Click for next page ( 32


The National Academies | 500 Fifth St. N.W. | Washington, D.C. 20001
Copyright © National Academy of Sciences. All rights reserved.
Terms of Use and Privacy Statement



Below are the first 10 and last 10 pages of uncorrected machine-read text (when available) of this chapter, followed by the top 30 algorithmically extracted key phrases from the chapter as a whole.
Intended to provide our own search engines and external engines with highly rich, chapter-representative searchable text on the opening pages of each chapter. Because it is UNCORRECTED material, please consider the following text as a useful but insufficient proxy for the authoritative book pages.

Do not use for reproduction, copying, pasting, or reading; exclusively for search engines.

OCR for page 31
Participation in Criminal Careers Efforts to develop effective crime con- tro! policies can be enhancer! by an un- derstanding of the ways in which inclivict- ual criminal behavior contributes to total crime. The panel's approach to the study of criminal behavior rests fundamentally on a criminal career paradigm of indivict- ual offending, which disaggregates the various elements of indiviclual offending into four key dimensions. This chapter summarizes the literature on one of those dimensions, the level of participation in crime and some demographic and social covariates of participation; Appendix A (Visher and Roth) ofthis report provides a detailed critical review of incliviclual stuclies.i iGordon and Gleser (1974) formally defined "prevalence of delinquency" (referred to here as participation), and resolved some of the confusion surrounding its precise definition, computation, and terminology. In a later paper, Gordon (1976) re- viewed several important studies of"prevalence" based on official-record data through the juvenile period (to age 18~. The Visher and Roth review (Appendix A) of participation in offending, on which this chapter is based, updates the review by Gordon and also includes studies of adult participation and self-reported participation. While Gordon used ra 31 Participation in offending is reflected in the fraction of a population ever com- mitting (or "doing") at least one crime before some age a (Da) or currently active during some observation period (ct). Esti- mates of participation have been derives! from self-report surveys of ofiencling in cross-section samples. Commonly, these studies present respondents with clescrip- tions of specific criminal acts that corre- spond to legal definitions of crimes. Cu- mu~ative participation (Da) is computed from responses to questions of the form "Have you ever. .. ?" Questions of the form "Within the past year, have you . . . ?" provide the basis for estimates of current participation all. Because the fraction of people who have committed any crime during the prece(ling year is smaller than the fraction who have ever committee] a crime, estimates of D obvi cial differences as a defining variable and adjusted published participation rates to reconcile differ- ences across studies, race is treated here as just one source of variation, and participation rates are re- ported as they appear in the published literature.

OCR for page 31
32 ously cannot be smaller than estimates of for the same sample and crime type. Estimates of the fraction of a popula- tion that is ever arrested, B. and the per- cent of a population arrested within some observation period, b, measure participa- tion as reflected in arrest (or other official) records. Since many people who commit crimes are never arrested, estimates of arrest participation are obviously less than those of crime participation, that is, b is less than d. As careers continue, how- ever, the chance of at least one arrest increases, so that the difference narrows between B and D. Although studies based on official rec- ords vary widely in design details na- ture of sample, criterion for identifying individuals who have participated, and length of observation period- b and B can be computed in only a limited num- ber of ways. Agency statistics on the age distribution of arrestees within a year can be used to compare b for any age by dividing the number of arrestees of that age by the entire population of that age. Because researchers usually want to study influences on participation beyond the demographic and criminal history variables contained in agency records and because only a fraction of crimes result in arrest, current participation is usually stuclied in terms of self-reported ct rather than officially recorded b. To estimate officially recorcled cumula- tive participation rates for example, BE (the fraction of a population arrested by age 18), three approaches are available. First, in prospective longitudinal studies, a cohort of individuals is selected and followed over time; notations of the ages at first arrest are used to compute B by each age. Second, in cross-section stud- ies, agency files are searched to ascertain the fraction of any sample of 18-year-olds for whom official records exist. Third, if arrest or court referral records for first offenders are easily distinguishable, a CRIMINAL CAREERS AND CAREER CRIMINALS life-table approach similar to that used in mortality studies can be used: the clistri- bution of age-specific initiation rates, Ia (i.e., the fraction of the population whose first arrest occurs at each age) can be computed and cumulated to age 18 to estimate Bit. This rate can be calculates] from the age (listribution of first arrestees in one year (T. Monahan, 1960, as cor- rected by Gordon and Gleser, 1974), or from arrest history data on members of a bird cohort (Wolfgang, Figlio, and Sellin, 1972~. However, to understand the rela- tionship between age and initiation rates, the conditional initiation rate, or hazard rate (ha)' may be more useful: this is the fraction that age-a initiators represent of the total a-year-old~s who have not yet initiated their criminal activity.2 Each of these three research designs has different implications for the measurement of B. Designs of self-report and official- record participation studies vary in other cletaiTs, such as the time period in which the data were collected; the seriousness of the behavior considered; and the threshold of contact with the criminal justice system, ranging from none (i.e., an uncletected crime) to a police contact, a court referral, or conviction. Self-report studies of delinquent activity usually in- clude a broader range of deviant behav- iors and less serious crime types than studies based on official police or court records. The source of official records also affects estimates: juvenile court recorcls, which record only incidents referred for frontal adjudication, are likely to produce 2Thus, for example, in a cohort of 1,000 boys, if 200 have initiated their careers by age 16 and 100 more begin in their 17th year, then In = 100/1,000 = 0.10, and he = 100/~l,000 - 200) = 0.125. At later ages, more of the offenders in the sample have already begun offending and they are therefore no longer at risk of becoming offenders for the first time, so Ja is likely to decrease but ha could well increase.

