boys and 8 percent of the girls would appear in juve- nile court in Philadelphia on a delinquency charge before reaching age 18. Unfortu- nately, his method was slightly in error (see Gordon and Gleser, 1974), but nonetheless his calculations established the feasibility of estimating cumulative participation from a single year's data. A few years later, a clear appreciation for the participation (or "prevalence") statistic, also related to officially recorded delin- quency, appeared in Ball, Ross, and Simp- son (1964:90~: Accurate delineation of the incidence and prev- alence of juvenile delinquency is an indispens- able prerequisite to analysis of adolescent behav- ior; it is important to know whether 2 percent, 20 percent, or 40 percent of the American adoles- cents appear in court before adulthood. This important paper included a formal dis- cussion of the methods, definitions, and equations for calculating cumulative partic- ipation from annual statistics, and it also reported estimates based on first court ap- pearances in Lexington, Kentucky. Shortly thereafter, Little (1965) re- sponded to the work of Ball, Ross, and Simpson, noting that their techniques of estimating "prevalence" could result in misleading estimates. In particular, in any single year, persons of different ages repre- sent different birth cohorts. Thus, trends in participation across successive cohorts (i.e., "cohort effects") will cause participation es- timates based on a single year's data to misrepresent offender participation among any single cohort. However, in relatively stable periods, these estimates are suffi- ciently close approximations to be useful for many purposes. This analytic issue is dis- cussed more fully later in this appendix. In the 1970s, attention to the concept and to the estimation of participation in offend- ing was revived by Gordon (1973, 1976; Gordon and Gleser, 1974~. In the only re- view of its kind to date, Gordon (1976) assembled the results of 10 "prevalence" CRIMINAL CAREERS AND CAREER CRIMINALS studies ant] assessed their consistency across different samples ant! communities. Only studies that were based on official records of juvenile delinquency (by age 18) were included. Gordon adjusted the esti- mates in different samples for variation in race composition "in order to enhance for- mal comparability" (1976:203~. For exam- ple, for samples that were dominated by white males, Gordon used data from other samples on black and female participation to arrive at an estimate for all males and females. Gordon concluded that for some purposes a useful criterion of delinquency is the juvenile court record, and, using this definition, he estimated Bit at about 17 percent for white urban males (1976:27 2721. Scope of Literature Review In selecting studies for this review of criminal participation estimates, we used several criteria. First, the study had to re- port participation rates occurring in popula- tions of interest or to provide the data needed to calculate them. This restriction eliminated studies designed to achieve par- ticular rates, by selecting institutionalized populations (for which participation is 100 percent), matched offender and nonof- fender samples (for which participation is designed to be 50 percent), or samples with other precletermined rates (e.g., Glueck and Glueck, 1934, 1940, 1950; Empey and Erickson, 1966; Erickson, 1973; Morash, 1984~. Second, measures of criminal involve- ment that reflect both participation and in- dividual frequency confuse two separate and distinct elements of a criminal career and were therefore not useful for the pan- el's purposes. For this reason, studies using aggregate data, such as UCR arrest or crime rates (e.g., Borclua, 1958; Clark and Wenninger, 1962; Chilton, 1964) are not included in this review. This consideration also eliminated studies that reporter! mean frequencies for specific crimes without sep- arately tabulating the "zero" or "none" cat- egory (e.g., Arnold, 1965; Clark and Harvek, 1966; Williams and Gold, 1972; Elliott and

APPENDIX A: PARTICIPATION IN CRIMINAL CAREERS Voss, 1974; Gold and Reimer, 1975; Krohn et al., 1980; Ensminger et al., 1983) and reports of other indices of criminal involve- ment that combined participation with fre- quency (e.g., "commission of burglary two or more times"; Havighurst et al., 1962; Hathaway and Monachesi, 1963; Berger and Simon, 1974~. Third, following the emphasis in the pan- el's report, we focused primarily on studies ~ . . . . .m · OI participation in specluc serious crimes, such as robbery, burglary, and aggravated assault, or in official-record categories that included those crimes, such as "arrests for nontragic offenses," "juvenile court refer- rals," and "convictions for indictable of- fenses." This focus further restricted the scope of our literature review and elimi- nated self-report studies that tapped only participation in status offenses or minor de- linquency, such as underage drinking, van- dalism, and theft under $2 (e.g., Slocum and Stone, 1963; Akers, 1964; Gould, 1969; Hindelang, 1971; Waldo and Chiricos, 1972), or that combined serious and minor offenses into one scale (e.g., Nye, 1958; Dentler and Monroe, 1961; Winslow, 1967; Hirschi, 1969; Gold, 1970; Walberg, Yeh, and Patton, 1975; Wilkinson, 1980~. The fourth restriction was that the study be published in the English language, ei- ther as a book, journal article, or report to a research sponsor. Papers presented at pro- fessional meetings, unpublished data, or working papers were not included in this review. Types of Studies and Data Sources Participation estimates are available from four types of studies: and · life-table calculations, · prospective longitudinal studies, · retrospective official-record searches' · self-reports of cross-section samples. The first type of study uses life-table techniques to derive participation estimates from annual statistics that describe court or police activity in a single jurisdiction. These studies reflect the participation be 2~7 havior of multiple birth cohorts as of a point in time, and the method is similar to that used to estimate mortality or morbidity at successive ages. Although many police de- partments and courts could compile life- table participation statistics, only a few such studies have appeared in the research liter- ature (i.e., T. Monahan, 1960; Ball, Ross, and Simpson, 1964; Little, 1965; Far- rington, 1981~. If an agency maintains separate age sta- tistics for first offenses (whether defined by arrests, referrals, or convictions), it is possi- ble to compute cumulative participation by a given age. This life-table method of com- puting B is useful because it produces a current "snapshot" of participation patterns among the birth cohorts at risk at the time of the analysis. If the age-specific first-offense rates remain constant across those cohorts, the results are identical to those from a longitudinal study of one cohort (Gordon and Gleser, 1974), and they provide reason- able approximations of a cohort's behavior if trends across cohorts are not unduly severe. Perhaps because the approach does not per- mit analysis of the relationship between participation and variables other than the demographic attributes (age, sex, and race) recorded at arrest, it is not widely used to analyze B. Life-table estimates of age-specific cur- rent participation, b, in a given year can also be easily computed by combining justice agency data on the age distribution of ar- restees or court referrals during the year with data for the same year on the age distribution of the general population. At any age, b is simply the ratio of offenders to the total population. Published studies us- ing life-table approaches have generally reported cumulative estimates only; annu- alized estimates rarely appear in the litera- ture. A second type of study is the prospective longitudinal study. Stimulated in part by interest in the relationships between partic- ipation and a broad array of characteristics, researchers have used longitudinal studies to track one or more cohorts of individuals over substantial follow-up periods. The studies are called "prospective" because

218 they involve samples of persons not known in advance to be criminals their criminal- ity is expected to emerge in the future, if at all. If the cohort is representative of all cohorts at risk of offending during the ob- servation period, the longitudinal approach does not produce participation estimates markedly different from those that would be obtained in a life-table study. The special strength of the longitudinal study lies in its relating participation to an array of variables. Prospective longitudinal studies enable researchers to relate crimi- nal career initiation and participation not only to age, sex, and race but also to char- acteristics of individuals (e.g., poor school achievement, early antisocial behavior), characteristics of their families (e.g., low socioeconomic status, antisocial behavior in parents), and life events (e.g., parental dis- cord and breakup, onset of substance abuse). CRIMINAL CAREERS AND CAREER CRIMINALS few prospective longitudinal studies have been carried out with large samples. We report criminal participation estimates from 10 major prospective longitudinal studies conducted in the United States, Great Brit ain, or Denmark. Analyses are typically per fon~led and interim results published be tween successive waves of data collection. Because estimates in interim reports fre quently change as additional data are gath ered or errors corrected, we tried to obtain the latest comprehensive reports in prepar ing this review. Thus, estimates reported here may differ from published interim es timates based on the same data set. One type of prospective longitudinal study is the two-wave prospective study, which has been used to test the power of some indicator (e.g., teacher ratings of be havior), measured at one point in time, to predict future participation by some subse quent age. While a large number of such A prospective longitudinal study involves studies have attempted to ascertain predic a sample of individuals selected at a point in five power with respect to various measures time. Initially, information concerning the of"delinquency" (see Loeber and Dishion, correlates of interest is gathered from the 1983), this review is limited to those yield subjects, from their parents or teachers, or ing estimates of participation as previously from records of school performance or defined. teacher ratings. The subjects are then The third and fourth types of study in volve single-wave, cross-section samples, for which participation is estimated from either retrospective official records or self reports. Officially recorded participation, Ba' is the proportion of age-a members of the sample who have an official criminal record (police arrest, court referral, or con viction) at the time of sample selection. The samples are usually selected to achieve a particular distribution of one or more hy pothesized correlates of participation. How ever, many of the samples also provide a basis for estimating participation in a sub population of interest. Surveys of cross-section samples can also provide estimates of self-reported offend ing. By their nature, studies in this category are well suited to estimation of crime specific participation. Depending on how questions are worded, studies in this cate gory can yield estimates of either the frac tion of persons who have participated in specific offense types at any time before the tracked over time, and their records are periodically updated. The updates may consist of indicators of criminal activity gathered from official records or sel£reports and information on the correlates of interest or life events that might trigger criminal career initiation. Tracking and record up- dates begin shortly after the sample is se- lected but events occurring before sample selection may also be recorded. In practice, the samples are sometimes selected (and their records located) retrospectively (e.g., a 1945 birth cohort selected in 1964), but on some basis other than known criminal activ- ity. As long as the sample is still represen- tative of the cohort (despite mortality, mo- bility, and other influences), the resulting data may be analyzed as if the sample had been selected at the beginning of the obser- vation period, with the advantage that re- sults become available sooner. Because of the effort involved in tracking chic and 'inflating their records, only a At, a_. ~,,~ ~,,= ~.~

APPENDIX A: PARTICIPATION IN CRIMINAL CAREERS 219 age at time of interview (cumulative partic- nile Aid Division ofthe Philadelphia Police ipation, Da), or only during the year (or Department on officially recorded police some other interval) preceding the inter view (current participation, d). Single-wave survey studies focusing exclusively on mi nor offenses have been excluded from this review, and participation estimates in the reviewed studies are reported only for the more serious crime types. The samples in some of the cross-section studies reviewed here reflect an age range, such as "high school age," and the resulting cumulative participation estimates are denoted DHS. Estimates of Criminal Participation by Age 18 Criminal participation by age 18 is per haps the most frequently reported measure of participation in crime. The measure re flects involvement in deviant or criminal behavior as a juvenile since, in most U.S. jurisdictions, the authority of the juvenile court ends at a person's 18th birthday. Moreover, this measure is easily compared across multiple samples because of its pre cise definition. We located 22 U.S. or for eign studies that reported participation by age 18 for large birth cohorts representing an entire urban area, for samples represent ing some subpopulation of interest, or for smaller"high-risk" samples (see Table 1~. In all these studies, estimates were based on official records of criminal activity re corded police contact, arrest, juvenile court referral, or conviction and thus we report Bit. Self-report estimates of participation are usually obtained by sampling high school students of different ages, and so the number of 18-year-olds in any single study is too small to support estimates of partici pation precisely by age 18. In the following pages, estimates of Bit are drawn from longitudinal studies of two Philadelphia cohorts, other U.S. longitudi nal studies, life-table analyses, analyses of multiple data bases, and British studies. The Philadelphia Cohorts In 1964, Wolfgang and his colleagues began assembling records from the luve contacts with a cohort of 9,945 boys born in 1945 who resided in Philadelphia when they were between the ages of 10 and 18 and were therefore at risk of police contacts in Philadelphia throughout that entire age range. As reported by Wolfgang, Figlio, and Sellin (1972) and shown in Table 1, Bit, as measured by police contacts for nontragic offenses (but including status and liquor violations), reached 34.9 percent for the entire sample, with levels of 28.7 for whites and 50.2 for blacks.4 As expected, participation estimates based on the FBI's Uniform Crime Report (UCR) index offenses (homicide, rape, rob- bery, aggravated assault, burglary, larceny, and auto theft) were lower than estimates based on all crimes, especially for whites (13.6 percent for all males, 8.2 for whites, and 26.8 for blacks). For non-index offenses, Bit was only slightly lower than that for all nontragic offenses, which indicates that very few offenders participated in index crimes only. Particination in crimes involving in- jury or theft was much lower than the other participation rates because of the narrower definition of criminal behavior-only about 7 percent for an offense causing injury and 10 percent for an offense involving theft. Wolfgang and his colleagues later se- lected a second birth cohort for study, 28,338 males and females born in Philadel- phia in 1958 and residing there through age 17. Based on Tracy, Wolfgang, and Figlio (1985), comparisons are presented in Table 1 between cohorts I and II. With the iden- tical domain of"all nontragic offenses" for the two studies, the overall value of Bit, based on recorded police contacts for males, declined slightly, from 34.9 in cohort I to 32.8 in cohort II. However, this small de- crease represents the net effect of larger decreases for each race separately (about 20 percent) and an increase in the proportion 4Some of the studies reviewed in this paper use the race designation "black," while others use "nonwhite." Because blacks comprise nearly all the nonwhite samples studied here, we have used the designation "black" throughout.

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224 CRIMINAL CAREERS AND CAREER CRIMINALS of blacks, among whom participation is recording police contacts for very minor greater. Similarly, when only UCR index infractions of the law, including status of ~ - ~ ~ tenses (Shannon, 1985, personal communi cation). Offenses were considered, Bus, remained vir- tually the same among whites (8.2 to 8.9) and among blacks (26.8 to 26.0), but this resulted in an increase in Bra for such crimes for all males (13.6 to 17.9) because of the changes in the racial composition of Philadelphia. Across the two cohorts, Bus, for non-index offenses declined for both races separately and for the male population as a whole, which suggests greater police atten- tion to the more serious index offenses. The data for females in the 1958 Philadel- phia cohort are based on a sample of 14,000, which is by far the largest group of U.S females for which data on individual crimi- nal behavior are available. For the females in the 1958 cohort, Buff was about 14 percent for a nontragic offense. The participation data for females were also differentiated by race: BE was twice as high among black (18.5) as among white females (9.2~. When data on UCR index and non-index offenses for all females were used, Bra for index offenses (4.0) was about one-third of that for all offenses, and BE for non-index offenses (12.1) was slightly below the level for nontragic offenses. Because the records of police contact are limited to contacts occurring in Philadel- phia, the reported estimates should be con- sidered as reasonable lower bounds. The empirical significance of arrests elsewhere is probably fairly small at age 18, but doubt- less increases as a cohort ages, moves, and travels in connection with military service. Other U.S. Longitudinal Studies In a series of longitudinal studies, Shan- non (1982a) and colleagues followed co- horts of males and females born in Racine, Wisconsin, in 1942, 1949, and 1955 through ages 32,25, and 21, respectively. In all three cohorts, Bit among males, based on re- corded police contacts, was high (41.0 per- cent in cohort I, 47.3 percent in cohort II, and 44.1 percent in cohort III) compared with other similar studies. These high lev- els (see Table 1) are probably due to the fact that considerable emphasis was placed on In a multigenerational study, Robins and colleagues analyzed the arrest histories of 223 black males born between 1930 and 1934, who were selected from St. Louis elementary school records, and 145 of their offspring who had attained age 18 by 1974 (Robins, West, and Herjanic, 1975; Robins and Wish, 1977~. On the basis of arrests for any crime, BE was 38.1 in the original sample of males and 31.4 and 13.6 for males and females, respectively, among their off- spring. Criminal participation among both male samples and the female sample was slightly lower than the estimates among black males and females in the Philadelphia cohorts, despite the narrower focus in Robins's study on juvenile court referrals. Another group tracked in a prospective longitudinal study is a group of 506 males born between 1925 and 1934 in Massachu- setts and identified by school, church, or other agency as either "difficult" or "aver- age" (McCord and McCord, 1959; McCord, 1978~. Half the sample members were ran- domly assigned to the Cambridge-Somer- ville youth study, which provided counsel- ing on a fairly regular basis to these youths between the ages of 5 and 13. The other half ofthe group was not counseled as part ofthe program. The primary intent of the longitu- dinal follow-up was to establish whether the counseling had reduced criminal be- havior, other deviance, ant] other problems as the sample aged. Records of the group were updated when they were in their 30s and again around 1978, when the subjects were between 41 and 50 years old. This study differs from other U.S. longitudinal studies in that it relied on convictions rather than arrests as the indicator of participation. The similarity of the conviction-based Cambridge-Somerville estimates (26.1 per- cent for juvenile offenses) to other arrest- based estimates in Table 1 indicates the high-risk nature of the Cambridge-Somer- ville sample. Palmore and Hammond (1964) analyzed police and juvenile court records through

