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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

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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, selreported 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

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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

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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.

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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.

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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

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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

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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 selreports 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_. ~,,~ ~,,= ~.~

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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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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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284 o ~ o .,' .,, s o .,, ~ rl P: - a) v .~ - U] A a: a) o ran m A: EN - s U) ~ ~ 0 .~' marl en 0 ~ JJ a) UB - 3 O S In ~0 - - - - a) tQ S o IC0 ood' CO ~-' ~e ~ In up Infir ~ ret ~ ~ ~up ~ ~ ~e O ~ _' ~ ~ ~ r- ~ a' Lo ~ IS Cal ~ Cal . - o S a) a) a) Sit a) A: - 1 to - ~ ~ fir UP ~ ~ ~ mao Cal Cal O O ~ ~ l~ u~ ~ _I tD d' ~r d' d~ un d' a " ~O ~ O C 01 ~ O ~ ~ ~~1 U] H ~ ~1 3 a, 0 0 ~ >1 ~ t~ E ~_' ~ 3 ~tJ _ S~ tt ~ N ~ O - C o ~, o 3 ~-I Q 1 ~ ~ ~ ~ ~ ,4 O O ~O O ~ ~ - oD _I Q Q r1 0 ~ O ~ O ~ O ~ O ~ ~ ~ _-~ ~ ~ O ~ ~ I ~ o ~ I ~ ~ 8 ~ ~ ~ o Vo ~ ~ |= ~ | Z V | 0\ ~ | ~ ~ Pt ~l~ H U] ~1 ~S O ~ ~n a) 0 ~ C) O ~ ~ eq ~ _ - m ~ O ' ~ e- - O - ~_ ~.- _ Ql ~ o' eq ~ - a' ~ s _ ~ ~C ~ ~ ~ ~ ~ ~0= 0 ~ ~ ~ O =~1 ~U~-~ ~ m-- ml.- mlo ~n mlo .- ~ o -ol - ~ - a, ~ ~a, ~ c c- - ~ ~ ~ - ~ ~ 0 ~ ~ 0 ~ s ~ C C a ~ ~ ~ _ ~ ~ _. - 0 0 0 C) C) C) - ~s 0 _ _ C 0 3 ~ - 4, tQ ~ ~ ~ U] ~ _ ~ _ O

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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 .

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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

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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:

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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~

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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

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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.