OCR for page 31
PARTICIPATION IN CRIMINAL CAREERS lower estimates of participation than are records of police contacts. As inventories of all crimes committee! by an individual, both official records and self-reports are subject to error. The prob- ability that an individual's offense will be recorded by police depends on such factors as patrol allocations, victims' re- porting behavior, offenders' success in avoiding police detection, and police dis- cretion in recording offender contacts, which is especially wide for juveniles. Errors in self-reports of criminal involve- ment arise primarily from under- ant! overreporting of criminal behavior and differences between individual and legal definitions of crime. These variations in measurement and their effects on esti- mated participation rates are a central concern in the following discussion of empirical research on participation. STUDY DESIGNS AND PARTICIPATION ESTIMATES Criminal participation is an incliviclu- ally basecI phenomenon that typically cannot be derived from aggregate arrest statistics. However, early estimates of B were made using record systems that dis- tinguish arrests or court referrals of first- time offenders from those of other of- fenclers. Although such systems are rare in American agencies, one exception is the Philadelphia Juvenile Court. In one of the first studies of criminal participa- tion, T. Monahan (1960) combined one year's age distribution of persons arrested or referred to court for the first time with data for the same year on the age clistri- bution of the general population (see also Ball, Ross, and Simpson, 1964~. British agencies routinely keep records of first offenders and this technique has also been used to estimate B in Britain (e.g., Little, 1965; Farrington, 19811. These data petit generalizations to contempo- raneous subpopulations, but they only 33 approximate participation rates in any single birth cohort represented in the subpopulation. Recorc! systems in most jurisdictions, moreover, do not collect the data needec! to study nondemographic correlates of participation; these data must be collected through interviews or searches of other record systems for incli- viduals being stuclied in cross-section samples or being tracker] longitudinally. Studies baser! on indivicluals' self-re- ports do permit study of the relationship between criminal participation (D and d) ant! a broacler range of characteristics. Data are gathered from cross-section or prospective longituclinal studies of sam- ples of persons representing some popu- lation of interest. Respondents are asked if they have committed specific criminal or delinquent acts, either ever (D) or during some definer] prececling interval (ct), and many other data are also col- lectecI. This method can generate cle- tailec! information on crime-specific par- ticination and its relationship to family structure, group membership, other be- haviors, ant] a wicle variety of socioeco- nomic characteristics. But measuring criminal involvement through self-re- ports can introduce several sources of error. For example, underrepresentation of offenders is a problem in self-report surveys because youths who are at a higher risk of criminal involvement are often school dropouts or truants or other- wise difficult to locate. Some evidence also suggests that underreporting and poor recall of crimes is common in self- reports of criminal activity. However, some respondents may exaggerate their criminal involvement. Differences in question wording ant! method of admin- istration also affect self-reporte(1 partici- pation rates in ways that make it difficult to compare results across studies. O~cial-record estimates of participa- tion (B ant! b) are computed by using a sample of inclivicluals selected on some

OCR for page 31
34 basis other than status as an offender, such as a random sample of a population or of participants in a prior study, perhaps unrelatecI to crime. Searches of official records have been carried out in conjunc- tion with prospective longitudinal or cross-section studies of demographic and social characteristics hypothesized to be relate c] to participation. Some researchers have gathered both offlcial-record and self-report data on the same individuals because of interest in comparing D with B (e.g., Gold, 1966; Hindelang, Hirschi, and Weis, 1981; Elliott et al., 19831. Because juvenile and adult records are generally maintained in separate reposi- tories, researchers concerned with cumu- lative participation estimates for adults- in particular, the lifetime risk of participa- tion, BL. have generally had to combine age distributions of participation rates from multiple sources and even multiple jurisdictions (Christensen, 1967; Belkin, Blumstein, and Glass, 1973; Blumstein and Graddy, 19821. To the extent that juvenile and adult participation behavior is similar across jurisdictions, this ap- proach can yield! reliable estimates of lifetime participation for different sub- populations. But since subpopulation composition may vary across jurisdic- tions, it is important that these subpop- ulations, which may differ systematically in terms of their participation (e.g., sex or race categories), be analyzed separately. Another concern in combining jurisdic- tions is that arrest recording thresholds and definitions may differ across the juris- dictions. Official records are becoming more widely accessible as a source of sequen- tial information about involvement in crime. However, since only a fraction (q) of all criminal acts lead to arrests that are recorded by the criminal justice system, official-record estimates of participation wit] always be Tower than actual levels of CRIMINAL CAREERS AND CAREER CRIMINALS involvement. In aciclition, crimes re- ported in an individuaT's official record may not be a representative sample of all crimes committed by that offender. Crimes of specific types (e.g., robbery relative to burglary) or of specific subpop- ulations (e.g., intoxicated offenders and inexperienced offenders) may be more likely to lead to arrest than others, thereby distorting comparisons of partici- pation across different groups. In addi- tion, police patrolling or investigation pri- orities defined in terms of location or crime type may also lead to over- or un- clerrepresentation of particular subpop- ulations in official arrest records (see Wil- son, 1968; Black and Reiss, 1970; Black, 1971; Smith and Visher, 19811. Informa- tion in arrest records, however, can be combined with other data to infer esti- mates about the likelihood of arrest for a given criminal event and for different subpopulations of offenders. A crime victim, in reporting an event to the police, has an important role in gen- erating an official arrest record. Reporting probabilities are known to differ by char- acteristics of the crime, the offender, and the victim (Hindelang, 1978b; Bureau of Justice Statistics, 1984a). Also, some re- ported crimes are "unfounded" which usually means that the crime is not re- corded- because the victim refuses to follow through with a complaint or be- cause police conclude that the reported event does not constitute a crime. The choice of data source also affects the type of criminal behaviors that are represented in any estimate of participa- tion. Most self-report studies do not have large enough samples to reliably measure D and, especially, ct for serious but less common offenses, such as burglary, large thefts, and robbery. Thus, self-report studies usually cover a much broa(ler set of criminal or deviant acts, frequently including school-relate(1 infractions and