APPENDIX A: PARTICIPATION IN CRIMINAL CAREERS 1963 for a sample of 319 males and females born during 1942-1944 and whose mothers received Aid for Dependent Children dur- ing 1950 in New Haven, Connecticut. Us- ing a criterion of "known to police or juve- nile court," they computed estimates of Bit for this high-risk sample, 56.0 for males and 15.4 for females. The value for males sub- stantially exceeds all other estimates, in- cluding those of Shannon, which are based on a broad criterion measure. The black- white differential for males is far less pro- nounced in Palmore and Hammond's high- risk sample than in more representative urban samples, such as the Philadelphia cohorts, but the race differentials for fe- males are actually greater than those in Philadelphia cohort II. In 1964, the same year that Wolfgang and his colleagues began their research, Polk ant] colleagues (Polk, Frease, and Rich- mond, 1974; Polk et al., 1981) began track- ing a cohort of 1,227 male high school soph- omores in Marion County, Oregon, the county that includes Salem. Because the county's population is nearly all white, it is reasonable to compare their estimate of Bit in Marion County, 25.0, with the estimate among whites in Wolfgang and colleagues' cohort I, 28.7, and cohort II, 22.7. Gordon (1976:249) described the consistency of these numbers as "a further indication that the rate structure for white populations re- mains practically invariant over a wide range of the urban-rural continuum and consequently over a wide range of types of places." The Marion County sample appar- ently excludes youths who dropped out of high school before the sophomore year. While such dropouts are fairly rare, their participation in criminal activity would be expected to be relatively high. For this reason, and because some sample members may not be recognized as offenders because their crimes occurred in other jurisdictions, the figures of Polk and colleagues are best treated as a lower bound. U.S. Life-Table Analyses In addition to the 1957 participation esti- mates he developed (discussed earlier), T. 225 Monahan (1960) estimated Bit for other years as well, using the life-table approach. On the basis of published Philadelphia Ju- venile Court statistics, Monahan computed distributions of age at the first juvenile court appearance for any offense (including a neg- ligible proportion of traffic offenses) for the year 1941 and for the entire period 1949-1954. By cumulating these distribu- tions of initiation rates, he computed BE for those years. (Data on other ages are avail- able in the original source.) As shown in Table 1, Monahan's estimates are quite sta- ble considering the span of time covered by his research. For males, Bin, was computed to be 17.1 in 1941 and 22.3 in the period 1949-1954. These estimates are about four times the participation rates for females, 3.9 in 1941 and 6.0 in 1949-1954. Monahan also reported substantial participation differen- tials by race: Bin, among black males ex- ceeded Bit among white males by a ratio of about 3 to 1 in 1941 and by about 2.5 to 1 in 194~1954. Among females, black partici- pation exceeded white participation by a ratio of about 4 to 1 in 1941 and 5 to 1 in 194~1954. It was later discovered by Gordon and Gleser (1974) that because of an error in his computational formula, Monahan's results were underestimates of Bin,. Monahan had correctly computed the initiation rate at each age, but in computing BE he had treated the initiation rates as if they were conditional hazard rates. Gordon and Gles- er's results, correcting for this error, also appear in Table 1. Only among black males does the correction change the results by more than one percentage point, raising BE from 40.8 percent to 50.9 percent. Gordon (1976:215) has noted that for blacks, Wolfgang's arrest-based participa- tion measure for the 1945 birth cohort is nearly identical to Monahan's measure (cor- rected) for 1949-1954, based on a narrower criterion of court referrals about 50 per- cent. For whites, however, the corrected court-based measure (17.9 percent) is only about 60 percent of the arrest-based mea- sure. If the referral- and arrest-based statis- tics for blacks actually referred to the same population and incidents, they would be

226 expected to follow the pattern observed for whites, since not all arrests lead to court referrals. Three possible explanations have been suggested by Gordon (1976:237-240, 2761. First, court referrals can be made by parents, schools, and other parties in addi- tion to police, and referrals from these sources may occur more frequently for blacks than for whites. Second, Wolfgang's data include only boys born in 1945 who resided in Philadelphia throughout the pe- riod 195~1962, at a time when whites were overrepresented among out-migrants and blacks were overrepresented among in- migrants. Gordon suggested that if partici- pation rates were lower for out-migrating whites than for nonmigrating whites, and higher for in-migrating blacks than for nonmigrating blacks, then the apparent in- consistency between the analyses of Monahan and Wolfgang would be dimin- ished; however, he acknowledged a lack of supporting evidence for these conjectures. A third possibility is that a higher percent- age of black arrests may lead to court refer- ral, either because black arresters' alleged crimes are more serious or because arrest- ing officers are more likely to refer blacks than whites regardless of the alleged of- fense (Gordon, 1976:239~. Additional data would be needed to test these hypotheses. Ball, Ross, and Simpson (1964), using juvenile court referral data from Fayette County, Kentucky, computed age-specific criminal participation for the year 1960, us- ing the life-table approach. The data in- clude referrals for a broad range of crimes, but only "serious or unusual" traffic of- fenses. Age-specific initiation rates were cumulated to measure Bit, Bit, and BE for males and females. As shown in Table 1, their results for Bit, 20.7 for males and 5.2 for females, are slightly lower than Monahan's corrected estimates. Later, Gor- don (1976) used other data reported by Ball and colleagues to compute BE separately for white males (16.8), black males (43.1), white females (4.2), and black females (10.8~. Gordon's estimates are only approx- imate since they rely on assumptions that racial composition is identical among first offenders and recidivists. CRIMINAL CAREERS AND CAREER CRIMINALS Analyses of Multiple Data Bases Three U.S. studies computed estimates of BE in the course of projecting national ar- rest volumes (Christensen, 1967; Belkin, Blumstein, and Glass, 1973; Blumstein and Graddy, 19821. Because no single data base includes age-specific initiation rates for the entire age range spanning both juvenile and adult offenders, each of these studies in- volves the merging of data from multiple sources. Christensen combined Washington, D.C., and Philadelphia County Court statis- tics to compute both age-specific and life- time participation estimates. As shown in Table 1, his estimate of participation by age 17~/2 was 25.1 for males and 6.5 for females, based on UCR Part I (index) and Part II (non-index) offenses. Six years later, Belkin, Blumstein, and Glass (1973) revised the Christensen esti- mates by replacing his Philadelphia County Court statistics on age-specific initiation rates up to age 18 with the newly available data from Wolfgang's Philadelphia cohort I, discussed earlier. As shown in Table 1, the new data led to higher B,8 estimates for both males (34.0 instead of 25.1) and fe- males (8.0 instead of 6.5) relative to the Christensen estimates. Later, Blumstein and Graddy (1982) com- bined the Philadelphia cohort I data on juveniles with age-specific first-arrest rates for adult male offenders active in the Dis- trict of Columbia in 1973. With the com- bined data set, age-specific participation rates were computed separately for white and black males. Because they focused on only arrests for index offenses, their esti- mates of BE are smaller than those for males in the U.S. studies previously discussed: 8.2 for white males and 26.9 for black males. British Studies In a British study, Little (1965) was ap- parently the first to note that life-table par- ticipation estimates diner analytically from age-specific estimates for any single cohort and that the empirical differences will be large if criminal participation is steadily

APPENDIX A: PARTICIPATION IN CRIMINAL CAREERS . . ~ . . . increasing or ctecreasmg in successive co- horts. Using longitudinal data on a 1942 London birth cohort, Little reported partic- ipation based on arrest for an "indictable offense" (roughly equivalent to U.S. felo- nies, misdemeanors, and serious traffic of- fenses) of 7.8 percent by age 18, the age attained by the cohort in 1960. This esti- mate exceeds his 1952 life-table estimate of 6.8 percent, but is exceeded by the 1962 life-table estimate of 9.6 percent (see Table 1) because crime was increasing throughout Britain generally during the 195~1962 pe- riod. Although Little did not report separate participation estimates for males and fe- males, he noted that approximately 90 per- cent of persons arrested during the period were male. Applying the life-table approach to 1962 data, he reported Bit separately for males and females convicted of an indict- able offense (12.3 and 1.9, respectively). Using the same method, Farrington (1981) reported a further increase in participation 17 years later, as measured by conviction for an indictable offense in 1979. Farrington estimated Bit, at about 15.0 for males and 3.0 for females. On the basis of retrospective searches of court records, the London Home Office (1985) Statistical Department reported the findings from a series of cohort studies of the convictions of persons born during four selected weeks of 1953, 1958, and 1963. Participation estimates for persons con- victed of"standard list" offenses (slightly broader than indictable offenses) are consis- tent with Farrington's projections using the life-table method. Over the 10-year period, BE for males was 16.6, 17.0, and 15.9, re- spectively, for the three cohorts a slight decline in the 1963 cohort. For females, estimates increased slightly across the three cohorts: 2.6, 2.9, and 3.1. Several British longitudinal studies have provided estimates of participation. The first (Douglas, Ross, and Simpson, 1968; see also Wadsworth, 1979), known as the Na- tional Survey, reported that 14.6 percent of males and 2.0 percent of females were con- victed or cautioned by the police for at least one indictable offense by age 17. The sam 227 pie is a 1946 cohort of 5,011 persons born in England, Wales, or Scotland. The cohort was 16 years old in 1962, the reference year for the Little (1965) estimate. The National Survey estimate for males is quite consis- tent with Little's life-table estimate (12.3), as well as with Farrington's (1981) life-table estimate for 1979 (15.01. A high-risk sample of 411 London males born in 1953-1954 and residing in a work- ing-class area of London was the subject of the Cambridge Study in Delinquent Devel- opment. Data collection for this study be- gan in 1961-1962; results are found in at least five major publications (see West, 1969, 1982; West and Farrington, 1973, 1977; Farrington, 1983a), as well as numer- ous others. For the Cambridge study the domain of crime was limited to convictions for "criminal offenses," defined as indict- able offenses more serious than traffic, drunkenness, and common assault. Despite this more restrictive definition, which ap- parently excludes police cautions, the higher estimate of participation relative to the National Survey, 25.7 by age 18, reflects the high-risk nature of this group. Another high-risk sample (Ouston, 1984) from London was born in 1959-1960, 6 years later than Farrington's sample and 14 years later than the National Survey's 1946 birth cohort. As part of a comparative study of 12 inner-London schools, data on teacher ratings of behavior, school performance, and criminal behavior were collected on 2,352 males and females. Criminal records were searched in 1978, when the sample was 17 years old, for information on all official police cautions or juvenile court convictions. As shown in Table 1, criminal participation among males in this sample (29.0) was slightly higher than in the Cambridge study data (Farrington, 1983a). Finally, in another longitudinal British study (Miller et al., 1974),763 children born in Newcastle in 1947 were followed from birth to age 22, and criminal records of court appearances for a broad range of offenses were collected up to age 18.5. Data were also gathered on family structure, school performance, and individual characteristics. Estimates of participation (28.0 for males,

228 and 5.6 for females) are consistent with the findings of the British longitudinal studies by Farrington and Ouston, but considerably higher than those of the National Survey (whose cohort was born only 1 year later) and the Home Office estimates for the 1953, 1958, and 1963 cohorts. The broader defini- tion of criminal involvement in the Miller et al. study, that study's urban sample, and the wider geographical coverage of both the National Survey (England, Scotland, and Wales) and the London Home Office esti- mates probably account for the differences. In all these British studies, the ratio of male-to-female participation estimates ap- pears greater than that in U.S. studies. The average ratio for the eight male/female com- parisons in Table 1 is about 6:1. The varia- tion in U.S. and British male/female ratios is discussed in a later section on male and female differences in participation. Criminal Participation by Older Ages, Including Lifetime Cumulative participation has also been estimated for ages beyond 18 years. When the cutoff age exceeds 45 years, the estimate is often referred to as a cumulative "life- time" participation, Be, estimate, since first arrests (and even first convictions) are rare alter age 45 (see Blumstein and Graddy, 1982~. A review ofthe literature revealed 16 studies from which estimates of participa- tion beyond age 18 could be calculated, including 7 studies that provide estimates of B~ (see Table 2~. U.S. Arrest Projections Estimating cumulative participation through ages greater than 18 requires rec- ords of troth juvenile and adult arrests. In the United States, assembling the necessary records is complicated by the fact that juve- nile and adult arrest histories are usually stored in separate repositories. For several prospective longitudinal follow-ups of se- lected samples, the necessary data were compiled after the researchers obtained permission from the appropriate juvenile and criminal justice agencies. But research CRIMINAL CAREERS AND CAREER CRIMINALS ers using life-table approaches have had to compute their estimates by merging juve- nile arrest data from one sample with adult arrest data from another. These procedures, in turn, have necessitated various adjust- ments as part of the estimation process. Christensen (1967) projected Be, based on arrests for nontraffic offenses, at 50.0 for all U.S. males and 12.0 for all U.S. females. These figures reflect (1) direct estimates for city areas, based on the Philadelphia Juve- n-ile Court data and District of Columbia data on age-specific first-arrest rates, and (2) projections for suburban and rural areas, based on aggregate arrest and age-sex-race data. Lifetime participation by race was reported separately by Christensen for the three geographic areas (urban, suburban, rural). In calculating an overall U.S. rate, we used a lower urban estimate for black males (80.0) than that reported by Christensen (p. 224) to account for some of the problems he raised with regard to the validity of his estimate. Christensen reported higher over- all estimates of BE for black males (68.3) and females (19.7) than for white males (46.9) and females (10.91. According to the Christensen estimates reported in Tables 1 and 2, about half the lifetime risk of of- fending is experienced by age 18 for males, and two-thirds for females. However, the black/white ratios from his data are much smaller than those estimated earlier by Monahan (1960) and Gordon (1976~. Christensen's estimates of BL. were com- puted with some adjustments for sex and race survival differentials, but they were based on fairly sparse first-arrest data at higher ages. Also, Christensen's statistics on rates of first-arrest beyond age 18 were based on a special study of convicted felons, rather than all arresters, in the District of Columbia (see Christensen, 1967~. Christen- sen noted that convicted felons as a group are likely to have first arrests at younger ages than arrestees generally, which would tend to bias his estimates upward in the early adult age range. Nevertheless, Chris- tensen's approximations are credible, and the effect of this bias should be negligible at older ages, when first arrests are unlikely to occur.

APPENDIX A: PARTICIPATION IN CRIMINAL CAREERS Revised national estimates of BE were developed by Belkin, Blumstein, and Glass (1973~. They generally followed Christen- sen's approach, but obtained data on age- specific first-arrest rates from Philadelphia cohort I to substitute for the Philadelphia Juvenile Court data. As shown in Table 2, this change increased the estimated By- based on nontragic arrests for both males (from 50.0 to 60.0 percent) and females (12.0 to 16.0 percent) relative to the Christensen estimates. The most recent national estimates of BE focus on only serious offenses and use more reliable data at older ages. With arrests for index offenses as the criterion, Blumstein and Graddy's (1982) estimates of BE are 14.6 for white males, 52.0 for black males, and 22.8 for all males. Consistent with Christen- sen and Belkin and colleagues, about half the risk of arrest-even for serious of- fenses is incurred by age 18 for both races. All three studies relied on similar data up to age 18, but Blumstein and Graddy's data covering arrests after age 30 omit arrests before age 18. Therefore, as they note, the estimates beyond age 30 would be biased upward because of persons who were ar- rested as juveniles but not arrested again until some age beyond 30. Because the number of such individuals is likely to be small, this bias is not thought to be large. U.S. Longitudinal Studies One of the oldest groups of subjects of a prospective longitudinal study is a group of 473 male and female children treated at a child guidance clinic between 1924 and 1929 (Robins, 1966~. Police arrest records were searched through age 43 in all loca- tions where subjects were found to have resided. For the subjects who were inter- viewed, officially recorded criminal activity was studied in relation to their childhood antisocial behavior, family conditions, and antisocial behavior among their family members.5 Discussion of those relation 5In the update interview of the child guidance patients, Robins and Lewis (1966) obtained the names of 67 sons of sample subjects who had at 229 ships is deferred to a later section. As a by-product, however, this study produced estimates of BE based on official arrest data. As shown in Table 2, BE among former male patients (60.0) is much higher than the other estimates even though juvenile arrests are excluded. For "major" crimes (apparently the FBI's index offenses), participation was 36.0 among males and 5.0 among females, which is higher than Bit for index offenses among white males ant] females in the Phil- adelphia cohort data. The high-risk nature of this sample accounts for much of this variation; Robins's definition of arrest was also slightly broader than that of many oth- ers. The Cambridge-Somerville youth study (McCord, 1979) generated estimates of BE for treatment and control groups. Records for the entire sample were updated in 1978, when the subjects were between 41 and 50 years old. This study differs from the other studies of BE in the United States because it relied on records of convictions rather than records of arrests. For the entire sample, McCord (1981) estimated By at 30.2 per- cent, based on convictions as adults for serious offenses. Because McCord's sample was predominantly white, the Blumstein and Gra~ldy estimate of BE among white males, based on index offenses (14.6), is the most comparable, and McCord's estimate is twice that, which indicates the high-risk nature of her sample. In a separate publication, McCord (1979) reported more complete data on By, includ- ing juvenile convictions, but for only 201 males from the treatment sample. This esti- mate of BL is only slightly higher (35.3~; separate estimates of BE. for property of- fenses (26.4) and personal offenses (16.9) were also reported. Shannon's study of three bird cohorts in Racine, Wisconsin (see Table 1 and related discussion), generated estimates of partici- pation by ages 20 to 30. The proportion of tained age 18 by 1960. Their police records were used to estimate Bit, which was reported as 24.5 for Me patients' sons-comparable to the estimate for white males reported in Philadelphia cohorts I and II.

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234 subjects with recorded police contacts for nontragic offenses was fairly stable across the cohorts: from 53 to 59 percent of the male subjects had at least one nontragic police contact. Shannon's estimates of par- ticipation levels, based on felony arrests by the age at data collection cutoff, rose sub- stantially over time, from 5.1 percent for males in cohort I by age 33 to 5.7 for males in cohort II by age 26, and to 12.7 for males in cohort III at only 22. Shannon (1982a:23) noted that this change may renect policy changes on the part of the Racine polices especially for juveniles, as the department focused more closely on serious offenses. In 1977, Wolfgang published estimates of criminal participation for all nontragic of- fenses through age 30, based on follow-up of a 10 percent random sample of Phila- delphia cohort I. The analysis of the fol- low-up data indicates that, by age 30, par- ticipation among all males had reached 47.3 percent. Foreign Studies Four of the British studies that generated estimates of Bat (see Table 1) also provided estimates of participation by older ages, including one projection of Be in England. As shown in Table 2, Farrington (1981), using the life-table method for estimating participation, reported BE at 43.6 for males and 14.7 for females, based on convictions for indictable offenses. Because a high per- centage of all arrests in England end in conviction, Farrington's projections are com- parable to the arrest-based estimates of Bel- kin, Blumstein, and Glass (1973) (60.0 for males and 16.0 for females) and are quite . . slim ar. Two other studies (Wadsworth, 1979; London Home Office, 1985) reported partic- ipation estimates by age 21, based on longi- tudinal studies of individuals. In cohorts of individuals born in 1946 (Wadsworth, 1979), 1953, and 1958 (London Home Of- fice, 1985), estimates of BE for males were 14.6, 23.3, and 24.2, respectively. Not sur- prisingly, in the 12-year time span, partici- pation among males increased by about one-third. The estimates of BE among fe CRIMINAL CAREERS AND CAREER CRIMINALS males- 2.0, 3.9, and 4.7 in the same time period showed a more dramatic increase of over 50 percent from 1946 to 1958. How- ever, this percentage increase is somewhat misleading because of the low rates of par- ticipation by females. Farrington (1983a) reported BE for the Cambridge study an urban working-class sample of 411 males (born between 1953 and 19541- to be 31.9 percent. Despite his slightly narrower definition of conviction (indictable offenses only), this level of par- ticipation is considerably higher than the 1953 cohort estimate (23.3) published by the London Home Office Statistical Depart- ment. However, the three cohorts studied by the Home Office included children born throughout England, Scotland, and Wales, whereas the Cambridge study's urban sam- ple should be considered relatively high -~ risk. By age 2~, paruc~patlon In the ~am bridge sample had increased to 33.9, which is about 20 percent higher than the national estimate for the 1953 cohort (28.3~. an_ . . .. . .1 ~ _ In another English study, Mitchell and Rosa (1981) computed crime-specific partic- ipation rates for 642 British boys selected in 1961 and followed for 15 years, to an aver- age age of 25. Based on convictions for all offenses, B2s was 14.3, which is less than half that reported by Farrington for his Lon- don sample at the same age. The discrep- ancy no doubt reflects the high-risk nature of Farrington's working-class sample. Several longitudinal studies of adopted Danish children have yielded participation estimates as a by-product of investigations of genetic causes of criminality. The first of these (Hutchings and Mednick, 1975) re- ported participation estimates based on convictions for criminal offenses (statsadvo- katsager) among 662 male children born in Copenhagen between 1927 and 1941 and adopted shortly after birth. Among the adopted children, BJ was reported to be only 15.9. All members of the sample were at least 30 years old when the record search and tabulation were completed. Although the domain of criminal convictions in Den- mark is said to be equivalent to the domain of convictions for indictable offenses in Great Britain, BJ for this cohort is lower

APPENDIX A: PARTICIPATION IN CRIMINAL CAREERS than BY estimated from the National Sur- vey in Britain. Hutchings and Mednick also reported BE based on both criminal offenses and minor offenses (politisager) for 1,145 adopted males, 1,145 nonadopted controls (matched on age, father's occupation, and residence), the adoptive and biological fathers of the adopted children, and the fathers of the controls. As shown in Table 2, the estimate of 16.2 for the adopted children was about double the estimate for the nonadopted control sample (8.81. More than one-third of the biological fathers of adoptees had rec- ords of serious criminal conviction, a figure that becomes even more startling when one notices that of all five groups in the sample the biological fathers had the lowest partic- ipation rate for minor convictions (15.9~. Considering all the studies reviewed here, only this group-biological fathers of the adopted youths seems to break the gen- eral rule that criminal participation for less serious crimes usually exceeds that for more . . serious crimes. Mednick, Gabrielli, and Hutchings (1984) recently reported new criminal par- ticipation statistics based on the entire data base of 14,427 adoptees between 1927 and 1947, together with their biological and adoptive parents. Thus, the analysis is based on 64,283 subjects, the largest sample of any study reviewed here. However, nei- ther the domain of"crime" nor the cutoff age or date for the search of official court records was reported. As in the smaller sample, biological fathers of male adoptees had a high rate of participation based on criminal convictions (28.6~; for the adoptees themselves, BE was 15.9, and for their adop- tive fathers, BE was 6.2. The same relative findings are reported for female adoptees and their biological and adoptive parents, but at lower absolute values. Combining parents and children, BE was reported as 15.9 for males and 4.7 for females. Criminal Participation by High School Age Another category of participation esti- mates arises in studies of self-reported (D) 235 and officially recorded (B) offending in cross-section samples of high-school-age youths. Eleven studies report estimates of crime-specific DHS and six studies provide estimates of BHS, the latter based on either self-reported police contacts or searches of official records. These studies differ from prospective longitudinal studies in that criminal activity is observed retrospectively at the time of sample selection. Most of these studies also include a variety of ages within the sample. The latter characteristic makes it impossible to derive age-specific participation estimates. The studies are im- portant, however, because of the crime- specific estimates they provide for persons of roughly high school apes although not necessarily tor representative population subgroups. Results from the studies are summarized in Table 3. Self-Report Studies Short and Nye (1958; Nye, 1958) were some of the first researchers to use the self-report method to estimate participation rates. They reported DHS for two samples, designated sample I (2,350 Washington high school students) and sample II (515 rural midwestern high school students). In both samples DHS among males was higher for assault (13.9, 15.7) and auto theft (14.8, 11.2) than for grand theft (theft of items worth more than $5~5.0, 3.51. Robbery participation was self-reported by 6.3 per- cent of the rural sample. For these four serious crime types, females were much more likely to be involved in auto theft or assault (about 5 percent) than robbery or grand theft (1-2 percent).6 For both males 6Estimates of self-reported participation in of- fending for specific crime types are highly contin- gent on how questions are worded. In reviewing studies that report participation estimates based on self-reports, we included only those estimates for serious crime types principally assault, auto theft, burglary, robbery, and grand theft (at least $50~. We tried to separate "joyriding" from auto theft and "fighting" from assault, but often the authors did not provide enough information (e.g., the exact word- ing) to be able to distinguish participation estimates for serious crimes from those for minor crimes. For

236 and females, DHS was not markedly dif- ferent across the two samples, which may reflect a relatively low degree of urbaniza- tion among the Washington sample. After the work of Short and Nye was published, self-report studies of criminal activity among youths flooded the research literature. Most ofthem were excluded from this review because participation estimates were not derivable from the published re- ports. Five studies, however, reported par- ticipation estimates for serious crimes, which appear in Table 3. In a reanalysis of data from a large study carried out in California by Hirschi (1969), Jensen and Eve (1976) calculated crime- specific estimates of DHS, which were not reported by Hirschi. This study is one of only two studies that include self-reported estimates of D for whites and blacks (the other is Hindelang, Hirschi, and Weis, 1981~. For grand theft, DHS in the Jensen and Eve reanalysis differs markedly be- tween white males (6.0) and black males (12.0), but the estimates for auto theft do not differ by race (11.0, 13.01. The same pattern exists for females, although the low rates of participation for grand theft among females of both races may make such comparisons unreliable. About 4 percent of the females admitted to ever committing an auto theft, but less than 2 percent admitted to theft of items worth at least $50. Three similar studies also reported crime-specific estimates of DHS for males and females (Kratcoski and Kratcoski, 1975; Cernkovich and Giordano, 1979; Figueira- McDonough, Barton, and Sarri, 1981~. For grand theft, the three estimates vary widely, despite consistent definitions of this offense across the studies. Even if participation es- timates for the two large theft categories example, in Me Short and Nye (1958) study, the offense description of "used force to get money from another person" was serious enough to be catego- rized as robbery in Table 3, and "beat up on kids who hadn't done anything to you" is referred to as assault. It is also common for youths to exaggerate Heir devil t behavior, which may inflate sel£re- ported estimates of participation (see Hindelarlg, Hirs- chi, and Weis, 1979; Elliott and Huizinga, 1983). CRIMINAL CAREERS AND CAREER CRIMINALS ($5~$500 and $500 + ) are combined in the study by Figueira-McDonough and her as- sociates (which is likely an overestimate because most offenders committing large thefts have probably also committed smaller ones), the estimates for males (16.0, 12.7, 9.4) are not easily reconciled. Differ- ences in samples may account for some of this variation. The location of the Figueira- McDonough study was less urban than that of Cernkovich and Giordano. The highest estimate (16 percent) is from the oldest study (Kratcoski and Kratcoski, 1975), but the least is known about the nature of that sample; possibly their "theft 50 + " category captured participation in auto theft. The estimates of participation in grand theft for females show less variation (3.0, 4.6, 1.4~. Participation among males in auto theft (5.5, 10.7) and robbery (17.0, 5.0) also varied considerably across studies; differences in question wording and respondent interpre- tation are likely explanations. Self-reported participation by males in burglary was much more consistent in all three studies (20.0, 16.5, 21.2~. Also, self- reported involvement in assault is identical in Cernkovich and Giordano and Figueira- McDonough and colleagues (11.6) despite the differences in samples. Among females, participation estimates for burglary (3.0, 3.7, 4.5) are more consistent than those for as- sault (6.6, 3.9~. For a major study of the ellect of alterna- tive survey techniques on self-reported of- fending, Hindelang, Hirschi, and Weis (1981) interviewed 1,610 male and female Seattle high school students during the school year 1977-1978 and calculated crime-specific estimates of DHS. In compar- ison with the Short and Nye results ob- tained more than 20 years earlier, only in- volvement in theft exceeding $50 showed a substantial increase among males, perhaps an artifact of inflation; the rate of auto theft among high school males appears to have declined. In comparison with the three studies just discussed, estimates of partici- pation reported by Hindelang and col- leagues are higher for grand theft, similar for auto theft, lower for robbery, slightly lower for burglary, and similar for assault.

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240 For many specific crime types, self-report- ed participation rates among males are nearly the same for blacks and whites, or slightly higher for whites. In Hindelang, Hirschi, and Weis, the rates for white and black males were approximately equal for theft exceeding $50 and shoplifting exceed- ing $50; this similarity is contrary to the findings of Jensen and Eve for a sample studied 15 years earlier. White males ex- ceeded black males with respect to auto theft (again contrary to Jensen and Eve) and burglary, while blacks exceeded whites with respect to assault causing injury and robbery. For all crimes, participation among females of both races was lower than among males of either race. In a cross-section survey of 200 male Texas students entering college, average age of 18, Porterfield (1946) reported DHS Of 3.0 for aggravated assault and 8.0 for bur- glary. These estimates are substantially lower than others reported in Table 3, prob- ably because freshmen entering college are not representative of 18-year-olds gener- ally. Finally, Elliott and Huizinga (1984) re- ported data that permit computation of crime-specific cumulative participation, al- though annual current participation rates were originally collected from a five-wave panel design in the National Youth Survey (see Elliott et al., 1983~. The participation estimates for robbery and felony theft are based on the experiences of males and fe- males combined. The sample includes three birth cohorts (1965,1962,1959) whose overlapping age ranges during the 5-year study period cover ages 11-21. Cumulative participation by age 17 is reported here for comparison with other studies in Table 3. The theft measure is composed of four of- fenses- auto theft, grand theft (over $50), breaking into a building or vehicle, and buying stolen property. Therefore, not un- expectedly, Elliott and Huizinga's con- structed estimate of DHS for theft (28.6) is much higher than the other estimates, which are based only on grand theft. How- ever, DHS for robbery (15.3) is lower than the estimate from Kratcoski and Kratcoski (17.0~. . . . CRIMINAL CAREERS AND CAREER CRIMINALS Of~cial-Record Studies In one of the first published studies to estimate criminal participation from official records, Reiss and Rhodes (1961) computed participation on the basis of juvenile court adjudication at age 12 or later for a sample of 9,238 white male Tennessee school enroll- ees selected during 1957. The sample ranged in age from 12 to 18 years and contained a mix of urban and suburban children in the area surrounding Nashville, Tennessee. Participation estimates were re- ported to be 2.1 for serious crimes and 5.1 for all nontragic offenses other than truancy. The participation measure used by Reiss and Rhodes adjudicated delin- quent after age 12-is narrower than that used in other studies in Table 3. Gordon (1976), using untested but not unreasona- ble assumptions, demonstrated that the Reiss and Rhodes estimates could be recon- ciled with the estimates obtained in other studies using broader measures of participa- tion. Four studies are unusual because they present both official-record and self-reports of BHS (Gold, 1966; Hirschi, 1969; Williams and Gold, 1972; Hindelang, Hirschi, and Weis, 1981~. For a sample of 522 Flint, Michigan, youths, Gold (1966) estimated BHS at 11.0 for males according to juvenile court records, and 16.5 according to self- reports of being caught. The self-report es- timate is consistent with the official esti- mates from Philadelphia, since the sample was youths aged 13-16, and the estimate of 16.5 lies midway between the estimates for age 12 (6.3) and age 16 (27.0) in Philadel- phia cohort I. In a study of 3,605 junior high and high school youths in California during the mid- 1960s, Hirschi (1969) reported BHS based on police records and self-reports of police contacts. The average age in this sample was about 14 years. However, the official- record estimates of BHS for white (26.0) and black males (53.0) are about the same as similar estimates among 18-year-old Phila- delphia white and black males (28.7, 50.2~. Self-reports of BHS for white males (34.0) exceeded the official-record estimate, but

APPENDIX A: PARTICIPATION IN CRIMINAL CAREERS the reverse was true for black males (42.0~. If the official records are assumed to be accurate, these findings suggest that the white males exaggerated their contacts with police, but the black males underreported their contacts. Alternatively, the police may have been more likely to record contacts with blacks than with whites, either be- cause the alleged crimes of blacks were more serious than those of whites or for some other reason. Using a 1967 national sample of males and females aged 1~16, Williams and Gold (1972) also estimated BHS based on both self-reports and official records. Unlike the results of Gold (1966) and Hirschi (1969) from single jurisdictions, BHS among both white and black males, based on self- reported police contacts (22.0, 21.0), sub- stantially exceeded BHS based on recorded police contacts (4.0, 5.0~. Moreover, the of- ficial-record BHS estimates lie well below both the Gold (1966) and Hirschi (1969) estimates and the range of 6.3 to 27.0 per- cent in Philadelphia cohort I for males in this age group. These facts together suggest the possibility that officially recorded ar- rests may be underreported in the Williams and Gold national sample because of the difficulty of obtaining complete records from multiple jurisdictions. Hindelang, Hirschi, and Weis (1981) also reported BHS estimates based on official police records and self-reports of police contact and court-ordered probation. A1- most half of the black male subgroup (46.5) had an official police record, compared with 26.7 percent of white males. Unlike the other estimates of self-reported BHS (Gold, 1966; Hirschi, 1969), all demographic sub- groups ofthis Seattle sample reported lower rates than their official records indicated. Underreporting rates ranged from over 50 percent for black males and females to 37 percent for white males. Court-ordered pro- bation was also rather common among this sample 8.7 percent of white males and 18.8 percent of black males. Interestingly, more black females admitted court-ordered probation (9.3) than white males; only 2.1 percent of white females admitted such in- volvement with the juvenile court. Official 24' record estimates were not reported for juve- nile court probation. Finally, in a two-wave study (Feldhusen, Thurston, and Benning, 19731~ a sample of ~_ ', ~ schoolchildren aged ~15 were identified by teachers as either "aggressive-disrup- tive" or "social." After 8 years, criminal records were obtained for the sample to ascertain whether the observations of early deviant behavior predicted subsequent de- linquent behavior. Because delinquency before the first observation (at an average age of 12) was ignored, this study does not yield a precise estimate of cumulative par- ticipation by the average follow-up age of 20. Using arrest records for nontragic of- fenses as an indicator of criminal activity, Feldhusen and colleagues reported By_ for males and females to be 42.5 percent. The separate participation rates based on juvenile court referrals for males and fe- males are 16.0 and 5.0, respectively, for a combined rate of 14.3. These estimates are consistent with Bin, in comparable samples (e.g., T. Monahan, 1960), which suggests that the increment to B between ages 18 and 20 in this sample is about equal to B before the first observation of the sample at age 12. --O ~ ~1 ~ ~ Current Participation Rates ~ he fourth type of participation estimate reviewed here is the current participation rate, ct the percentage of a population committing an offense within some obser- vation interval. Estimates of c! are usually based on self-reports of criminal activity within the past year. In Table 4, data are presented from four studies that report cl for serious offenses (Weis, 1976; Bachman, O'Malley, and Johnston, 1978; Tittle, 1980; Elliott et al., 1983~. In studies in which observation periods longer than 1 year were used (Bachman, O'Malley, and Johnston; TitHe; Weis), we annualized the rates to permit comparisons among them. These an- nualized rates should be interpreted cau- tiouslY~ however, since they assume that offenses were evenly distributed over the observation interval. It is likely that our _ _. , , - , ,

242 e C P 0 - ~l ~ ~Q _ 4 4d ~n tQ a rQ o Q N a,' - U] o a,' a,' a,' P~ a S~ C) m h 4) oo o o _ 4, oo 4J Ll Q ~ a. _ 4) 4' C) O ~ 1 q~ :~ q~ ~ o 0 4' u,- m a, 43 ·a a a' ~ E' _ ~ o x W Q' U] ~4 o a, JJ 10 z Ll a q~ a, a) a ~E" ~a, E ~c' nl - 00 0 r~ 0 ·.~ U~ ~CO · · ~ 0 ~O ~ o' 0 ~ 00 00 · . . . ·· .. d' ~ ~ tD 0 _ r~ · 1 _~ 1 · ~ O4 ~ · ~ ~ r~ tD · · tD ~ 0 0 · ~ ~ r~ · ~ r~ 0 U. ~0 00~ 00 0 . .. ··· ·· ~ tD ~0 CO ~ ~ ~r ~ ~ r~ ~ ~r ~ ~r ~ ~r · .· . · · · ~ N ~ _1 0 0 d' ~ ~ ~r ~ ~un ~r ~ ~ ~u~ ~ tD ~ ~4 ~ C ~ ~ C~ 1 11 1 1 + 1 1 1 11 1 1 1 1 1 1 1 u~u~ U, u' u, ~ tD OD ~ ~ ~ u ~ In ~ u, ~ ~ a' o~ ~ ~ ~ ~r ~o .~1 ~.,1 _, ~ c)1 ~ ~C) ~t)- C) ~ 4J ~ C - ~ ~ C _ P~ ~ ~ ~O4 ~ ~ ~a {D ~01 ~ G' a] N N ~G) N Ll ~ .,1 ~ ~Ll C) . - 0 ~0 0 ~1 0 ~O a 114 ~a q~ `4 ~ ~q~ ~ ~ ~ :' C ~ :' Ul ~n c u~ ~u' C 4~ C ~ ~ C ~ ~ ~ C - - - ~ 54 . - ~ a-1 ~ - ~ . - ~4) ~a) ~ D D D D 4) ~ a' Ul ~ a, ~ a' o~ ~ fE ~ F~ ~e ~ ~ ~ 1 . - 1 . - ~1 · - 1 ~ r0 q~ ~q~ ~ 4, ~ ~IU Ll ~Q, ~0J C) ~ C) :- ~ V ~ ~ ~ a) 4 ~a ~o ~ID ~n {Q U) U) C,q U] - - - - JJ 0 · - a, ~ ~ N 55 tn ~. - C q4 U) 0 ~5 ., ~Ql ~ ~JJ C : 00 ~n ~a, a, ~ 00 0 00 ~_. ~ ~_ _ _ _ ~a ~ a ~t~ ~a ~a ~a :'~ ~ O ~ 0 - ~O O O O ~ o. ~n ~D >, 4, ,,' ~P4 ~q3 c 4) a,G, ~J a' a' 8g C ~ ~ ~0a ~a ~a1 cn ~c' Z~ ~ ~ ~ 1 0 ~I c o ~ a 'O ~D s ~o ~ Q. 4.~ 1- ~ ~ a ~ ~ c ~c ~m ~ 3- E~ ~- O ~0 0 u, 0 H ~t) tD _ ~U) C o C ·- q~ ~ tD ·~1 L~ ·- ~ _I ~ a ~·- ro q~ 05 a~ ~a) - a a ~C ~54 c _I c ro oq ~ r~ ~ ~a ~c~ 0 :' ~ ~ ~ O ~ ~- - C ~ ~ ~ _ _ _ _ · - 1 C _1 ' GJ S JJ ·~1 ~ ~ ~ ~4 ~a ~a -I ~l ~ It~' ~a~ ~ ~ ~ ~a ~l ~ ~ ~0 c c ~c ~ 0 0 Q Q c~1 ~0 ·- ~ ~ 0 4~ tn u~ ~51 ~ ~ a' u~ a~ 1 ~ O ~ O O ~ S 05 N ~ U ~a) _~ C ~ ~ S O J J _I 0 ~4) t ~{D I_ o5 _ ~0~ 1~ ·- ~ q~l ~' ~O U) Ul U} U] _ ~_I ~(~ _ _ _ _ a' ~ · ~ C · · ~ C - :E J- ~qS ~lS ~ ~ 00 _ {,q _ _ _ eq 01 0 C ~ ~tD JJ O s ~ ~a) s ~ ~ ~ O - a ~_ ~_ ~ 0 _ JJ ~C '~ CD ~ ~ ~ JJ ~ ~ a, 4 ~ C ~15 1 - - ~ Co _ JJ a ~tS t- O ~e=m O ~0m e ' - ~4J S C ~. - ~ 00 . - ~S C ~ _~ - JJ c.~ ·~s - ,l _~ - ,~ _~ - ~ ~a - _ ~a 4 ~_~ a~ ~ b3 E ~a: s ca 3 ~1 ~- + .- C o :~. Y o. ~ 60 · ~ 53 C C 13 S ~O ~m ~