OCR for page 31
PARTICIPATION IN CRIMINAL CAREERS minor delinquencies (e.g., fighting, tres- passing, vandalism, alcohol use) in which a large proportion of all youth are in- volved. Official records generally include only behaviors that are serious enough for a crime to be reported to police ant! thereby brought to the attention of the juvenile or criminal justice system. Even when official records ant! self-reports capture the identical set of events, dis- crepancies are likely to exist because of differences between legal and public def . . r Unctions or crimes. PARTICIPATION AMONG MALES Participation in offending is more often estimated for males than females. Female participation receives less research atten- tion because female offenders account for a much smaller share of crime, as mea- surec! by official statistics on total arrests. Because of the large amount of research on mates, the pane] used estimates of D and B for mates as a "baseline" for com- parison with other subpopulations. Crim- ~na~ paruc~panon among males has been estimated using the methods described above for vastly different samples and across several decades. Although few studies have attempted to produce na- tional estimates of participation, consis- tent findings across jurisdictions increase the confidence with which generaliza- tions can be made from local studies to subgroups regardless of their location. Our discussion focuses primarily on mate participation before the 18th birthday, Bit, and lifetime participation, BI, as de- rived from official-record estimates in published English-language research. Other measures of participation-current participation, c! (e.g., within the year pre- ceding the interview) and cumulative participation by high school age, DHS which are generally derived from self- reported data are also considered (for 35 more detail, see Visher and Roth, Appen- dix A).3 O~cial-Record Estimates Wolfgang, Figlio, and Sellin (1972) re- ported that 35 percent of a sample of mates born in 1945 and residing in the city of Philaclelphia from ages 10 through 18 had at least one recorded police con- tact for a nontragic offense by their lSth birthday (see Table 2-11.4 This estimate has become the most widely cited esti- mate of criminal participation among U.S. males. Since not all juvenile police con- tacts result in court referral, it is not sur- prising that analyses of Philadelphia juve- nile court statistics collected at about the same time (mid 1950s to mid 1960s) yield slightly smaller estimates of Bit. Those analyses found that 25 percent of mates had a juvenile court record by age 18 (reanalysis of T. Monahan, 1960, by Gor- don ant! Gleser, 1974~. Findings in Ken- tucky and, more recently, in Oregon are consistent with the Philadelphia court statistics: by age 18, 21 percent (Ball, Ross, and Simpson, 1964) and 25 percent (Polk et al., 1981) of males had juvenile court records. Table 2-1 presents estimates of partici- pation by 18 (Bit) for all ofEcial-record studies reviewed by the panel. While some of the estimates differ substantially 3Not all types of data exist for these four measures of criminal participation. In fact, estimates of partic- ipation by age 18 and in a lifetime are exclusively based on studies with official-record data, with one exception (Porterfield, 1946~. In contrast, active par- ticipation and participation by high school age are usually estimated from self-reported data (a few studies report BHS) Estimates of Dis, Do, and b do not generally appear in the published literature. 4"Nontraffic offenses" in the Philadelphia study encompass a very broad range of reasons for police contact, including many nonserious charges such as disorderly conduct, liquor violations, drunkenness, and investigation.

OCR for page 31
Crime Type and Level of Involvement . U.S. Studies Known to police or juvenile court Nontragic arrest or police contact 36 CRIMINAL CAREERS AND CAREER CRIMINALS TABLE 2-1 Estimates of Male Participation Rates by Age 18 (official record data) Participation Rates (percent) White Black All Males 52 23, 29 Juvenile arrest or court referral Juvenile court conviction Arrest for index offense British Studies Conviction or police caution, indict- able offenses Conviction for indictable offense 64 42, 50 13, 17, 18 8, 8, 9 31, 38, 38, 43, 50 26, 27, 27 56 25, 33, 34, 35, 41, 44, 47 17, 21, 25, 26 26, 28 12, 14, 18 15, 28, 29 12, 15, 16, 17, 17, 26 NOTE: See Table 1 and discussion in Visher and Roth (Appendix A) for sources and analysis of these alternative estimates. from Wolfgang et al.'s estimates, much of the variation can be explained in straight- forward ways. Differences in the set of offenses included, in the threshoIc3 of in- volvement (e.g., police contact, arrest, or conviction), or in the composition of the base population lead to considerable vari- ation across studies. A broad definition of criminal activity that includes clisorclerly conduct or suspicious behavior generates higher estimates of Bit, which may ex- plain the high average estimates of 56 percent reported by Palmore and Ham- mond (1964) for a high-risk sample in New Haven, Connecticut. Similarly, the difference between Shannon's (1982a) es- timates of BE for nontragic contacts (41, 44, and 47 percent) and those from the Philadelphia cohorts (33 and 35 percent) is likely due to the fact that in the Shan- non stucly consiclerable emphasis was placed on recording police contacts for minor infractions of the law as well as for status offenses (L. W. Shannon, 1985, per- sonal communication). When the measure of participation is restricted to arrests or contacts for index offenses, BE drops to 14 percent in the 1945 Philadelphia cohort and to 17 per- cent in Shannon's 1942 cohort (L. W. Shannon, 1985, personal communica- tion). Thus, a narrower seriousness defi- nition of criminal involvement substan- tially lowers Bit: according to four estimates, about 15 percent of all males participate in serious criminal activity, defined as an arrest for an index offense. Estimates of participation for a specific time period and location are also vuIner- able to changes over time in the scope of crimes and in population composition. For example, analysis of delinquency in a second Philadelphia cohort, born in 1958, was initially interpreted as implying that BE was almost identical with BE for mates born 13 years earlier (for the same offense definition and threshold of in- volvement). In fact, participation rates ac- tually decreased for both whites (from 29 to 23 percent) and blacks (from 50 to 41 percent); however, because of the large increase in the black population between 1945 and 1958, the overall rate appeared relatively unchanged. One possible ex- planation contributing to the race-specific declines in participation is that the range

OCR for page 31
PARTICIPATION IN CRIMINAL CAREERS of crimes that prompted police to stop suspects or make arrests may have nar- rowec] cluring this interval. If police in Philadelphia began to focus on more serious crime types in the 1960s, the participation estimates could have cle- cIined. Other Philadelphia data and another cohort study do show an increase in par- ticipation rates for serious crimes over the period (Shannon, 1982a; Tracy, Wolf- gang, and Figlio, 19851. For all Philadel- phia mates, Bit for violent index offenses (murder, rape, aggravated assault, rob- bery) increased from 4 to 10 percent. A similar pattern emerges from Shannon's cohort data: cumulative participation es- timates, based on at least one felony ar- rest by age 18, were 9 percent, lo percent, and 15 percent for males in the 1942, 1949, and 1955 cohorts, respectively. However, additional analyses are needed to partition this apparent increase in par- ticipation among effects of changes in population composition, of changes in participation behavior across successive cohorts in any subpopulation, and of changes in police arrest and recor~keep- ing practices. Estimates of lifetime participation, Be, are considerably more scarce-16 esti- mates, 10 of which are from two studies- and subject to some methodological con 37 cems rooted in the imprecision of mortal- ity adjustments and in the nature of the samples (see Table 2-21. In general, about half of all mates have been projected to have at least one police arrest for nontraf- fic offenses by ages 40 to 50 (Robins, 1966; Christensen, 1967; Belkin, Blum- stein, and Glass, 1973) and perhaps as many as 25 to 35 percent of U.S. mates will have arrests for an index offense (Robins; 1966; Blumstein and GracIdy, 1982~. As the threshold of criminal involve- ment narrows to a conviction record, esti- mates of BE would be expected to drop. McCord (1979) reports that about 30 per- cent of a Massachusetts sample of mates treated for childhood problems in the 1930s had a conviction record for any offense by age 50. A British projection based on aggregate statistics (Farrington, 1981) also concludes that 44 percent of British mates wit! have a conviction record] in their lifetime. These surpris- ingly high participation estimates reflect particular aspects of the studies' designs: broad definitions of crime were used, including serious misdemeanors (Far- rington) and disorclerly conduct (Mc- Cord); McCord's sample is generally ac- knowledged to have been at high risk of criminal participation; and the very high probability of conviction following arrest TABLE 2-2 Estimates of Male Lifetime Participation Rates (official record data) Participation Rates (percent) White Black Crime Type and Level of Involvement Nontragic arrest Arrest for index offense Conviction for serious offenses (unspecified) Conviction for property offense Conviction for violent offense All Males 47 68 15 52 50, 60, 60 23, 36 6, 29, 30, 35, 44 26 17 NOTE: See Table 2 and discussion in Visher and Roth (Appendix A) for sources and analysis of these alternative 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.

OCR for page 31
38 in Britain makes the arrest and conviction thresholds more comparable there than in the United States. Self-Report Estimates Altemative estimates of cumulative participation in crime (D) are available from self-report studies of specific crimi- nal activities (e.g., theft over $50, bur- glary, robbery) by cross-section samples of youth, usually those enrolled in high school. Since several grade levels are typ- ically sampled, the reported measure is interpreted as participation by an age range (e.g., 13 to 18 years), or more sim- ply, by "high school age," which we de- note as DHS. Considerable imprecision surrounds this measure since both D and vary strongly with age during the teen- age years. Nevertheless, the literature on these estimates provides much of the available information on relative crime- specific participation rates, and general consistency emerges from 10 studies con- ducted over the last 25 years.5 From these studies, a systematic pat- tem emerges in criminal participation across crime types. The two studies based on self-reports of high-school-age mates during the 1950s and 1960s report that 13 percent have stolen autos and 5 to 6 percent admit having stolen items other than autos worm more than $50 (Short and Nye, 1958; Jensen and Eve, 19761. In more recent studies conducted in the 1970s ant! 1980s, DHS for non-auto thefts over $50 has increased to around 15 per- cent, and similar recent estimates for auto sMany other studies have obtained self-reports of delinquent involvement among samples of high school youths, but the panel chose to focus on the subset of studies that reported involvement in seri- ous crime types for which an adult could be ar- rested. In addition, many self-report studies of delinquency only report aggregate frequency mea- sures or composite scales and not crime-specific individual participation rates. CRIMINAL CAREERS AND CAREER CRIMINALS theft have decreased to 10 percent. These changes in crime-specific participation likely reflect Me effects of inflation and enhancer] security features on newer au- tos. Burglary appears to be a relatively common crime among high school mates: in three different studies, 16 to 20 percent reported ever committing at least one burglary. For assault with injury, cumula- tive participation averages 13 percent in both the oIcler and more recent studies. Last, participation rates for robbery are generally consistent across several stud- ies, with about 6 percent of high-school- age mates reporting commission of a rob- bery, although one study, using a constructed single cohort, reports DHS for robbery of 15 percent.6 A few stuclies of high school males also measure participation rates through both self-reported and officially recorded in- volvement with the police or juvenile court. These estimates vary widely, prob- ably because of differences in definitions of crime, in thoroughness of record searches, in year of survey, and in geo- ~ranhic area. One recent study (Hinde- lang, Hirschi, and Weis, 1981) permits a direct comparison of official-record and self-report estimates of the fraction of a single sample with police contacts. In that study, involving a sample of high school students in Seattle selected in 1978, one-third to one-half of the teenag- ers did not report their police contacts to interviewers, if the official records are accurate; the underreporting was highest among white females and black mates. However, the findings from earlier stud- ies comparing police contacts as mea 6Estimates of cumulative participation by age 17 were calculated from data reported by Elliott and Huizinga (1984:62) for a synthetic cohort that was aggregated from three birth cohorts (1959, 1962, and 1965) to get cumulative participation rates at each age from 11 to 21 for the entire sample. The offense types used in their analysis are actually broad clus- ters of crimes, but some comparisons are possible.