243 nl ~n_ ~ ~o U. ~· o ~ ~r ~a' ~r · ·· a, ~c ~ 0 ~ ·- u~U) as ~In u ~a · ~. . - . o o o o ~r0 0 ~ 0 0 0 tD ~ ~O O O O O .. . .... ~.. .. ..... £ a' ~ ~ ~D O ~ ~ ~ d' u~ ~ ~_ _ o CO ~a . · · · · · · ~ tD ~U~ ~ O o ~r ~ ~r~ ~u, c ~ ~r ~o ~ ~ ~ c~ 1 1 1 1 1 + 1 1 1 1 1 1 1 1 ~n u~ u~ u~ u ~ iD a~ a~ ~ u ~ ~ ~ co a~ r~ c ~o ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ r~ ~_ ~_ ~4) a' t1 o O O o O O Q ~n. n ~ ~a 4, a) a, ~a, a) G. cn u ~u~ _ _ _ _ _ _ _ _ _ ~ ~0 ~0 0 0 ~a ~o 4, a, Q) ~a a, a ~a Ul ~q 00 ~a _ _ _ _ _ _ _ _ ~_ ~a ~4 ~4 ~a ~ ° ~32 S33 n ~ a ~a ~a) 4 41 a, ~a, 4' a ~n ~n 10 al ~n _ _ _ _ _ _ 4, ~ · C · ~ C -4 ^ ~ 0 ~ ~ 0 4' ° £ JJ ~ :~: ~ ~_ ~ ~_ ~ C tD ~ O ~ s ~a, ~c _ - ~ O _ a ~- ~ ° - ~m e~a, ~4J, ~c~= JJ a, 4' ~ ~ - ~ ~a ~ 0 a, ~e ~ ~O ~ ~ ~ . - ~4J s C ~ oo ~ ~s C ~ - ~U ~o - ~.- - C.) fe - 4, ~ ~E4 m :c ~m ~4 0 _ q~ s 0 ~s Q' ~E~ r~ ~ ~ ~ c 0 ',, _ 3 .. x - c) Q m ·~ a) .,. 3 3 - a' C) D o a, X o a .,. ~a U] Q oo .,, C ~a ~e) JJ u: a Ll a, e e ·a 00 0 q4 e ~ . - 4, s JJ c - o :, · 0 ~ 4, V, L. ~ °c a, a, 3 0 c C C O O c JJ ~ O Q' ~ ~ 41 ~t) .,. ~ ~ 4, . ~ a' _ ql 4, q4

244 annualized estimates of c! for the three studies underestimate the true annual par- ticipation rate because some offenders in the sample presumably participated during more than one of the years in the observa- tion period. National Youth Survey In 1977, Elliott and his colleagues began tracking 1,725 males and females aced 11-17 in a representative national house- hold sample. Self-reports of criminal behav- ior were obtained annually through 1981. Based on these reports, annual current par- ticipation rates were reported in Elliott et al. (1983~. Although the authors did not present any statistics on crime-specific cu- mulative participation by a given age (ex- cept for the rates for the "synthetic cohort" in Table 3), they did present extensive breakdowns of current participation for spe- cific crime types the first available for a series of years for the same sample. As shown in Table 4, `1 for aggravated assault and robbery for both age groups was higher for males and blacks than for females and whites, and lower for groups aged 1~21 than for groups aged 11-17.7 For breaking and entering, the black-white dif- ferential was much smaller but the declin- ing trend as the cohort aged remained. Ac- tive auto thieves were shown to be extremely rare among all groups-only 1-2 percent of youths were involved in auto theft in any given year. Participation in grand theft was especially high among males and blacks, and increased slightly with age. More precise age-specific data are presented below during a discussion of the relationship between age and participation. 7This drop in participation rates at older ages occurs for most offenses studied by Elliott et al. (1983~. However, Fanington, Ohlin, and Wilson (1986:Chap. 8) suggest that this decline might re- flect changes in sample composition over the 5 years because sample dropouts tended to be black, lower class, and urban groups, which often have high participation rates. Alternatively, the decline might reflect the fact that respondents become less coop- erative and admit to fewer offenses over time. CRIMINAL CAREERS AND CAREER CRIMINALS Youth-in-Transition Project Another national longitudinal study of high school youths, male sophomores se- lected in 1966, was conducted by Bachman and his associates, and results were pre- sented in several studies (see, e.g., Bach- man et al., 1967; Bachman, 1970; Bachman, Green, and Wirtanen, 1971; Bachman, O'Malley, and Johnston, 1978~. On the basis of subjects' self-reports gathered between 1966 and 1974, Bachman, O'Malley, and Johnston (1978) reported c] for five age cat- egories and four crime types robbery, as- sault, auto theft, and grand theft (over $50~. The initial observation period covered the 3-year period when the subjects were aged 13-15, the second observation period was 18 months, and the three other observation periods were each 12 months. When annu- alized, these current participation rates for all four crime types peaked at age 19. Also, at all ages, assault was the most common crime type, followed by grand theft; rob- bery and auto theft were relatively rare crimes. In comparison with these results, Elliott and colleagues' National Youth Survey showed ct to be slightly higher among males for robbery, somewhat lower for auto theft, and slightly lower for grand theft. The more restrictive assault definition (aggravated as- sault only) accounts for the NYS estimates of ~ for males being lower than those from the Youth-in-Transition study. Other differ- ences between the two longitudinal na- tional studies may well be attributable to the 10-year gap in the initiation of the two studies. Self-Reports by Cross-Section Samples Two studies report ~ based on single interviews with respondents. Tittle (1980) presented estimates of ~ based on the self- renorts of a sample of 1,984 adults in three states. The age variation within the sample enabled Tithe to present estimates of ct for a much wider set of age ranges than is pre- sented in reports based on longitudinal studies. For both grand theft and assault, was highest within the age range 1~24 and

APPENDIX A: PARTICIPATION IN CRIMINAL CAREERS then declined for successively older groups. These results are perhaps the only crime- specific estimates of ~ available at these older age ranges. Weis (1976) sampled males and females in both the 8th grade (aged 1~14) and 11th grade (aged 15-17) for a study of delin- quency among middle-class youths. Ques- tionnaires were used to obtain information primarily about status offenses and minor criminal activity in the preceding 3 years. Only 3 offenses of the 34 deviant behaviors studied could be classified as serious grand theft (over $50), individual weapon fight, and illegal entry. Among males aged 16-17, ct for grand theft (2.9) and assault (1.3) was much lower than the estimate for the same age group in Bachman and col- leagues' study (6.0, 12.7~. Summary of Participation Estimates In view of the overrepresentation of males among offenders, in this section we use the previous discussion as the basis for establishing participation rates for all males and for white and black subgroups. Our estimates of participation in offending among males are summarized in Tables 5 and 6. We report two measures because of their relatively wide availability, participa- tion by age 18, Bit, and lifetime participa- tion, Be. Participation by Age 18 For a broad domain of"crime" (but ex- cluding nonoffense contacts), information in Table 5 suggests range estimates for Bis of 13.1-28.7 for white males, 31.4-50.9 for black males, and 17.1-34.9 for all males. These ranges exclude the two outlier stud- ies- Palmore and Hammond (1964), and Shannon (1982a~which used a broader definition of police contact (see earlier dis- cussion). Calculating arithmetic averages for these ranges, average Bis (based on nontragic offenses, but excluding Shan- non's estimates) is 19.8 for white males,41.9 for black males, and 26.7 for all males. Variation within the range for white males seems largely explainable by differ 245 ences in level of criminal justice contact: for example, recorded police contact in the Philadelphia cohort studies (28.7, 22.7) and court referral in T. Monahan's (1960) data (13.11. Thus, the average police contact rate of 25.7 and the referral rate of 15.9 for white males suggest that 62 percent of all police contacts led to court referral. The range for black males is somewhat more difficult to interpret. As indicated pre- viously, the estimates of Monahan, as cor- rected~by Gordon and Gleser (50.9), and Philadelphia cohort I (50.2) appear incon- sistent, but several possible explanations have been offered. The estimate from Phil- adelphia cohort II (41.8) is not comparable to any other estimate because it is based on a much more recent sample. Both estimates by Wolfgang and colleagues are higher than the estimates by Robins, West, and HerJanic (31.4) and Robins and Wish (38.1) for their high-risk St. Louis samples, but their "court referral" is a more stringent criterion than arrest. The estimate of Bit for the St. Louis sample born in the 1930s (38.1) is consistent with T. Monahan's data from the Philadel- phia Juvenile Court in 1941 (37.8~. When considering all males, the range of 17.1-34.9 (observed when Shannon's Racine cohorts and the Palmore and Ham- mond study are excluded) is fairly straight- forward to interpret. At the low end, the estimates of Ball, Ross, and Simpson (20.7) and Polk et al. (25.0), both based on police records, likely reflect the less urbanized setting of their samples. As Gordon (1976) has noted, Polk et al.'s sample was almost entirely white; thus, the position ofthe Polk estimate midway between the two esti- mates of Wolfgang and colleagues for white males demonstrates consistency. The low- est estimate (17.1- T. Monahan) is based on data from the Philadelphia Juvenile Court in 1941. Monahan also estimated a rate of 25.8 for court referrals during 1949-1954 in urban Philadelphia, which is consistent with the estimates by Wolfgang and his colleagues, based on police contacts (31.2, 34.9), if court referral rates are on the order of 75 percent. Christensen's estimate of 25.1 was derived directly from Monahan's. Mc- Cord (1978) reported BE for convicted

246 CRIMINAL CAREERS AND CAREER CRIMINALS TABLE A-5 Official-Record Data on Male Participation Rates by Age 18 (B18) (in percent) Crime Type and Level of Involvement U.S. studies White Known to police or juvenile court 52.0 Nontraffic arrest or police contact Black 63.5 22.7, 28.7 41.8, 50.2 Juvenile arrest and/or court referral 13.1, 16.8, 17.9 Juvenile court conviction Arrest for index offense British studies Conviction or police caution, indictable offenses Conviction for indictable offense All Males 56.0 25.1, 32.8, 34.0, 34.9, 41.0, 44.1, 47.3 31.4, 37.8, 38.1, 43.1, 50.9 __ 8.2, 8.2, 8.9 26.0, 26.8, 26.9 17.1, 20~7, 25~0, 25.8 26.1, 27.5 12.3, 13.6, 17.9 14.6, 28.0, 29.0 12.3, 15.0, 15.9, 16.6, 17.0, 25.7 NOTE: See Table A-1 and related discussion for sources and further description of specific estimates. males of 26.1-27.5, not surprisingly high in view of the high-risk nature of her sample. When a more serious definition of crimi- nal activity is used arrest for an index offense the estimates of BE for white males (8.2-8.9) and black males (26.~26.9) separately are consistent and much lower than the estimates based on nontragic of- fenses. Differences in racial composition produce a wider range of estimates for all males combined (12.~17.9~. The index ar- rest estimates are based on the two Phila delphia cohorts and the most recent na- tional arrest projection (Blumstein and Graddy, 1982~; however, the latter projec- tion was derive(l, in part, from the Philadel- phia data. Participation by age 18 in index offenses, observed in Philadelphia cohorts I and II, suggests an interesting pattern over time. For both black and white males, BE in cohort II (26.0, 8.9) was approximately the same as that in cohort I (26.8, 8.2~. However, participation for ad males increased (cohort

APPENDIX A: PARTICIPATION lN CRIMINAL CAREERS I 13.6, cohort II- 17.9) because cohort II included a greater proportion of blacks than cohort I, among whom BE based on index property offenses was higher. The estimates from British studies, shown in the bottom portion of Table 5, were also discussed earlier. In general, the variation among the nine estimates results from differences in the nature of the sam- ples. The average of these estimates (19.3) is lower than the U.S. range (26.1-27.5), which is based on juvenile court convic- tions for a broader range of offenses than in the British studies. But it is higher than the estimates baser! on FBI index arrests, which cover a more narrow domain than British "indictable offenses." Thus, the only estimates of Bit for males that need] interpretation are Hose for the three Racine cohorts, 41.0, 47.3, and 44.1 based on police records of nontragic of- fenses (Shannon, 1982a), and the Palmore ant] Hammond estimates (52.0, 63.5, 56.0~. The domain of"crime" represented by the 247 Shannon estimates is fairly broad; as we mentioned earlier, it includes status of- fenses as well as many minor behaviors, truancy, and running away. Such a broad domain could explain the high values of the estimates. The Palmore and Hammond study was based on a high-risk sample children bone to welfare clients and they only had to be "known to the police or juvenile court" to be classified as clelin- auent. Presumably, this definition would include incidents such as truancy, running away, and over status offenses. Lifetime Participation In Table 6, the separate estimates of BE for any offense for white (46.9) and black (68.3) males are those derived by Christen- sen (1967) from multiple data bases. Sur- prisingly, no subsequent refinements of his estimates have been attempted for this broad domain of criminal activity despite (or perhaps because of his cautions about TABLE A-6 Official-Record Data on Male Lifetime Participation Rates (pL) (in percent) Crime Type and Level of Involvement White Black All Males Nontraffic arrest 46.9 Arrest for index offense Conviction for serious offenses (unspecified) Conviction for index property offense Conviction for index violent offense 14.6 68.3 52.0 50.0, 60.0, 60.0 22.8, 36.0 6.0,a 29.0, 30.2, 35.3, 43.6 26.4 16.9 NOTE: See Table A-2 and related discussion for sources and further description of specific estimates. aThis anomalous 6 percent applies to the adoptive fathers in Mednick, Gabrielli, and Hutchings (1984), who were presumably screened for absence of criminal records before being permitted to adopt.