OCR for page 31
PARTICIPATION IN CRIMINAL CAREERS sured by self-report and offlcial-record data are inconsistent: some show higher rates on self-report than official-record data, and some show other differences by subgroup (see Visher and Roth, Appendix A:Table 31. For white mates in the Seattle study, about 27 percent had an official record of police contact, which is consistent with official-record estimates for white males of 26 percent for BHS in a 1964 Califomia sample and 29 percent for BIS, in Phila- clelphia. The self-report estimate of po- lice contact of 17 percent for the white males in the Seattle cohort (Hindelang, Hirschi, and Weis, 1981) is also similar to that reported in two other studies (Gold, 1966; Williams and Gold, 19721. In con- trast, only 5 percent of one 1967 national sample of youths had official police rec- ords (Williams and Gold, 19721. This lat- ter estimate may reflect both the difficulty of obtaining complete official records on a nationwide sample and Tower participa- tion rates among the rural youth that were more heavily represented in that sample. When participation is measured by the presence of a juvenile court record that includes adjudication, the estimates range from 2 percent for index offenses in a 1967 national sample to about 11 per- cent for a broader range of offenses in the recent Seattle study. The three cumulative measures dis- cussed thus far are the most common statistics on participation reported in the literature either from official records or self-reports. But for many purposes, an annual measure of current participation by active offenders' 3, is useful. (Esti- mates of b are not commonly reported in the literature.) As discussed earlier, c! is computed as the fraction of some popula- tion committing at least one crime within a specified interval, usually one year. Es- timates of ct are less common in the liter- ature than estimates of D or B. cumulative participation. 39 All estimates of ct reported here were obtained by the self-report method through questions about involvement in specific offense types during a specific preceding reference period. In one study, reports of ~ were based on a 12-month reference period; for the other studies, 12-month estimates were interpolates] from values basest on reference periods of 18 months and 3 years. The panel re- viewed four studies (Weis, 1976; Bach- man, O'Malley, and Johnston, 1978; Tit- tle, 1980; Elliott et al., 1983) that used similar methods ancl reported ~ for five serious crime types: grand theft (over $50), breaking and entering, assault with a weapon or injury, robbery, and auto theft. Published statistics were annual- ized to provide comparable estimates across all studies. In any given year, about 3 to 6 percent ofteenage males steal items worth at least $50. Slightly more youths, 4 to 7 percent, report breaking en cl entering a building. Estimates of ~ for assault with a weapon (or causing injury) are less consistent across studies, with a range of 3 percent for younger adolescent mates (12-14 years) to 13 percent for oIcler males in high school (16-17 years). The age di~er- ences and personal definitions of"as- sault," even with injury or a weapon, are likely explanations of this variation. Last, ~ for robbery and auto theft among teen- agers averages 5 percent and 2 percent, respectively, although some variation ex- ists between studies and age categories. Few studies report `1 for aclults, but some limited data suggest that current partici- pation declines rapidly in the early 20s. In summary, estimates of cumulative participation rates among mates by high school age, by age 18, and by age 40-50 (lifetime) and current participation rates are influenced by: (1) the type of data used (aggregate statistics, official records, or self-reports); (2) the crimes in which participation is being measured; (3) level

OCR for page 31
40 or threshold of involvement (police con- tact, arrest, court referral, or conviction); and (4) the characteristics and representa- tiveness of the sample. These factors ac- count for most of the variation in esti- mates of participation (see Visher ant! Roth, Appendix A, Tables 1-4, for more details). CRIMINAL CAREERS AND CAREER CRIMINALS crime type, level of involvement, or mea- sure of participation. With few exceptions, the ratio of male- to-female participation in U.S. samples ranges from less than 3:1 for broadly de- fined offense categories to 5:1 for index offenses and specific crime types. In the 1958 Philadelphia cohort study, which included females, 14 percent of females had a recorder] nontragic police contact by age 18, as compared with 31 percent of males. In the three Racine, Wisconsin, cohorts, the average BE for males (with crime types broadly cleaned) was about 45 percent; for females, BE averaged 19 percent (Shannon, 1982a). Juvenile court referral estimates of B. which average 25 percent for males, range from 5 to 14 percent for females in four studies. Life- time participation estimates for females converge at 15 percent, compared with BE for males of 50 percent based on any nontragic offense. For specific crime types, corresponding male/female ratios of DHS and c! vary more across studies as a result of low reported participation values based on self-reports. PARTICIPATION ESTIMATES BY SEX, RACE, AND AGE Differences in participation across de- mographic subgroups~efined in terms of sex, race, and age, are discussec! be- cause much available data on participa- tion are reported in these terms. Further- more, the often substantial bivariate relationships are robust in multivariate analyses ant! stable across a variety of temporal and geographic settings and data collection methods. The policy im- plications of these empirical associations ant] those of other covariates are dis- cussed in later chapters. Sex Some of the research that reports par- ticipation rates for males also reports comparable measures for females. For fe- males, 16 estimates of Bit, 5 estimates of By, and 11 estimates of DHS were located in the literature reviewed by the panel; current participation, 4, among females in specific crime types was also reported in three studies. In general, patterns of par- ticipation among females parallel those among males: higher estimates for broad crime domains (e.g., all nontragic com- pared with index offenses) and low thresholds of involvement (e.g., police contacts or arrests compared with convic- tions). The most consistent pattern with respect to gender is the extent to which mate criminal participation in serious crimes at any age greatly exceeds that of females, regardless of source of data, Race Racial differences in criminal participa- tion have been examined with both self- report and official-record data for cumula- tive participation measures, Big, BL., and DHS, and for current participation, ct. These differences reflect a number of social and economic factors that are cor- related with both ethnicity and participa- tion. Self-report studies that report partic- ipation rates separately for white and black male subgroups (e.g., Gold, 1966; Hirschi, 1969; Hindelang, Hirschi, and Weis, 1981; Elliott et al., 1983) generally find negligible differences for primarily minor delinquent acts. The few self- report studies that permit race compari- sons for serious offenses show that the estimated ratio of black/white participa