248 the estimation difficulties raised at higher ages by black-white survival differentials and the sparseness of initiation-rate data. For all males, Christensen's national esti- mate of BE is 50.0 for nontragic arrests. Replacing Christensen's distribution of early age-specific initiation rates with those of Wolfgang, Figlio, and Sellin's Philadel- phia cohort I, Belkin, Blumstein, and Glass estimated Be at 60.0, which seems to be the best available national estimate of BE among all males. That figure is reasonably comparable to estimates obtained from three U.S. longitudinal studies that fol- lowed male cohorts to the oldest ages. Robins's estimate of 60.0 for her sample of youths treated at a child guidance clinic appears consistent, but most of that sample was born before 1920. According to WolEgang's (1977) follow-up to age 30 of a 10 percent sample of Philadelphia cohort I, 47.3 percent had been arrested for a nontraf- fic offense, but this estimate excluded first arrests occurring after age 30. McCord esti- mated Be through age 40~1 at 35.3 for conviction, a more stringent criterion, but one based on a high-risk sample. Estimates of BE for index offenses by males are taken from Blumstein and Graddy. In turn, BY in that study was com- puted from the 10 percent follow-up of Philadelphia cohort I; beyond age 18, their estimates were computed using a sample of 1973 District of Columbia arresters. Thus, the estimates are clearly most appropriate for urban populations. Narrowing the do- main of criminal behavior from all nontragic offenses to only index offenses reduces BJ substantially among white males (14.6) and all males (22.8), but BE for black males (52.0) remains at a high level. Disaggregating still further, Table 6 shows Be separately for the FBI's index property and violent offenses, but only from McCord's study. For property offenses, 26.4 percent of McCord's male sample had a conviction record by age 41~0, whereas only 16.9 percent had a conviction record for violent offenses. In summary, using arrest or recorded po- lice contact as the criterion, the literature suggests that BY among urban males is CRIMINAL CAREERS AND CAREER CRIMINALS about one in three for all crimes more seri- ous than traffic offenses, and one in five for all index crimes. The corresponding esti- mates for BL. are about 60 percent for all nontraffic crimes and one in four for all index crimes, which suggests that 60 to 80 percent of all criminal careers as mea- sured by official records are initiated by age 18. SeZf-Report Estimates P~rhninat~on estimates based on self- reports of involvement in specific crime types are difficult to summarize. Participa- tion estimates for burglary appear reason- ably consistent (12.~21.2), but more varia- tion exists in the range of male participation estimates for auto theft (5.~14.8), grand theft (3.~17.3), and robbery (4.1-17.0~. Some of this variation can be explained by differences in when and where the study was carried out. Other factors, such as ques- tion wording and respondents' age or race, may also account for some of the inconsis- tencies, but this information was often not reported. Among females, DHS is fairly consistently about one-quarter that of males 2 to 4 percent reported involvement in any spe- cific crime type. Because these estimates are based on self-reported participation (D) rather than only participation that attracted official attention (B), it is not surprising that they seem high relative to estimates of B18 based on broader categories, such as non- traffic offenses. The more interesting comparison is be- tween police contacts as reported by re- spondents and as recorded by police. These are compared in only four studies (see Ta- ble 3 and related text). Unfortunately, those studies reached different conclusions-the sel£report measure was higher than the official-record measure in two samples (Gold, 1966; Williams and Gold, 1972) and among blacks in Hirschi's (1969) sample. But the official-record measure was higher among whites in Hirschi's sample and among both whites and blacks in Hindelang, Hirschi, and Weis (1981~. Dif- ferences among these studies in sample

APPENDIX A: PARTICIPATION IN CRIMINAL CAREERS composition, location, and year of study- in addition to unknown differences in ques tion wording make it difficult to reconcile these disparate findings. Thus, these com parisons between self-report and official record measures of arrest participation are best described as inconclusive. FACTORS ASSOCIATED WITH PARTICIPATION The participation rates reported in the preceding section suggest that demographic variables, such as sex, race, and age, are at least correlated with participation in offend ing. These relationships are summarized and discussed below (Tables 7-9~. Studies linking the demographic attributes of age, sex, and race with participation rates have been conducted primarily because the data for such research were readily available from police records or interviewer observa tion scientific theory has not established a causal relationship between demographics and criminal participation. Several of the studies already discussed include analyses oftheoretically more inter esting correlates of participation, such as family influences, income and social class, and early antisocial behavior. These rela tionships are the primary focus for the rest of this appendix (Tables 1~16~. For the most part, the discussion of correlates is based on findings from research yielding the participation estimates presented in the earlier tables. The life-table studies based on agency statistics are, by their nature, not suited to providing results on correlates of participation, other than demographic cor relates. For this reason, the studies that augmented individual data from official rec ords and self-reports with data on relevant attributes are the basis for discussion here. In nearly all instances, the reported corre lations are consistent with several alterna tive theories of crime. Therefore, strongIn considering Tables 1 - , perhaps the correlations merely suggest fruitful areas formost striking impression is the consistency research using more sophisticated designswith which male participation in offending to test competing theories; in themselves,' they do not generally confirm or disconfirm theories. Two other types of analysis that have 249 yielded insights on factors that may be as- sociated with participation are also ex- cluded from this discussion. Studies that compare hypothesized correlates for sam- ples of known criminals and matched sam- ples of presumed noncriminals have pro- duced some interesting results. However, because known criminals were deliberately selected at a predetermined rate (e.g., 50 percent of sample), those studies cannot produce participation estimates and are therefore outside the scope of this review. An additional problem with such studies is that the criminal subjects are usually incar- cerated inmates. since they are relatively easy to locate and measure in terms of the attributes of interest. Incarcerated subjects are not representative of offenders gener- ally, however, since the imprisonment de- cision is influenced by dimensions of the criminal career, such as its seriousness, in- tensity, and duration. Therefore it is not possible to isolate the relationship of the attributes to participation. The problem of isolating the specific re- lationship of attributes to participation also led to a decision to exclude many analyses in the studies reviewed that relate potential correlates to indices or scales of"criminal- ity." As mentioned earlier, such indices are usually intended to capture multiple career dimensions in a single number and, occa- sionally even the dispositions of arrests for criminal incidents. In analyses in which scale values of zero clearly indicated the absence of known criminal activity, it was sometimes possible to isolate results on correlates of participation in which case the results are summarized here. With these limitations in mind, correlates of participa- tion are discussed in the following subsec- tions. Sex and Participation exceeds female participation in offending, regardless of data source, definition of C`of- fender,', culture, or measure of participa- tion. Drawing on the summaries in Tables 1

250 CRIMINAL CAREERS AND CAREER CRIMINALS TABLE A-7 Summary of Male/Female Ratios of Participation, by Type of Estimate Type of Study (number of studies/samples) Range of Male/Female Ratios BROAD CRIME DEFINITION (official records) Participation by age 18-25 (A 8-25) U.S. studies Aggregate statistics (5) Longitudinal studies (6)b Single-wave (5)c British studies (12)d Lifetime participation (BL) U.S. studies (3)e Danish studies (3)f SPECIFIC CRIMES (self-reports) Aggravated assault (10) Robbery (5) Theft over $50 (9) Auto theft (4) Burglary (5) 3.9-4.4 1.8-3.6 2.5-8.0 4.8-7.3 2.0-4.2 3.0-5.3 1.8-4.5 3.0-5.6 1.8-6.7 2.1-3.8 3.0-6.7 NOTE: It is implicit in each ratio that the rate for females is 1. 2~. Monahan (1960) (2); Ball, Ross, and Simpson (1964); Chrittensen (1967); Belkin, Blumstein, and Glass (1973). -Palmore and Hammond (1964); Feldhusen, Thurston, and Benning (1973); Robins, West, and Herjanic (1975); Shannon (1982a) (3); Tracy, Wolfgang, and Figlio (1985). -All are based on high school samples: Gold (1966); Williams and Gold (1972); Hindelang, Hirschi, and Weis (1981) (3). dLittle (1965); Miller et al. (1974); Wadsworth (1979) (2); Farrington (1981, 1983a); Ouston (1984); London Home Office (1985) (6). eRobins (1966); Christensen (1967); Belkin, Blumstein, and Glass (1973). utchings and Mednick (1975) (3). includes pHS (participation by high school age) and d (current participation); Porterfield (1946); Short and Nye (1958); Tittle (1980); Kratcoski and Kratcoski (1975); Weis (1976); Cernkovich and Giordano (1979); Figueria-McDonough, Barton, and Sarri (1981); Hindelang, Hirschi, and Weis (1981); Elliott et al. (1983).

APPENDIX A: PARTICIPATION IN CRIMINAL CAREERS through 4 that report separate but compara- ble male and female participation rates, Table 7 reports the range of male/female participation ratios for various groups of studies. Except for the prospective longitudinal studies, the U.S. participation estimates in Table 7 that are based on official records generally estimate male participation rates at 3 to 5 times female rates, which is consis- tent with other research (Gordon, 1976:212; Hindelang, Hirschi, and Weis, 1979~. In fact, only 3 of the 13 U.S. life-table and cross- section estimates of participation based on official records lie outside this range (Hin- delang, Hirschi, and Weis, 1981; Robins, 1966~. Of the six ratio estimates from longi- tudinal studies, the relatively low ratio of 2.3:1 reported by Robins, West, and HerJa- nic (1975) for offspring of black males is consistent with a suggestion (discussed be- low) that male/female participation ratios may be lower among blacks than whites. (Note that in all the ratios presented below it is implicit that the female rate is 1.) But no comparable explanation exists for the low male/female ratios observed by Tracy, Wolf- gang, and Figlio (1985) in Philadelphia co- hort II for both blacks and whites. It is interesting to note that for all nontragic offenses, the three consecutive Racine co- horts studied by Shannon (1982a) show suc- cessively lower male/female ratios for Bis (4.7, 3.1, 2.0), a result of increasing partici- pation over time by females and relatively stable participation among males. Moreover, that pattern appears when the analysis is re- stricted to index offenses (data not shown; Shannon, 1985, personal communication). The Danish estimates of Be also produce male/female ratios in the range of 3 to 5. However, the seven British studies, which generated 12 estimates, show a higher range, with male participation (based on conviction) at levels 5 to 7 times those for females. Because the Danish studies show- ing ratios similar to the U.S. ones are also based on convictions, the higher British ratios likely reflect cross-national differ- ences in behavior rather than the narrower definition of participation. 25] Table 7 also reports ranges of the male/female ratio of crime-specific partici- pation rates based on self-reports. The crime-specific participation rates for fe- males are quite small, so these male/female ratios should be interpreted cautiously. The range of ratios is also relatively wide. None- theless, few of the 32 available crime- specific ratios exceed the ratio of 5 to 1 observed for the broader categories of crime. Eight of the participation studies re- viewed provide comparable male/female participation ratios separately for blacks and whites. For 17 of the 20 estimates, the male/female ratio is lower among blacks than among whites, which reflects much greater racial differentials in female partici- pation than in male participation (the ex- ceptions are from self-report studies). Thus, Palmore and Hammond (1964), using a very broad definition of crime, reported a male/female participation ratio of 6.2 for whites but only 2.0 for blacks. Based on juvenile court referrals, T. Monahan's (1960) data reveal male/female participation ratios of 5.3 for whites and 3.2 for blacks. Christensen's (1967) data are also consis- tent 1.3 for whites and 3.5 for blacks. Us- ing self-report data, Hindelang, Hirschi, and Weis (1981) reported similar male/ female ratio patterns by high school age for robbery (5.8 for whites and 3.0 for blacks), theft exceeding $50 (9.7 and 2.7), auto theft (12.1 and 4.3), burglary (3.4 and 3.0), and assault (3.2 and 1.7~. A few studies report essentially no differ- ence in male/female ratios for blacks and whites. In Philadelphia cohort II (Tracy, Wolfgang, and Figlio, 1985), the ratios were only slightly lower for blacks (2.2) than for whites (2.5) for nontragic offenses, and sim- ilar patterns emerged for UCR index (4.3, 4.9) and non-index (2.2,2.4) offenses. (See also Ball, Ross, and Simpson, 1964; Elliott et al., 1985~. But as a rough approximation, it appears that, in the United States, offenders are 3 to 5 times more prevalent among males than among females, and that the ratio is toward the high end for whites and toward the low end for blacks.

is 1. 252 Race and Participation Drawing on results in Tables 1 through 4 that report separate participation estimates for black and white males in a common sample, Table 8 reports black/white ratios of participation estimates. For example, for a broad definition of crime, the black/white ratio for BE is approximately 1.75:1 in the Philadelphia cohorts. In the high-risk sam- ple studied by Palmore and Hammond, the ratio for Bit is only 1.2. The two ratios derived from life-table estimates are higher and consistent with each other (2.6, 2.8), but an especially low ratio is reported by Christensen (1.5) for BL. When attention is restricted to only the more serious crimes, the ratio for BIS, is CRIMlNaL CAREERS AND CAREER CRIMINALS much higher: 3.3 and 2.9 in Philadelphia cohorts I and II, respectively, for all FBI index offenses. Blumstein and Graddy re- port ratios of 3.3 and 3.6 for B18 and BL, respectively. While the ratios for crime-type groups are all derived from official records, ratios for five specific crime types have been esti- mated from studies based on self-reports (Jensen and Eve, 1976; Hindelang, Hirschi, and Weis, 1981; Elliott et al., 1983~. Black/white ratios from those studies (see Tables 3 and 4) are consistently lower than the ratios for broader crime types based on official records. In contrast to the broader crime-type groups, the black/white partici- pation ratios for auto theft, burglary, and grand Weft are generally around 1:1, and TABLE A-8 Black/White Participation Ratios for Males in Official-Record Studies Source By Age 18 Lifetime Broad Crime Definition T. Monahan (1960) Ball, Ross, and Simpson (1964) Palmore and Hammond (1964) Christensen (1967) Hirschi (1969)a Wolfgang, Figlio, and Sellin (1972) Hindelang, Hirschi, and Weis (1981)a Tracy, Wolfgang, and Figlio (1985) Average Ratify All Index Offenses 2.8 2.6 1.2 __ 2.0 1.7 1.7 1.8 1.8 Wolfgang, Figlio, and Sellin (1972) Blumstein and Graddy (1982) Tracy, Wolfgang, and Figlio (1985) 2.9 1.5 1.5 3.3 3.3 3.6 Average Ratiot 3.2 3.6 NOTE: It is implicit in each ratio that the rate for white males Chased on participation by high school age. ~ alculated from the sum of all estimates of participation for blacks and the sum of all estimates for whites in Tables 5 and 6.

APPENDIX A: PARTICIPATION IN CRIMINAL CAREERS some ratios are less than 1. Only for robbery and assault do blacWwhite ratios based on self-report data approach those based on official records in Table 8. However, these variations across data sources (self-reports ~ ~ . . . ~ and omc~a~ recorcts) may be due to the different age groups represented and the generally lower participation estimates for specific crimes. The comparability of offi- cial-record and self-report results concern- ing race differentials is considered by Weis (Volume II). Age and Participation Several of the studies summarized in Ta- bles 1 through 4 provide year-by-year data that can be used to study the relationship between age and participation. It is impor- tant here to distinguish between two alter- native ways of defining that relationship: as the probability of initiating a criminal ca- reer at a given age (summarized in Table 9) and the probability of committing an of- fense at a given age (see Figure 11. It is useful to recall the distinction be- tween two alternative notions of the proba- bility of initiating a criminal career. The "age-a initiation rate" is the probability that a member of a sample becomes an offender at age a. Many of the participation rates by age 18 that are reported in Table 1 were computed, for example, by summing initia- tion rates from ages 6 (about the earliest that persons are ever arrested) through 17. But in trying to understand the relationship be- tween age and initiation probabilities, the initiation rate can be misleading, because at successively later ages, more of the offend- ers in the sample have already begun of- fending and are therefore not still at risk of becoming offenders for the first time. That is, a sample member who became a first offender by ace 16 has zero probability of becoming an offender at age 17. Thus, it is helpful to estimate the probability of be- coming an offender at age 17 among only the 16-year-olds who are not already of- fenders. These conditional probabilities, or hazard rates, are reported in Table 9 for four studies in which either the rates or the data for computing the rates were pub _ 253 fished. For each study, the peak values of the hazard rate are underscored. Hazard rates for initiating criminal ca- reers are highest in the age range 1~18 for all seven distributions in Table 9. They decline quite rapidly during the late teens, and are well below half their peak values by age 21. Even for the broad domains of crime examined in the studies by Wolfgang and colleagues and in the British studies, the peak hazard rate at any age is less than .1. Two ofthe patterns reported in Table 9 are somewhat surprising. First, while hazard rates for the first index offense are higher for blacks than for whites at all ages, the black rate does not peak until age 18, 3 years after the peak for whites, according to Blumstein and Graddy. Second, in Philadelphia cohort I, the peak age for the first FBI index of- fense is 15, 1 year earlier than the peak age for all offenses. The latter finding raises questions about the extent to which delin- quent careers progress from less serious to more serious offense types. Evidence con- cerning such progressions is considered systematically by Cohen (Appendix B) and in Chapter 3. The relationship between age and the probability of committing an offense is best examined with age-specific current partici- pation rates, d. Four studies reported this participation measure for specific crime types (see Table 4 and earlier discussion). However, in three of the studies (Weis, 1976; Bachman, O'Malley, and Johnston, 1978; Tittle, 1980), estimates of c! were not reported for consecutive ages. Never~e- less, some age trends are apparent in those studies. In a five-wave longitudinal study, Bach- man, O'Malley, and Johnston (1978) found a consistent increase in ~ through the mid- teens to a peak at age 19 (the fourth wave) for four crime types, and then a sharp de- cline at age 23 (the last wave). Weis (1976) reported that c! was higher among those aged 1~17 years than those aged 12-14 years for burglary and grand theft; however, for assault, ~ was higher among the younger group. Using broader age categories, Tittle (1980) found that ct decreased markedly in the mid-20s. For example, among those

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APPENDIX A: PARTICIPATION IN CRIMINAL CAREERS (a ~ Robbery of Strangers 4.0 ~ =51 ~ 2.5 - 3.0 2.0 _ - 1.5 r 1.0 : .5 7.0 251 6.0 of o ~4.0 A: 3.0 5.0 it Lid 2.0 cr cr c: 1.0 o \ (1.2~.6) (0~.7) (.5~.6) ,~,, V\ - (0-2.1 ) - (0-1 .4) (0-2.4) 1 1 1 1 1 1 '- ' 1 11 12 13 14 15 AGE (b) Breaking and Entering (0-2.5) , 1 1 1 1 1 1 1 1 16 17 18 19 20 (3.1-10.1 ) \ (1.6-7.7) /> (.2/7) (.1 -3.7) \/ 11 12 13 14 15 AGE 255 16 17 18 19 20 FIGURE A-1 Age and current participation rates for specific crime types for three cohorts. Source: Derived from data in Elliott et al. (1983~.