OCR for page 31
PARTICIPATION IN CRIMINAL CAREERS tion is only slightly above 1:1 for self- reported serious property offenses such as grand theft, auto theft, and burglary (see Hindelang, Hirschi, and Weis, 1981; Visher and Roth, Appendix A:Tables 3 and 41. For self-reports of robbery and assault ant! for scales limited to index offenses, this ratio increases, especially at younger ages. For example, in the Na- tional Youth Survey, annual current par- ticipation rates for robbery, ct. for blacks ant! whites aged 11-17 were 9 and 4 percent, respectively, for a black/white ratio of 2.25:1. But in the fib wave of interviews, when the age range was 1~21, ct for black and white youth in the same sample was 3 and 2 percent, respec- tively, for a lesser ratio of only 1.5:1 (El- liott et al., 1983; see discussion in Visher and Roth, Appendix A:Table 4~. Studies using official data generally re- port greater black;/white ratios and stron- ger associations between race and partic- ipation in crime as the seriousness of criminal behavior increases from nontraf- fic offenses to all inclex offenses to violent index offenses. Combining data from sev- eral studies with criminal participation broaclly defined as nontragic offenses, the black/white ratio averages 1.8:1; for index offenses, the ratio averages 3.2:1 (Visher and Roth, Appendix A:Table 81. The Philadelphia cohort data are the only source of offlcial-record participation estimates by racial group across several levels of offense seriousness (Tracy, Wolfgang, and Figlio, 1985:Tables 4a and 5a). For the cohort born in 1945, the black/white ratios for Bit were 1.8:1 for nontragic offenses, 3.3:1 for UCR index crimes, and 4.5:1 for offenses with injury. For the cohort born in 195S, the ratios were very similar: 1.8:1, 2.9:1, and 3.2:1 for nontragic offenses, UCR index crimes, and offenses with injury, respectively. Analysis of all the data shows that racial differences in aggregate measures of criminal behavior appear to be largely a 41 function of differences in participation rather than offending frequencies. For example, the 1980 black/white ratios for arrest rates of males uncler age 18 were 1.6:1, 2.4:1, and 3.4:1 for nontragic of- fenses, all inclex offenses, and violent in- clex offenses, respectively.7 These ratios are very consistent with the participation ratios just presenter! for the Philaclelphia cohort born in 1958. Since aggregate ar- rest rates are a function of both participa- tion rates and indiviclual frequency rates (A= ,ub), the similarity in the black/white ratios suggests that racial differences in criminal behavior are largely a function of differences in participation. More black youth are arrested at least once, but black and white offenders tend to be rearrested! at similar rates (see also Blumstein ant] Bradley, 1982; Tracy, Wolfgang, and Figlio, 1985). Age The relationship between age and par- ticipation in criminal behavior can be examined using several measures. Com- mon measures are age-specific values of cl and of the hazard rate for initiation (h), as discussed above. Often, hazard rates can be calculated from official records (e.g., Wolfgang, Figlio, and Sellin, 1972; Far- rington, 1983a). Age distributions of cur- rent participation rates, data, are usually generated by studies that gather multiple waves of self-reportecl data on criminal involvement during recent intervals (e.g., Elliott et al., 1983~. Some patterns emerge from the studies that the pane] reviewed. Even though only a small fraction of youth at risk begin criminal careers at any given age, a con- centration of initiations among youth is 7These ratios were computed from 1980 race- specific arrest data (Federal Bureau of Investigation, 1981) and 1980 population figures (Bureau of the Census, 1983:Table 33~.

OCR for page 31
44 One reason for this result may be that a single teacher's or parent's rating of child- rearing practices may be influenced by various subjective factors that affect the generalizabiTity of the findings. Another explanation might be that the presence of multiple risk factors within a family (such as poor supervision, poor cliscipline) pre- dicts delinquency better than single risk factors. Recent studies of the effects of parent- ing techniques on pre-aclolescent con- duct disturbances as precursors to later criminal behavior have also pointer! to the adverse effects of parents' lax super- vision, passive attitudes, ant! ineffective cliscipline.~ In adclition, cross-section research has also founcl correlations be- tween some family management vari- ables principally discipline and super- vision ant! criminal involvement, but many of these studies do not report crim- inal participation rates (e.g., Nye, 1958; Hirschi, 1969; Patterson and Stouthamer- Loeber, 1984~. Parental Criminality A factor consistently associated with serious delinquency and aclult criminal participation in many different studies is criminal behavior of parents. In one study, for example, twice as many chil- ciren at age 10 with a convicted parent had a criminal conviction by age 25 as those without a convicted] parent (Far- rington, 1933a; see also Osborn and West, 19791. A multivariate analysis of these same clata shower! that having a convicted parent was a significant predictor of juve- nile convictions and self-reportec! delin- quency. This relationship persists in iRecent discussions of this topic can be found in Hirschi (1983), Patterson (1982), and Butter and Giller (1984:18~188~. For reviews of studies relat- ing nondelinquent but disturbing antisocial conduct to family functioning, see Butter (1977), Hinde (1980), or Patterson (1980~. CRIMINAL CAREERS AND CAREER CRIMINALS studies of children whose parents, or even grandparents, have a history of juve- nile delinquency, arrest, or other antiso- cial behavior, such as excessive drinking or a poor work record (see Robins and Lewis, 1966; Robins, West, and Herjanic, 1975). rental criminality and participation their children in delinquency is sup- norted bv studies that suggest that some offender characteristics (e.g., low arousal levels of the autonomic nervous system, certain EEG patterns, low intelligence) may arise from a mix of inherited ancl environmental factors. The strongest evi- dence for a partially genetic origin emerges from several studies concluctec! in Scandinavian countries, showing that adopted chil OCR for page 31
PARTIClPaTION IN CRIMINAL CAREERS Likely environmental explanations for the observed empirical association in un- broken families are that children who are raised in homes with criminal parents are exposed to aggressive behavior and anti- social attitudes (Rutter and Giller, 1984), poor child-rearing practices (Wilson, 1975), and adverse family conditions as- sociatec! with lower-cIass upbringing (Van Dusen et al., 1983~. Because the relationship exists even with respect to parental delinquency occurring before the child's bird, it is apparently not a consequence of direct involvement in the parents' criminal activity (Farrington, Gundry, and West, 1975~. Last, parental antisocial behavior, including unstable work patterns, alcohol ant] drug use, and a record of delinquency, also appear to be significant in the genesis of serious delin- quent behavior in their children. Family Disruption The impact of family disruption, espe- cially divorce and separation, on the par- ticipation of youth in criminal behavior has been a popular topic in studies of juvenile delinquency (for reviews, see Hennessey, Richards, and Berk, 1978; across studies in the base rate of delinquents and the selection ratio used by the researchers (for further discussion of RIOC, see Chapter 4 in this volume and Copas and Tarling in Volume II). Eight different predictors were examined for their associ- ation with male delinquency: composite measures of parenting; child problem behavior; stealing, ly- ing, or truancy; criminality or antisocial behavior of family members; poor educational achievement; single measures of parenting; separation from par- ents; and socioeconomic status. Loeber and Dishion found that the median RIOC for these predictors (averaged over studies with data on a specific pre- dictor) followed the above order. For parental crim- inality, the median RIOC was .24 with a range of 1.0 to .08. For example, the Hutchings and Mednick (1975) study of adoptees was used to calculate three RIOC measures: .11, .13, and .20; in addition, the false-positive rates for this study exceeded 70 per- cent. 45 Wilkinson, 19801. Family disruptions are consistently related to a record of convic- tion (Wadsworth, 1979; Farrington, 1983a) and to self-reported commission of index offenses or serious offense types (Farrington, 1979b; Elliott et al., 1983), with participation rates almost twice as high among youth from disrupted fami- lies as those from intact families. However, self-report studies that use nonserious offenses or other measures of criminal behavior besides participation report small and inconsistent associations between family disruption and delin- quency, perhaps because such minor acts are so widespreacI. For example, one study found a slight effect of family dis- ruption on a six-item scale of self-report- ed criminal activity that included prop- erty damage and theft uncler $2 (Hirsch), 1969; see also Nye, 1958; DentIer and Monroe, 1961; Berger and Simon, 1974~. It appears that "broken homes" may dif- ferentially affect mates and females, ur- ban and rural youth, and different ethnic groups (see Datesman and Scarpitti, 1975; Austin, 1978; Wilkinson, 1980), ant! these variables conic] account for some of the inconsistent results in research on family disruption and criminal participa- tion. There is also some evidence that family disruption has a selective impact on delinquency, primarily affecting rebel- lious behavior such as running away and truancy. In any case, it does not appear that family disruption per se is associated with clelinquency. Rather, parental discord, which usually precedes a break-up, or other difficulties that follow a break-up apparently impair normal family func- tioning and increase the risk of clelin- quency. Marital conflict within intact homes is associated with participation in delinquency, perhaps to a greater extent than broken homes (Rutter, 1981; Mc- Corcl, 19821. Evidence that parental death is unrelated to criminal involvement