256 aged 1~24 years, d was 3.2 percent, but it dropped to only 1.4 percent among respon- dents aged 25~4 years. Despite some consistent pattems, the re- sults from these studies are not based on annual age-specific estimates of d. The es- timates of ~ for all three studies had to be annualized because observation periods ex- ceeded 1 year and two studies used cross- section samples with multiple ages, which may confound age and cohort effects. To our knowledge, the only longitudinal study to report ~ annually for successive years is the National Youth Survey (Elliott et al., 1983~. Figure 1 plots ~ over the 5 years of data collection for three birth cohorts in the Na- tional Youth Survey, using breaking and entering and robbery of strangers as repre- sentative crime types. The 1,725 males and females in the national sample were 11-17 years old in 1976 and 1~21 years old in 1980. We selected the 1960,1962, and 1964 birth cohorts (aged 12, 14, and 16 years, respectively, in 1976) from the seven co- horts in the study. Confidence intervals (with p = .05) reported by Elliott et al. (1983) appear in parentheses for the first and fifth years. Looking first at the age-specific cts for breaking and entering-a typical teenage offense the pattern for each cohort shows a general decline over the 5 years of data collection. However, this decline occurs in both the 1960 birth cohort (aged 12-16 dur- ing the study) and the 1964 birth cohort (aged 16-20 during the study) despite the age differences. In addition, the peaks in c! occur for consecutive ages (ages 13,14,16, respectively) for each of the three cohorts, rather than for the same age, as would be expected if crime-specific ~ generally peaked at a specific age. A similar pattern exists for robbery. Thus, these patterns do not appear consistent with a general in- crease in ~ through the mid-teens and a decline during the late teens and early 20s. Moreover, the confidence intervals shown in Figure 1 reveal large overlaps in the first and fifth estimates for each cohort, which support the view that these year-to-year changes in ~ are not statistically significant. For example, to interpret the apparently CRIMINAL CAREERS AND CAREER CRIMINALS sharp decline in d for robbery from age 12 (3.9 percent) to age 16 (0.9 percent) as an age effect is misleading, since the confi- dence interval around the upper estimate (1.2 6.6) overlaps that of the lower estimate ((~2.1). Given these two confidence inter- vals, the hypothesis that ~ at ages 12 and 16 is similar in this sample is not untenable. The confidence intervals also overlap for the five other pairs of ct estimates. A tabula- tion not reported here, in which all cohorts were combined, also did not suggest sys- tematic interaction between ct and age over the range 11-20. Other Factors Associated with Participation Only a few of the studies discussed above had estimation of participation levels as a sole objective. Rather, most of them were intended to relate participation to character- istics of individuals, their families, or other environmental factors. In the literature re- viewed here, the usual approach to study- ing such relationships was to compare par- ticipation across subsamples defined in terms ofthe characteristics of interest. A few ofthe studies reported bivariate statistics or used multivariate techniques to examine the relationship between participation and a set of several characteristics simulta- neously. Throughout this discussion, the reader should bear in mind that even the strongest and most consistently replicated statistical associations would not support many predictive uses of these factors, be- cause predictions based on them would lead to unacceptably high error rates. Tables 10 through 16 summarize the comparative and multivariate (MVA) results of studies that relate participation to the following sets of characteristics: socioeco- nomic status (SES), family structure and disruptions, family influences (including parental behavior), family members crimi- nal behavior, school performance and intel- ligence, early antisocial behavior, and other characteristics. We have limited this review to published reports from which estimates of overall participation can be derived (ei- ther based on official records or self-reports)

APPENDIX a PARTICIPATION IN CRIMINAL CAREERS and have omitted other types of studies (e.g., matched samples) for the reasons pre- viously explained. Also, we omitted much of the literature oriented primarily toward delinquency precliction (for reviews, see Loeber and Dishion, 1983; Loeber and Stouthamer-Loeber, 1986~. Because of these omissions, and because the designs of the reviewed studies were guided by a variety oftheoretical orientations and objec- tives, the following discussion should not be regarded as a complete treatment of factors associated with participation. Never- theless, it does summarize the implications of one important body of literature for the understanding of participation in offend- ing. Socioeconomic Status The debate over the relationship be- tween social class and criminal behavior is one of the oldest in criminology, and much of it has been carried on in literature other than that reviewed here (e.g., Merton, 1938; Kvaraceus, 1944; A. Cohen, 1955; Nye, Short, and Olson, 1958; Akers, 1964; Hirschi, 1972~. (For other reviews, see Tit- tle, Villemez, and Smith, 1978; Hindelang, Hirschi, and Weis, 1979; Clelland and Carter, 1980.) Nevertheless, the literature summarized in Table 10-focusing only on studies that report participation rates- constitutes an important part of the debate. Although disagreement exists over the nature of the relationship between social class and criminal participation, recent studies support the view that social class is generally not related to seZf-reported crim- inal behavior because this method of data collection primarily taps nonserious of- fenses, including vandalism, fighting, school infractions, and small thefts (e.g., Hindelang, Hirschi, and Weis, 1979; Clel- land and Carter, 1980~. However, a strong relationship usually appears when partici- pation is measured by official police or court records presumably because of a higher level of seriousness in those data. As noted by Hindelang, Hirschi, and Weis (1981: 181), a finding of no relationship in analyses of self-reports but of an inverse association 257 in official-record studies dates back to Short and Nye (1957) and can be supported by early statements on conflict theory (Bonger, 1916; Sellin, 1958). The findings presented in Table 10, however, suggest a more com- plicated relationship. Results are presented in Table 10 for three official-record studies published in the 1960s and early 1970s-Reiss and Rhodes (1961), Gold (1966), and Philadel- phia cohort I, as analyzed by Wolfgang, Figlio, and Sellin (1972) and reanalyzed by Jensen (1976). In various ways, all appear consistent with the hypothesis that delin- quent or criminal behavior is more preva- lent among members of lower socio- economic classes. Within occupational categories, Gold (1966) reported a similar pattern that is also consistent with higher participation rates among lower socioeco- nomic groups. Reiss and Rhodes (1961) analyzed partic- ipation rates for serious delinquency (i.e., having a court record of conviction for ag- gravated assault, armed robbery, grand lar- ceny, auto theft, or burglary), by white- collar/blue-collar status of the subject's father and by IQ. For all IQ levels, partici- pation in offending among sons of blue-col- lar fathers exceeded participation among sons of white-colIar fathers; however, the differential increased with IQ level, both relatively and absolutely. Data on socioeconomic status, race, and participation published by Wolfgang, Figlio, and Sellin (1972:55) were the sub- ject of a later reanalysis by Jensen (1976). The data clearly show an inverse relation- ship between socioeconomic status and par- ticipation, both overall and for each race separately. They also show a substantial racial effect within each socioeconomic sta- tus, and Jensen differed from Wolfgang, Figlio, and Sellin only in his view of the appropriate relative emphasis on the two attributes. On closer examination, however, the findings from these studies are probably not reliable indicators of the class-crime rela- tionship, especially for urban areas in the 1980s. Wolfgang, Figlio, and Sellin used an ecological measure of social class, mean

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262 census tract income, which may have little relation to individual socioeconomic status (see Tittle, Villemez, and Smith, 1978; Hindelang, Hirschi, and Weis, 1981~. The study by Gold (1966) was based on a high school sample from Flint, Michigan, and only 28 youths had juvenile court records. Thus, Gold's data by social class in Table 10 are based on very few individuals. Finally, the Reiss and Rhodes study is based on a large sample but some of the offenses re- corclec! in their juvenile data occurred as early as 1950. As shown in Table 10 also, three studies from approximately the same time period and based on official records show small or negligible relationships between socioeco- nomic status and participation (Robins, Gy- man, ant! O'Neal, 1962; Polk, Frease, and Richmond, 1974; McCord, 1979~. Robins, Gyman, and O'Neal reported a small class relationship among their patient sample and a slightly larger association in the control group. But only 11 of the con- trols were classified as delinquents on the basis of police arrest records. McCord first computed measures of partial correlation between alternative indicators of socioeco- nomic status and participation by average age of 43, then estimated a regression equa- tion including only the explanatory vari- ables with strong partial correlations. Even though McCord's two measures of socioeco- nomic status tapped different dimensions, father's occupation and neighborhood qual- ity, neither showed even a strong partial correlation. The lack of a relationship may reflect a small elect of childhood social class on adult criminal behavior or homoge- neity in socioeconomic status within the sample. Nearly 60 percent of the respon- dents' fathers in McCor(l's study were clas- sified as unskilled workers, over 90 percent were classifier] as either unskilled workers or skilled tradesmen, ant] all neighborhoods were "congested urban." Similarly homo- geneity may have masked relationships in the study by Polk, Frease, and Richmond, and the one by Robins, Gyman, and O'Neal. In the coroner, the location of the study, Marion County, Oregon, floes not include any large cities and the measure of socio CRIMINAL CAREERS AND CAREER CRIMINALS economic status was simply a dichotomous indicator of the father's occupational status. In Robins and colleagues' sample of chil- dren seen at a guidance clinic, more youths were from lower-class families. Finally, in a study of juvenile delin- quency, Hindelang, Hirschi, and Weis (1981) examined the cIass/participation re- lationship based on a broad range of of- fenses in official records. Unfortunately, participation rates by status group were not presented. However, the authors reported gammas of only -.17 (based on median income of census tract) and -.05 (based on father's occupation) and concluded that "by neither measure of social class and by no measure of delinquency is there even a ,, , moderate relation between the two-- tp. 196~. These conclusions are consistent with the data in Table 10. Thus, the relationship between social class and participation, as measures] by of ficial records, is not as clear-cut as previous literature has suggested. When participa- tion is restricted to serious offenses in of- ficial records (e.g., Reiss and Rhodes, 1961; GoIcI, 1966), the relationship appears stron- ger. Recent evidence, however, is limited in part because of the (lifficulty of linking official records and individual interviews for a common sample. Some existing data sets presumably contain He necessary data, but the analyses have not been reported in the literature (e.g., McCord, 1979; Hinclelang, Hirschi, ant! Weis, 1981; Shan- non, 1982a; Thornberry ant! Farnworth, 1982~. Results ofthe few self-report studies sum- marizec] in Table 10 are somewhat ambigu- ous. Elliott et al. (1983) reported crime- specific current participation rates by a three-category socioeconomic classification. Only for aggravated assault and all index offenses was current participation consis- tently greatest among the lowest socioeco- nomic group. For breaking and entering, theft exceeding $50, and robbery, the group with the highest participation rates varier! by age between the lowest and midcIle socioeconomic group. Auto thieves were so rare in all classes that no pattern can be ascertained. In other analyses of these data

APPENDIX A: PARTICIPATION IN CRIMINAL CAREERS (Elliott and Huizinga, 1983), social class differences emerged when criminal partici- pation was restricted to serious offenses (felony assault scale, all index offenses, and robbery), and this association persisted after controlling for race. Williams and Gold (1972:Figure 7) re- ported a relationship between social class and participation (based on self-reports of police contacts) that appears inverse to the relationship observed by others using offi- cial records. Reported participation among white males decreases from 19 percent in the highest category of father's occupational status to 9 percent in the third-highest cat- egory and rises to 11 percent in the lowest category.8 But based on gamma statistics, they characterize this relationship as "neg- ligible," report that inclusion of blacks fur- ther "diminishes" the relationship, and re- port "no reliable relationship between social status and police contacts among girls" (1972:221~. Noting the difference be- tween these results and the results of stud- ies based on official records, Williams and Gold speculated that among youths who come to police attention, blacks, who are almost exclusively of lower status, are more likely than whites to be referred to courts and "become more officially delinquent during the judicial process" (1972:227~. However, they provide no direct tests for racial or socioeconomic correlates of the decisions to refer and to record, and only 53 black males were in their sample. Hindelang, Hirschi, and Weis (1981:196) also collected data on social class and self- reported participation, although participa- tion rates were not reported. Using father's occupation as the measure of social class and a constructed index of involvement in serious offenses, they reported gamma be- tween social class and participation for white males of only -.08, which is incon- sistent with the results from Elliott et al.'s study. Williams and Gold (1972:225) also reported that the association between social class and participa- tion, based on official police records, is negligible among white boys, but "statistically reliable" among white girls. 263 Finally, two British studies show strong relationships between social class and par- ticipation. In examining participation based on conviction for an indictable offense by age 25, Farrington (1983a) reported signifi- cantly higher participation among members of the lower status group, as measured by family income at age 8 and quality of hous- ing at ages ~10, but not by parent's occu- pation at either ages 8-10 or age 14. How- ever, using multivariate techniques to identify correlates of participation within specific age intervals, he reported that the occupation-based measure at age 14 was related to conviction at ages 17-20. In addi- tion, family income at age 14 was signifi- cantly related to participation at ages 21-24 and family housing at ages ~10 was related to conviction at ages 1~13. In other analy- ses of the same data, not reported in Table 10, Farrington (1979b) reported that low social class at age 8, but not at age 14, was related to self-reported delinquency. For a national British cohort, Wadsworth (1979) reported participation estimates based on convictions by age 15 at 6.8 among children of professional-salaried workers, 15.5 among children of other nonmanual workers, 22.9 among children of unskilled workers, and 15.3 among children of agri- cultural workers. For the industrial occupa- tions, similar findings (not shown) were reported by Ouston (1984) for a sample of London youths. In summarizing the U.S. literature re- viewed here, it appears that socioeconomic status is weakly correlated with participa- tion in offending based on official records. However, few of the U.S. studies were based on large, recently selected samples that display substantial variation in social class. In contrast, British studies generally show a strong correlation between partici- pation and various measures of social class. The two U.S. studies that found a relation- ship between social class and participation for serious crime types controlled for two of the characteristics that are related to socio- economic status, race and measured IQ. When participation is measured by self- reports of serious offenses, similar relation- ships emerge, but the relevant data are

264 limited. Divergence in results between some self-report studies and the official- record studies may reflect socioeconomic correlates of criminal justice system behav- ior and record-keeping practices, especially with respect to less serious offenses, socio- economic differentials in respondent coop- erativeness or recall during interviews, the broacler spectrum of delinquent acts in- clucled in most sel£report data, or some combination of these effects. Some findings of a relationship between "crime" ant! so- cial class in other literature may confound effects of social class on participation and on individual frequency. Measures of criminal activity that incorporate both of these di- mensions of the criminal career (e.g., mean scores of scales with values 0, 1, 2, 3 + ~ may account for some of the inconsistent results in the research on social class and crime. Family Structure and Disruptions Table 11 summarizes results relating par- ticipation in offending to family size, struc- ture, and disruptions. According to West (1969:73), "investigators all agree . . . that families with a large number of children contribute a disproportionately large num- ber of juvenile delinquents." This state- ment is consistent with findings from stud- ies summarized in Table 11. On the basis of family size at subject's age 15, Wadsworth (1979) reported that participation among children win one or two siblings only slightly exceedecl participation among chil- dren with no siblings (9.1 and 10.0, respec tively) but that participation among on- spring in families of four or more increased substantially to 24.3. Similarly, Farrington (1983a) reported participation rates nearly twice as high among sons of"large" families as among sons of"o~er" families.9 Explanations for the correlation between 9"Large" family size and "other" were not explic- itly defined in this study. Few U.S. studies have examined the relationship between family size and participation in offending. Those that have (e.g., Nye, 1958; Hirschi, 1969) used composite indices of criminal activity that were dominated by trivial offenses. CRIMINAL CAREERS AND CAREER CRIMINALS participation and family size have included overcrowding and the low standard of living associated with large low-income families (see, e.g., Butter and Giller, 1984: 186~. Wadsworth (1979:42) suggests that inher- ited characteristics associated with criminal behavior (e.g., low intelligence, low birth weight) may be more common in large fam- ilies. Nye (1958) suggests that direct control of children is more difficult in large fami- lies, a situation that may hamper parental supervision and could! delay learning to inhibit antisocial behavior. It could also be argued that even if par- ticipation were otherwise independent of family size, a child in a large family faces greater risk of having a delinquent sibling. Through some mechanism, such as learn- ing, peer association, adverse labeling of the family, or family stress created by one sibling's delinquency, participation in of- fending among the other children might be indirectly increased. One study summa- rized in Table 13 is consistent with this hypothesis, though the analysis is based on a very small sample (Robins, West, and Heganic, 1975~. Among male children with no delinquent siblings, participation was virtually identical for boys with one or two siblings (21 percent) and boys with three or four siblings (20 percent). Among boys with one or more delinquent siblings, participa- tion was about three times as high, regard- less of whether the total number of siblings was one or two (69.2) or three or four (57.1~. Similarly, the data for females show partic- ipation rates to be relatively independent of family size but adversely affected by the presence of a delinquent sibling. However, further research with larger and more rep- resentative samples is needed to partition the effects on participation of family size from those of delinquent siblings. As shown in Table 11, Wadsworth (1979) reported that participation by age 21 (based on convictions) increased with further fam- ily growth after the subject's birth, and that the effect was aggravate<] by later or longer periods of growth. In a related analysis, Wadsworth reported that participation de- clined steadily as the length of time as an only child increased. He also reported that

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268 children of mothers who were married be- fore age 20 or after age 30, or who were married less than 1 year when the child was born, had higher participation rates than other children. The consistent effects of measures of fam- ily structure (e.g., family size, birth order, birth spacing) on participation suggest that these relationships have a common origin. It is likely that these family-structure vari- ables are closely associated with low socio- economic status and other adverse family conditions associated with poor housing. In one multivariate analysis of factors related to delinquency in ogler children and pre- teens (Farrington, 1983a), family size dicl not significantly affect participation, but low family income and poor housing were im- portant predictors (see also Butter ant! Gil- ler, 1984~. Four studies reviewed in Table 11 pro- vide some evidence that family breaks, es- pecially parental separation and divorce, increase participation in offending (Wads- worth, 1979; Elliott et al., 1983; Farrington, 1983a; Rankin, 1983~. For the two age groups in Table 11, Elliott et al. fount] a higher self-reported current participation rate for robbery and for index offenses among chflciren living with one natural par- ent than among children living with both. When the definition of participation was broadened] to status offenses or a general delinauenev index. the relationship per- sisted but was slightly weaker (data not shown). Rankin (1983) reanalyzed the self-report data gathered by the National Survey of Youth (Williams and Gold, 1972; Gold and Reimer, 1975) and found very small effects of family disruption on three serious of- fenses-breaking and entering, assault, and auto theft. However, contrary to Elliott et al. (1983), family disruption had a much larger effect on three types of minor clelinquen- cy running away, truancy, and fighting. Moreover, parental death and marital breakup had similar effects on running away, although less than 10 percent of the sample had experienced the death of a par A, , . . . .. . .. ent. McCord (1979) looked at the relationship CRIMINaL CAREERS AND CAREER CRIMINALS between family disruption and lifetime par- ticipation in her longitudinal study. In a series of bivariate regressions, father's ab- sence was unrelated to convictions for prop- erty crimes, but was weakly related (p = .07) to convictions for personal crimes. In other analyses, however, McCord (1982) showed that the operative factor was actu- ally family conflict and not a broken home. Men raiser] in broken homes had lower rates of participation in serious crimes than men from intact homes with conflict. Other studies have also found significant effects of family conflict on participation (see Far- rington, 1979a; Butter, 1981~. Two British stuclies, using convictions as the criterion, show strong relationships be- tween family disruption and participation. Wadsworth (1979) reported that the effect of a marital breakup on participation is more important than the death of a parent: com- pared with a participation rate of 14.2 among children of unbroken homes, (leash of the father had no effect, and death of the mother only a small one (to 19.6~. Divorce or separation nearly doubled participation by age 25, to 26.6, in his sample. Farrington (1983a) found that two types of family break-separation from a parent by age 10 or a broken home by age 15-each raiser! participation based on convictions above 50 percent, compared with participation of about 30 percent among children of unbro- ken homes. In another analysis of these data, Farrington (1979b) found family dis- ruption at age 10 related to self-reported delinquency at age 14, but not at age 18. The Wadsworth data also show clearly that family breaks before age 11 increase partic- ipation in offending, but that the magnitude of the effect declines with age at the breakup. Participation was actually lower among children who experienced the break between ages 11 and 15 (9.9) than among children of unbroken homes (14.2~.~° resee Gibson (1969) for another examination of age and family disruption, using early data from the Cambridge study. He found that age (before or after 5 years) is not important, but that controlling for other family influences affects the broken home/de- linquency relationship. Broken homes have less

APPENDIX A: PARTICIPATION IN CRIMINAL CAREERS Thus, the participation literature shows some support for the view that family breaks increase participation in crime and delinquency, but there are subtleties in the data. Divorce or separation appears to have a stronger adverse effect than death of a parent, but this is an especially difficult area to research because of the large samples needed for a reasonable sample of both delinquent youths and youths who have lost a parent. Whether family disruption affects both participation in serious offenses and "acting-out" behaviors, such as running away or truancy, cannot be answered fully with the data presented in Table 11. More- over, several studies that were not included in this review suggest that family disruption may have different effects depending on the sex, race, and age of the youth (Datesman and Scarpitti, 1975; Austin, 1978; Wilkin- son, 1980~. Future research should pay close attention to these potentially con- founding demographic factors. Finally, some researchers have argued that the rela- tionship between "broken homes" and of- ficial delinquency is spurious, reflecting differential treatment in the juvenile justice system (e.g., Rankin, 1983~. However, Far- rington (1979b) reported that family disrup- tion was related to both self-reported delin- quency and official records of conviction. Other researchers with the appropriate data should examine associations between vari- ous types of family disruptions and the self- report and official-record measures of delin- quency (e.g., Elliott et al., 1983; Rankin, 1983~. Other Family Influences Several of the studies reviewed here re- port strong empirical associations between participation and various aspects of behav- ior by family members that affects the sampled individuals, including parental be- havior, parent-child relationships, and anti- social behavior by parents and grandpar effect on socially disadvantaged families than on families without social disadvantages (e.g., poor housing, large family, low income). 269 ents. However, rarely was a specific parental characteristic associated with par- ticipation much above 50 percent. The anal- yses are summarized in Table 12. Farrington (1983a) contrasted participa- tion based on convictions by age 25 be- tween subjects whose parents fell into the "most adverse" quartile and other subjects, according to interviewers' ratings of various parental behaviors. As shown in Table 12, the strongest contrasts were found with re- spect to ratings of supervision and an over- all index of parental behavior when the child was 8. In multivariate analyses, the parental behavior index was also signifi- cantly correlated with participation be- tween ages 10 and 13, controlling for IQ, poor housing, and other family and subject characteristics. The weakest correlates in- vestigated by Farrington, nervousness in the father and attitude, still differentiated the two groups, but were not statistically significant. Farrington also reported a strong relationship between participation and the rated quality of the subject's rela- tionship with his parents: participation was higher among those with poor parental re- lations (46.5) than among others (30.2~. Farrington also looked at the effect of parental employment on official delin- quency. Youths whose fathers had erratic employment were much more likely to have an official record of conviction by age 25 (53.2) than other youths (30.3~. However, youths whose mothers worked full time were no more likely to be convicted than youths whose mothers did not work or only worked part time. The effect of father's employment probably reflects its correla- tion with low social class, low family in- come, and poor housing. Wadsworth (1979) reported that participa- tion by age 15 declines dramatically as teacher ratings of parental interest in school progress increase. Similarly, McCord (1979) found that such parental attributes as qual- ity of supervision, mother's affection and self-confidence, father's deviance and ab- sence, and parental conflict and aggression all correlated with lifetime participation in property ancl/or personal crime. Other recent studies and reviews of the .. . ..

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APPENDIX a PARTICIPATION IN CRIMINAL CAREERS effects of family influences (other than family criminality) on conduct disturbances and minor delinquency in young children and later criminal behavior have also pointed to the strong adverse effects of poor supervision, passive attitudes, and ineffec- tive discipline (Patterson, 1982; Hirschi, 273 pected, in the sense that parental and granclparental antisocial behavior showed similar association with participation. Family Members' Criminal Behavior ~ ups; Butter and Giller, 1984: 18~188~. Six studies reviewed here present data on Thus, the findings in Table 12 relating the participation among offspring of criminal behavior of parents to participation in of- and noncriminal parents (Robins and fending by their offspring appear consistent Lewis, 1966; Robins, West, and Herjanic with the larger literature relating parental 1975; Farrington, 1983a; Hutchings and behavior to other measures of criminality Mednick, 1975; McCord, 1977; and among children. (For a review of studies re- Mednick, Gabrielli, and Hutchings, 1984~. rating nonclelinquent disturbances of conduct These are summarized in Table 13. to family functioning, see Butter, 1977; With one exception, the six studies con Hinde, 1980, Patterson, 1980; Loeber, 1985.) sistently show a positive association be The other studies inclucled in Table 12 tween criminal participation by parents and examined the relationship between partici- by their offspring. The lone exception ap pation and antisocial behavior by both par- - - ents and grandparents. Robins and Lewis (1966) studied participation among the 67 offspring of subjects of the earlier follow-up of patients of a chilcl guidance clinic. The offsprings' participation, as measurer! by ar rest, was correlated with reports of both their parents' and grandparents' antisocial or deviant behavior (e.g., arrests, excessive drinking, poor work record, desertion, ne glect, cruelty, gambling, and extramarital relations). As expected, antisocial behavior in earlier generations had a strong positive as s ociation with participation. M ore s urpri s ing is that the magnitude of the effect ap peared greater for antisocial behavior by the subject's grandparents than by the parents. Unfortunately, the small sample size pre vented Robins ant] Lewis from testing the grandparents' influence while controlling for antisocial behavior by aunts and uncles. Thus, it is possible that the influence was indirect, through antisocial behavior and perhaps marriage to an antisocial partner by the grandparents' offspring. A similar three-generation study (Robins, West, and Hispanic, 1975) examined partic ipation among the offspring of 223 black males followed in an earlier study (Robins and Wish, 1977~. The sample is probably atypical, however, because no male or fe male subject without an antisocial parent was arrested by age 18. However, as shown in Table 12, the results were more as ex pears in Robins and Lewis (1966:504), who found lower participation by age 18 among sons of delinquent patients of a child guicI- ance clinic (17.1) than among sons of nondelinquent patients (21.9), but the dif- ference is probably not statistically signifi- cant. In another sample, Robins, West, ant] tierJanic (1975) found the expected rela- tionship between parents' and children's participation; the effect was greatest in fam- ilies in which the mother (or both parents) was arrested, and slightly lower when only the father was arrested. The association with the children's participation was found to hold for both parental delinquency and criminality as adults. Similarly, Farrington (1983a) reported that conviction of at least one parent before age 10 dramatically increased the probabil- ity of subsequent conviction of the son. In addition, in the same study, a convicted sibling before age 10 had an equally strong effect on participation as measured by a conviction before age 25. These two mea- sures of family members' criminal behavior were also significantly relatecl to conviction at two earlier ages in multivariate analyses that controlled for earlier delinquent behav- ior and other personal characteristics. These findings support the previous results of Robins, West, and Herjanic (1975), who found that participation was higher for indi- viduals with delinquent siblings. McCord (1977) also had data on fathers

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APPENDIX A: PARTICIPATION IN CRIMINAL CAREERS criminal behavior for her sample of men who had participated in the Cambridge- Somerville youth study. Although participa- tion rates cannot be computed from the published data, McCord reported that fa- thers who were convicted of either assault or larceny were significantly more likely than other fathers to have sons who were convicted! of those crimes. A similar rela- tionship existed for drunkenness and other minor, nontragic crimes. Hutchings and Mednick (1975) presented several sets of statistics on participation among samples of adoptees and their bio- logical and adoptive parents. The data were intended to isolate participation influences that are interpreted as genetic (e.g., crimi- nality in the biological parents) from rela- tionships that are primarily environmental (e.g., criminality in the adoptive parents). Their statistics were based on the criminal records as of 1971 for 1,145 males born in Copenhagen, Denmark, between 1927 and 1941 and subsequently adoptecI. Compar- ative statistics were also presented for 1,120 nonaclopted controls, matched for sex, age, father's occupation, and place of resi- dence. From the data reported by Hutchings ant] Mecinick, it is possible to contrast three pairs of participation rates: for adopted sons conditional on criminal activity of their bi- ological and adoptecl-fathers and for non- adoptec] controls conditional on their natu- ral fathers' criminality. These contrasts are reported in Table 13. With respect to minor crimes, participation among adopted sons was only marginally associates] with crimi- nality in the parent generation in all three contrasts. With respect to serious crimes, participation was 8 percent for nonadopted sons with noncriminal fathers and 16 per- cent for those with criminal fathers. For acloptec] sons, participation was 14 percent if the adoptive father was noncriminal but 27 percent if he was criminal. A smaller participation clifferential was related to criminality of the adoptees' biological fa- thers: 14 percent if the biological father was noncriminal, but 27 percent if he was crim- inal. The association with the biological father's criminality was interpreter] by the 277 authors as evidence of a partially genetic influence on participation. In the same study, Hutchings and Mednick reported results of a "cross-foster- ing" analysis of participation, controlling simultaneously for criminality of the adop- tive and biological father. As shown in Ta- ble 13, the statistics, which were based on 662 acloptees selected in an unspecified] way from the original 1,145, show an in- crease in participation from 10 percent when both the adoptive and biological fa- thers were noncriminal, to 12 percent when only the adoptive father was criminal, to 21 percent when only the biological father was criminal, and to 36 percent when both were crlmlna . In assessing the results, the authors noted that because of adoption agency policy, the social classes of the biological and adoptive fathers were correlated. Therefore, as noted by Robins (1975), adoption studies (lo not completely separate genetic and environ- mental influences on participation. How- ever, in a later analysis of an expanded Danish adoptee cohort, Van Dusen et al. (1983) found a correlation of only .14 be- tween the social classes of the biological and adoptive parents as defined by occupa- tion; they also found that participation was related independently to the social classes of both sets of parents, with higher partici- pation among children of lower class par- ents. Two characteristics of the Hutchings ant! Mednick work may have affected its valid- ity as a test of genetic influences on partic- ipation. First, while only a negligible frac- tion of the adoptive fathers could not be located, about 15 percent of the biological fathers could not be found. If criminal par- ticipation levels differ between the biolog- ical fathers who were and were not located, the relationship between their participation and that oftheir sons would be overstated or understated, clepending on the direction of the difference. Second, the data base did not include any information on the crimi- nality of either the biological or adoptive mothers, and so the description of intergen- erational transmission of criminality is in- complete.

278 In a later study, Mednick, Gabrielli, and Hutchings (1984) presented participation results based on 14,427 adoptions, appar- ently all that occurred in Denmark between 1927 and 1947. As shown in Table 13, among all parties involved in the adoptions, participation was highest among the biolog- ical parents, followed by the adopters. Par- ticipation was lowest among the adoptive parents, who were presumably screened to prevent known offenders from adopting children. The following "cross-fostering" results were also reported: If neither the biological nor the adoptive parents are convicted, 13.5 percent of the sons are con- victed. If the adoptive parents are convicted and Me biological parents are not, this figure rises only to 14.7 percent. However, if the adoptive parents are not convicted and We biological par- ents are, 20.0 percent ofthe sons are convicted. If We adoptive parents as well as the biological parents are convicted, 24.5 percent of the sons are convicted (p. 2241. It is not clear whether conviction of one set of parents is intended to refer to at least one member of the set or to both members, and no data were presented to support a later assertion that participation among the olI- spring was associated more closely with the mother's conviction than the father's. The study also included a graph relating conviction participation among adopted sons to the number of convictions of the biological parent. The numbers, as read from the graph, suggest a strong tendency for participation in property crimes to rise with the number of parental convictions (Table 13~. A slight tendency in the same direction is apparent for violent crimes, al- though parental age was not controlled. However, because of the time required to accumulate multiple convictions, the par- ents with three or more convictions may have been older than the parents with none or one conviction. Because participation in- creases with age, age-controlled statistics are necessary to isolate genetic influences. The qualifications expressed above con- ceming the earlier cross-fostering analysis are also applicable here. In particular, 36 percent of the biological fathers and 17 percent of the biological mothers could not . . . CRIMINAL CAREERS AND CAREER CRIMINALS be located. No information or even specu- lation was offered concerning characteris- tics of those parents; the authors said only that the "sons of parents not fully identified have levels of criminal law convictions and rearing social status that are approximately the same as for the sons of those parents twho were] fully identified" (p. 8931. The authors also reported a statistically . . . significant association between participa- tion among male adoptees and time in the orphanage awaiting adoption (51 percent were placed in the first year and 89 percent were placed before age 2~. They suggest that this association may be explained by institutionalization effects or a bias toward later adoption of less desirable boys, who are eventually convicted at above-average rates. If the duration of institutionalization was longer for the sons of criminals than for other children, the association would lead to an overstatement of the relationship be- tween participation levels in the two gener- ations. But the study did not test this asso- ciation. The observed association between the biological fathers' and sons' participation could potentially be explained by nonge- netic relationships between the two gener- ations that involve correlates of participa- tion. For example, Mednick, Gabrielli, and Hutchings (1984) reported that the children's participation was related to the duration of institutionalization prior to adoption. If the duration was also related to the father's criminality (e.g., because crimi- nals' children are systematically rejected as less desirable than other children), that re- lationship would contribute to the associa- tion between participation indicators in the two generations. Similarly, Kamin (1985) suggested that in attempting to place chil- dren in adoptive homes that resembled their natural homes, adoption workers may have unknowingly invoked criminogenic family characteristics that did not appear in the n~rm~n~?nt records available to Med- nick and associates. Moses (1985) noted that a monotonic increasing or decreasing trend in participation over successive cohorts of fathers and sons could cause the observed association. However, Mednick, Gabrielli,

APPENDIX A: PARTICIPATION IN CRIMINAL CAREERS and Hutchings (1985) replied that Kamin's "criminogenic placement" effect was un- likely under adoption agency procedures as of the relevant period. They also argued that the reported associations occurred even when separate analyses were performed for subcohorts, each of which involved a time span too short to reflect long-term participa- tion trends. To summarize, studies of family influ- ences show clearly that, in unbroken fami- lies, participation among offspring is in- creased if the parents or siblings have official criminal records. Thus, the literature reviewed here is consistent with a major recent review of the correlates of delin- quency (Rutter and Giller, 1984:182), which stated that "of the parental characteristics associated with delinquency, criminality is the most striking and consistent." More- over, this association exists even when the children are separated from their biological parents because of adoption. This pattern is consistent with theories of participation that invoke inherited characteristics; however, further research is needed to eliminate rival explanations and to assess the consistency of the pattern in locations outside Denmark. Early Antisocial Behavior Of the participation studies reviewed for this paper, eight present analyses of the relationship between early antisocial be- havior and participation in offending. Those studies are actually a small part of the vast literature relating childhood behavioral problems to later deviant behavior (see Loeber, 1982; Loeber and Dishion, 1983; Butter and Giller, 1984:Chapter 21. Most of the larger literature, however, does not fo- cus on participation in sermons delinquency or criminal activity as the criterion. Never- theless, the data presented in Table 14 are consistent with this larger literature and clearly show that indicators of early antiso- cial behavior are related to later criminal activity, as measured by official records. These results are summarized in Table 14. In Table 14, the results from Feldhusen, Thurston, and Benning (1973) show that relative to children rated "social" by their 279 teachers, participation based on police rec- ords was twice as high among children earlier rated "aggressive/disruptive," and participation based on court convictions was eight times as high. Prospective dis- criminatory power of other teacher ratings ("good" versus "potentially delinquent") is also shown by Reckless, Dinitz, and Kay (1957~. The average age of their subjects when the study began was 12 years. Two British studies also tested the pre- dictive~ power of teacher ratings of child- hood antisocial behavior on officially re- corded participation by early adulthood. In both samples, the subjects were about 10 years old. Mitchell and Rosa (1981) used the more restrictive participation measure (con- victions), and the teacher's index was most strongly associated with theft offenses. Compared with others in the sample, more than twice as many children who were rated in the most adverse group had a con- viction by age 25 for theft. Violent offenses were less well predicted by the teacher ratings. Ouston (1984) reported participa- tion rates by age 18 for youth earlier classi- fied as "neurotic," "anti-social," "mixed," or "average." Both male and female chil- dren with the antisocial ratings had the highest participation rates. However, the "average" male children had higher rates than the children rated "mixed." For fe- males, the average group did have the low- est participation rates. Robins (1966) combined the samples of St. Louis child guidance patients with a control group and assessed the relationship between referral and lifetime participation. On the basis of all nontragic arrests, the referred males were three times more likely to have an arrest than those not referred; the relationship was even stronger for females. When only index offenses are considered, none of the nonreferred males or females had adult arrests; in contrast, 30 percent of referred males and 5 percent of referred females had index arrests as adults. How- ever, this finding should be interpreted cau- tiously because the sample of nonreferred children was small and index arrests are relatively rare among general samples. To explore developmental sequences

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282 culminating in delinquency, Robins and Wish (1977) employed an actuarial tech- nique developed by Robins and Taibleson (1972~. Designed explicitly to exploit the power of longitudinal data bases on individ- uals, the technique searches for chains of hypothesized causal links, restricting the search to causes occurring before their hy- pothesized effects, and adjusting for the longer exposure period that follows "causes" that occur at earlier ages. Using this technique, they found no empirical link between Bit and alcohol use or sexual ac- tivity by age 15, failure in elementary school, or leaving home before age 18. In separate analyses, they found participation increased with marijuana use, excessive el- ementary school absences, and school drop- out by age 15. However, the effect of school dropout disappeared when the other behav- iors were controlled simultaneously. Using ratings of various characteristics, Farrington (1983a) compared cumulative participation by age 25 between the "most adverse quartile" of the Cambridge sample and the rest of the sample. Of the character- istics tested, the following showed the greatest discriminatory power with respect to participation: "troublesomeness" at ages ~10, daring at ages ~10, truancy at ages 1~14, aggressiveness at ages 1~14, hostile attitudes toward police at age 14, and anti- establishment attitudes at age 18. Of sample members ranking in the most adverse quartile on each of these attributes sepa- rately, more than half were convicted of an indictable offense by age 25. In similar comparisons, proaggression and prodrug at- titudes at age 18 showed less discriminatory power, and "neurotic extroversion" at ages 10 and 14 showed virtually none. Nervous- ness showed an inconsistent relationship: conviction by age 25 was actually less prev- alent among the most nervous quartile of 8-year-olds than among other 8-year-olds. However, the relationship was reversed when measurements of nervousness at age 14 were used. Wadsworth (1979:95-97) presents a sum- mary discussion relating early antisocial be- havior to participation among male youths. He reported no consistent relationships be ,, . . . CRIMINAL CAREERS AND CAREER CRIMINALS tween participation and parental reports of aggressiveness, bed-wetting, or referral to a child guidance clinic. He did report a rela- tionship to the Pintner and Maudsley per- sonality tests, symptoms such as stammer- ing and tics at age 15, and truancy. He found cheating on schoolwork a correlate of par- ticipation in minor crimes, and he reported greater participation in sex offenses among boys experiencing late puberty. In summary, the studies reviewed here show that later participation increases with the emergence of early antisocial behavior as observed by parents, teachers, and peers. However, even among the highest risk groups identified in these studies, participa- tion in subsequent offending does not ex- ceed 65 percent. Thus, this literature leaves unanswered the question of why the antiso- cial behavior patterns of many children and adolescents terminate short of officially re- corded delinquency and adult arrest. School Performance and Intelligence Nine of the studies reviewed report that poor school performance and low intelli- gence are associated with higher participa- tion. The results of these studies are sum- marized in Table 15, except those of Reiss and Rhodes (1961), which are summarized in Table 10. Wolfgang, Figlio, and Sellin (1972:63) found a nearly monotonic, increasing rela- tionship between participation and a school-achievement scale, for both blacks and whites in Philadelphia cohort I. Among the two lowest achievement categories, par- ticipation among black males exceeded 50 percent, and the black-white differential was large. The race differential nearly dis- appeared among the highest category of achievers. In an early study, Polk, Frease, and Rich- mond (1974) reported that for sons of both blue-collar and white-collar families, a bet- ter high school grade-point average was related to lower participation, based on ju- venile court records. Also, Palmore and Hammond (1964) report lower officially re- corded participation for both black and white high school students with averages of

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285 ) U] ~ ·'= ~ · - ~ ·'Q O Q 03 ~ ~ ~ S Q ~Q a, 0 0 ~ ~a) 0 0 in _1 _I ~ 1 _I _ ~ O - ~ ~ ~ ~ U] m~ ~ O lo- - O ~-~1 ~ IS ~ aY 0 ~ in ~ BY O ~ 1 O ~ S- - ~ ~O C) be:- - O ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ O _ Q n' ~ ~ ~ ~_Q + + _ _ ~ ~ us us O ran ao ~ IU] ~ ~ ~ ~U] ~ o ~ Cot ~ · ~ ~ ~ ~ ~ ~ ~ ~T o o o o or o o o o 1 1 1 1 1 1 1 ~ ~ ~ ~ t9 U~ o cn ~ 0 d~ C ~U) ~ C~ ~ ~ ~ · ~ ~ ~ ~ ~ ~ ~ ~r 0=== mr 0=== 11 1 1 1 1 1 1 ~n en u~ u a) a ~n ~ ~u, tQ a ~ ~o ~ ~ a) ~ a, ~ .Y a., ~ C.~= ·~ ~{~ ~·- m~- s ~s ~s - 5: 3m~m :~m3 m 8 0 s u' ~ ~- t) ~ eQ u, ~ 0 ~ m~ um ~ ~ _ ·~1 N m l ~. - u, u, - · - ~ = - G' ~ o- ~ ~ ~10 O ~ eQ ~ ~ a, ~ ~a.) ~ ~ u, 0 [Q eq ~ a, s ~ a) ~ ~ 0 U] ~ ~ ~ 3 · - ~ . - ~ ~ 0 cn~ ~ 4' O'~ ~ ~ mlu' C ~C~ _ 00 a' - ~, .,' S V U] ~ a) s~ . - =- - ~ :~: .,' :n tQ ·,' o ~r: - .,' ·,' C) V .,' .,' S 'CQ o a, a) ·,' S o ~Q o u] u] o .-l · - ~: ~1 .

286 C or better compared with students with lower averages. Similar to the Philadelphia results, black youths in the lower achieve- ment category had participation rates above 50 percent. In the study of a high-risk sample of children referred to a guidance clinic, Rob- ins, Gyman, and O'Neal (1962) found that having at least one juvenile court appear- ance by age 18 was much lower for youths who graduated from high school (9.1 per- cent) than for youths who left school before grade nine (74.2 percent). (For further evi- dence that school failure may be a precursor of delinquency, see Havighurst etal., 1962.) In a larger study, Reiss and Rhodes (1961) reported an inverse relationship between measured IQ and officially recorded partic- ipation among children of white-collar and blue-collar parents (see Table 10), but they did not control for school achievement. Three British studies examine the rela- tionship between school performance/intel- ligence and participation, also based on official records. Wadsworth (1979) reported that higher teacher ratings of pupil dili- gence at age 10 were associated with a lower rate of conviction for an indictable offense by age 15. In a series of compari- sons, Farrington (1983a) found participation by age 25 adversely affected by low IQ, limited vocabulary, and leaving school at an early age. Moreover, in his multivariate analysis of factors predicting at least one conviction between the ages of 10 and 13, IQ at ages 8-10 had a significant effect independently of antisocial behavior and parental characteristics. Ouston's (1984) study of another London sample found that standardized reading and IQ scores at age 10 were clearly related to participation rates, based on police and court records. As would be expected, in a similar analysis with test scores taken at age 14, these same measures were slightly more predictive of later delinquency. Last, Hindelang, Hirschi, and Weis (1981) examined the association between officially recorded and self-reported partic- ipation and grouped values of school grades and general-knowledge test scores. For white males and females of both races, they CRIMINAL CAREERS AND CAREER CRIMINALS reported gamma statistics demonstrating the expected relationship. For black males, the associations were statistically insignifi- cant and, for the general-knowledge mea- sure, in the "wrong" direction. However, the authors expressed strong doubt con- cerning the validity of the grades and self- report data for this group. Taken as a body, the participation litera- ture indicates that regardless of race and social class, higher school achievement is associated with a lower participation level. (See also discussions in Gordon, 1976; Hirschi and Hindelang, 1977; Butter and Giller, 1984.) However, school achieve- ment and low intelligence appear to be closely intertwined and further research is needed to sort out their relationship to par- ticipation. Miscellaneous Attributes Researchers have also examined the rela- tionship of participation in offending to var- ious other characteristics, such as legitimate activities, psychiatric diagnosis, physical at- tributes, and peer involvement. Because these relationships have been studied using a variety of methodologies, the studies sum- marized in Table 16 should be considered only a small, possibly unrepresentative, portion of the relevant research. As shown in Table 16, Elliott et al. (1983) found that in the early years of their study, youths employed full-time reported higher levels of current participation than nonem- ployed respondents. However, in later years, the participation difference between full-time employed and nonemployed re- spondents essentially disappeared. Because the respondents were aged 11-17 at the time the study began, the data may reflect a maturation process, as employment is trans- formed from a source of freedom from pa- rental controls to an adult activity tying the individual to society. Both Farrington (1983a) and Viscusi (1983) reported a strong positive relationship between participation and an unstable job record or low job status in early adulthood (ages 18-19), which is consistent with the trend in Elliott et al.'s data. Viscusi studied over 2,000 young

APPENDIX a PARTICIPATION IN CRIMINAL CAREERS black men from Philadelphia, Boston, and Chicago and found that for a variety of criminal behaviors, currently unemployed men reported higher participation rates than employed men. This relationship per- sisted even when controls were introduced for drug use and criminal history variables. Farrington's unemployment measure was also a significant predictor of conviction between ages 21-24, even controlling for convictions at earlier ages and low family income during childhood. Farrington (1983a) also examined the as- sociation between conviction by age 25 and involvement with delinquent peers and drug use. Not surprisingly, Farrington re- ported greater participation among those who reported involvement with negative peers (not further defined) around age 14 (59.2 percent) than among other youths (25.3 percent). Drug use was also a signifi- cant factor influencing participation by young adults in this London sample and in the study by Viscusi (1983~. Robins (1966) reported extremely high paruc~pation rates among adults diagnosed as sociopaths. However, this finding does not necessarily indicate a causal relation- ship because arrest was 1 of 19 factors used in making the diagnosis and was the third most common in this sample. The results of Farrington (1983a) that bear on the relationship between participa- tion and physical attributes are also summa- rized in Table 16. The vast majority of studies of physical correlates of criminal activity have been conducted by comparing samples of incarcerated criminals with sam- ples of presumed noncriminals in terms of the attributes of interest. Because such stud- ies confound relationships involving both participation and frequency (A), they were not reviewed here. The reader is referred to Mednick et al. (1982) and to Wilson and Herrnstein (1985) for more comprehensive reviews of that literature. Farrington (1983a) reported higherpartic- ipation among boys who were rated clum- siest, shortest, and lightest in weight at ages 8-10. However, the participation differen- tials were slight with respect to size mea- surements taken at that age, and were non 287 existent with respect to remeasurements at ages 14 and 18. Wadsworth (1979:99) re- ported similar body-size effects, but ob- served that they were eliminated when so- cial class and birth-order effects were statistically controlled. (Tabular data were not reported.) One physical attribute, low pulse rate, is considered a measurable indicator of an undersensitive autonomic nervous system, which has been hypothesized to be associ- ated with higher rates of participation (see Wadsworth, 19761. As shown in Table 16. Farrington reported a weak relationship be- tween low pulse rates at age 18 and convic- tions by age 25. Wadsworth (1976:249) ob- served no difference in pulse rate at age 8 in a mildly threatening situation among mem- bers of his sample who were and were not eventually convicted. However, those con- victed of violent or sexual offenses exhib- ited si~nificantlv lower oulse rates an ob ~. ~ V ~ ~ 7 servation consistent with the theory. CONCLUSION Perhaps the most striking finding about criminal participation is the pervasiveness of involvement in serious crimes. The best available estimates suggest that 25~35 per- cent of urban males will be arrested for at least one index offense in their lives, and 15 percent will be arrested before reaching age 18. There are systematic demographic pat- terns of participation in serious crime: males are more widely involved than fe- males, and blacks more than whites; also, the majority of criminals begin their careers before reaching their early 20s. But demo- graphic participation patterns offer little policy guidance, because they are too broad to offer a basis for decision making, because their interpretations are ambiguous, and be- cause basic social values would be affronted by decision rules that invoked demographic characteristics . Other family and individual characteris- tics related to participation are of more in- terest to scholars and policy makers. The family influences most consistently found to be associated with higher levels of partici- pation in serious crime include:

288 o o .,' .,' U] o ~ · - v . - ~4 a) a: o . - . - v .,1 Q .,, - a, v a) - ~Q to a) ee Q O .,, a, a, 0 V s U] ~ .,' a, ~£ At: EN U] ·' to ~ a) O ~ Q . - v o U] U] en up A a) ~ ~ a) 54 a ~ a O a · - U1 a o v a a a) ~: o s o v v V a) al s~ U] o 1 - · - - _ ~ O · - a O ~ O O V ~ o o Io o o oo o o C0 · · ·e · C~ ~ _I C~ O 1D a~ 0 0 00 0 0 · ~ .... d' ~ ~ O ~ - ~ 0o O O O O O O ~ · · · · · e er ~ d. ~ ~ O ~ O O O 0 00 t- · ~ . ... d' ~ ~ ~ ~ ~ I_~ _~ ~· · _ ~ _ _ a' ~+ + 1 + O O O O O Od' ~- --- ~ · ~ . ... a' ~ u~ ~co ~ C~ · ~ U~ U, ~U] ~ U1 a, ~ ~ ~ m o -.- o -.- ~ ~o ~ 8 ~ JJ s ~ ~ ~ V ms ~a o H V · - _ _ u, ~n _ a' _ C0 - ~ ~x ~a Q ~·' ·' a Q ~e ~u, - ~ - o, O ~ ~ ~_ ~ ~ ·' ~0 ~ ~0 - a, _ ~_ _ ~m. - ~ _ m. - a) U] a, ~= a, ~~ ~·- ~ ~ ~1 ~=1 ~ ~1 ~ ~ ~1 ~=1 ~ ~Q a) 0 a) ~ 0 ~ ~ ~ ~ ~ 1 a, ,1 ~ ~m~ ~ O ~ ~ O Ql ~ - ~ V O o ° O ~ ~O - C) C) ~C) O - . _ ~ ~_ co O .,, ,~, ~ ~V ~a) - ~' - u' -

289 C~ · - 0 .,, a~ ~n o o · - ~n ~ · - o ~o o o .. JJ U] U] U] o a o · - s - a) s o · - z ~q s o .,, o tn o o o o · · · ~ a' ~ c~ ~ Io o o o · · ~ ~ ~ ao ~ ~ c U] a U] o £ ~: ~ ~ o ~ ~ o ~ ~ · · · ~ ~ e · O ~ ~ ~ ~ O ~ CO · · ~ · · · ~ o0 ~ ~ M° O er O O O . . _I _ o u ~_ 1 __ ~ ~ _ ~ O O ~ - _ 0 ~1 ~ ~ _ _ _ c'` {Q 1 1 ~ ~ ~ a' O ~n s In ~- u~ oo co , aJ . - ~ '~ t~ a) -_ _ _ _ _ ,-1 U] ~ - Q O Q' - O · - ~ ~ o ~ ~rn s s s s s s ·'l a,) _I JJ eq s ~ ~ s ~ ~ ·~ - ~ ~ ·~ - ·- 0 ~ ~ 0 ~ ~ ~ ~ ~ a O ~ u' o ~o (' :~ :~: ~ :~3 O tQ ~ _ C, O-,l ~n ·' (V ·' ^ ~, tQ ~_ ~ ~ ~ ~ ~s O ~· - o U] ~ ~ U1- - ~ ~·' ~ ~ = - ~ ~ O a) ~,~ ~ . - ~= ~ ~ m t) ~ml~ ~ u, mlo ·,l >, ~u, ·,l O · - V Q u, aJ ~ o ~ ~ s ~ ~ ~ ~ ~ · - O Q. ~ ~ ~ ~ ~ ~ O ~= V ~ ~ ~ ~ ·~= ~o s == O O O C) {: O - O _ ·-l ~ ~ ·^ ~ ~· - ~, _ Q _ ~, _ O P~

290 · inadequate parenting, in the form of inconsistent or sporadically violent disci- pline, poor parent-child communication, and poor supervision; · parental delinquency and cr~m~na~ty; · parental discord and family breakups; and · some indicators of low socioeconomic family status, such as low income and poor housing. High rates of delinquency participation have been found consistently for children exhibiting the following behaviors at an early age: · antisocial behaviors, such as aggres- siveness, fighting, and lying; and · poor school performance. Some studies suggest that certain factors measured in the mid-teen years are empir- ically related to participation, although they do not necessarily precede initiation of the criminal career. These include: · association with delinquent peers; · abuse of hard drugs; · employment status, which may have different effects for juveniles and adults; and · large family size. These family and individual characteris- tics will be familiar to many readers as "causes of crime" that have been discov- ered and supported in large bodies of em- pirical research. However, much of that research has measured crime in ways that reduce distinct career dimensions partici- pation, offending frequency, diversity and seriousness in crime types, and duration to a single number. By limiting attention to research in which the various career dimen- sions can be partitioned, this review and that of Cohen (Appendix B) attempt to iso- late the separate relationships between in- dividual and family characteristics and the respective career dimensions. Even though the associations just listed emerge consistently in the participation lit- erature, two limitations should be noted. First, while the empirical relationships re- ported here provide prospective indicators CRIMINaL CAREERS AND CAREER CRIMINALS of increased participation risk, predictions based on them will produce substantial er- ror rates because, generally, at least 40 per- cent of the individuals presenting any risk factor do not become offenders, as mea- sured by arrest before age 18. Some gains in accuracy could probably be achieved using scales that combine multiple characteristics associated with participation risk. But the magnitude of those gains may be disap- pointing because the risk factors do not occur independently of one another. One relatively unexplored approach to improv- ing predictive accuracy is the search for specific stressful events associated with the initiation of criminal careers, such as school failure or a family death. These events may alter base participation rates from the levels that would have been expected on the basis of demographic characteristics and other risk factors. Second, caution is essential in assuming that relationships observed in one time and place are applicable to others. Associations involving B18 in Philadelphia cohort I, for example, describe behavior occurring by 1963 at the latest; major changes in demography, social norms, and social pro- grams since that time may well have made those associations inapplicable today. Sim- ilarly, differences between Britain and the United States suggest caution in assuming that relationships observed in one of the countries would apply in the other. Conse- quently, there is a clear need to develop new U.S. data bases that describe individu- als' career initiation and participation be- havior as well as their pertinent character- istics and experiences, as of the present time. New data bases would be especially helpful in resolving unanswered questions about criminal participation if Hey were designed to facilitate synthesis of official records and self-reports of illegal activity and contacts with the criminal justice sys- tem. To maintain both the chronological accuracy and richness of detail needed to merge information on event sequences, such data bases should be developed longi- tudinally. A longitudinal design would in- clude periodic reinterviews of subjects to

APPENDIX A: PARTICIPATION IN CRIMINAL CAREERS gather incident reports concerning their il- legal activity and police contacts, as well as other relevant information. It would also include recurrent searches for official rec- orcis of the subjects' criminal and juvenile justice system contacts. With carefully de- signed samples, such data bases would be useful in resolving some contradictions be 29] tween the official-record and self-report par- ticipation literatures (especially those con- cerning the roles of race and social class), in facilitating more crime-specific participa- tion research, in clarifying patterns of cur- rent participation, and in understanding the influences of specific events and interven- tions on participation.

Next: Appendix B: Research on Criminal Careers: Individual Frequency Rates and Offense Seriousness »
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By focusing attention on individuals rather than on aggregates, this book takes a novel approach to studying criminal behavior. It develops a framework for collecting information about individual criminal careers and their parameters, reviews existing knowledge about criminal career dimensions, presents models of offending patterns, and describes how criminal career information can be used to develop and refine criminal justice policies. In addition, an agenda for future research on criminal careers is presented.

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