OCR for page 31
46 while parental divorce increases delin- quency suggests that conflict between parents may account for the association between family disruption and delin- quent behavior (see Butter, 1981; see also, West and Farrington, 1973; Wads- wor~, 1979; but see Rankin, 19831. When father absence was broadly defined to include death and other separations unre- lated to divorce in two other studies, it was not a significant predictor of adult criminal behavior when multivariate analysis was used to sort out the impor- tance of several variables (Farrington, 1983a). And, a recent empirical review of several studies found that separation from parents at an early age was only weakly predictive of delinquency as an adoles- cent (Loeber and Dishion, 19831. A composite measure of parental be- havior that includes parental conflict, however, does predict adult criminal par- ticipation (Farrington, 1983a) and juve- nile convictions (McCord, 19791. As the operative factor, parental discord proba- bly reduces the effectiveness of parental supervision and discipline, interferes with supportive parent-child relation- ships, and offers negative, antisocial mod- els for a child. Moreover, the association between family conflict and criminal par- ticipation among children is probably a complex relationship affecting some youth but not others, depending on other family variables and the youth's charac- teristics. Family Size ant] Structure Family size appears related to delin- quency, but explanations for this finding are not yet established. Large families- defined as those with at least four chil- dren may handicap effective parenting and result in increased delinquency par- ticipation by children. However, the fam- ily size/delinquency relationship does not appear in a few studies of children CRIMINAL CAREERS AND CAREER CRIMINALS from large middle-class families, suggest- ing that the pertinent explanatory vari- able is the "disadvantages which tend to accompany family size in poorer sections of the community" (Rutter and Giller, 1984: 186) and not simply family size. For example, the decreased control of chil- dren because of lack of resources for child care and overcrowding in homes are plau- sible intervening explanatory factors (see Hirschi, 1983; Butter and Giller, 19841. In Farrington's (1983a) multivariate analy- sis, family size was not an independent predictor of criminal involvement in any of the four age groups examined; how- ever, associated variables, such as low family income and poor housing, were significant predictors of delinquency by ages ~10 and 1~13. Other family structure characteristics that may increase participation through their influence on parenting skills in- clude short intervals between first and second birds, continued growth in family size after a child reaches age 6, younger mothers (under age 20), and short inter- vals between marriage and the first child's birth, especially less than 1 year (see Wadsworth, 1979~. But these types of variables, including family size, have not been extensively studied with U.S. data (for an exception, see Hirschi, 1969~. Early Antisocial Behavior Using various measures of antisocial behaviors in the elementary school or preadolescent years, many investigators have examined the association of early antisocial behavior with later serious de- linquency and adult criminal activity. With few exceptions, the evidence indi- cates that such conduct as aggressive be- havior, "troublesomeness" in school, dis- honesty, and stealing are all related to a record of arrest or court conviction in later years (see Loeber and Dishion, 1983~. For example, in one study, 62 percent of

OCR for page 31
PARTlCIPaTION IN CRIMINAL CAREERS children who were rated by teachers, peers, or parents as troublesome at ages ~10 had court convictions by age 25, compared with 26 percent of other chil- dren (Farrington, 1983a; see also Feldhusen, Thurston, and Benning, 19731. In adclition, the pane} found that more general measures of early antisocial behavior-referral to a chiTct guidance clinic, teacher rating as "potentially de . ,, `` . . ,, . .~nquent or ant~soc~a , anc . excessive elementary school absences were simi- larly associated with criminal activity at oIcler ages (Reckless, Dinitz, and Kay, 1957; Robins, 1966; Robins and Wish, 1977; Ouston, 19841.~2 Further evidence of a strong associa- tion between preadolescent antisocial be- havior and delinquency appears in some research that has examined the impor- tance of various categories of variables in predicting delinquency. In a review of more than 20 studies, child problem be- havior including stealing, Tying, and tru- ancy- was second only to poor family management practices as a predictor of later juvenile and adult criminal involve- ment (Loeber and Dishion, 19831. Using several different techniques, Robins (1966; Robins and Wish, 1977) concluded that childhood deviance and adult antiso- cial behavior represented different stages of a single developmental process and that childhood behaviors were better pre- clictors than family variables. Last, Far- rington (1983a) also supports the view that criminal behavior is part of a devel- opmental sequence usually initiated by troublesome, clefiant, or aggressive be- havior in children before the age of 12. In i2A large literature outside the scope of the pan- el's focus on criminal careers addresses the preva- lence of antisocial behaviors (e.g., fighting, lying, stealing) in elementary school children and the evidence of continuities between these behaviors and various psychosocial problems in adulthood (Olweus, 1979; Loeber, 1982; Loeber and Dishion, 1983; Butter and Giller, 1984:Chapter 2~. 47 his data, family influences and the child's antisocial behavior were equally impor- tant in predicting conviction by age 25. Despite the apparent consistency of Me relationship between early antisocial be- havior and subsequent criminal participa- tion, data are lacking on several signifi- cant points. First, while continuities between antisocial behavior and partici- pation in crime have been fount! in stud- ies of older children (ages ~14) followed into adolescence or early adulthood, vir- tually no studies have followed children from ages 4 to 7, when antisocial behavior tends to begin, into young adulthood, when the risk of criminal career initiation has largely passed. Therefore, under- standing of the relationship between early behavior and criminal participation is incomplete. Second, most children who exhibit antisocial behaviors do not become involves! in criminal activity as teenagers or adults. There is little knowI- edge of the factors that reliably identify antisocial preadolescents who do not progress to offending patterns involving serious crimes. Furthermore, there is ev- idence that suggests it is even more diffi- cult to preclict eventual serious criminal behavior among persons who first be- come offenders in young adulthood. Social Class Social class is often discussed as an important correlate of criminal behavior, although there is substantial debate over the consistency of the relationship be- tween Tow social class anc! involvement in criminal activity and about its underly- ing meaning. Most of the recent U.S. studies of this cIass/crime association have relied on self-report data, which tap nonserious criminal activity that is rela- tively common and does not necessarily attract justice system intervention. In the panel's review of the research relating participation rates to individual

OCR for page 31
48 level measures of social class, no signifi- cant association emerges in self-report studies when the measure of criminal activity is primarily nonserious behavior, such as vandalism, fighting, or small chews. This result probably reflects He fact Hat a large fraction of youths engage in that behavior regardless of Heir social cIass.~3 Also, in studies of the class/ participation relationship in which mea- sures of official involvement (e.g., police contact, arrest record) encompass a wide range of delinquent behaviors, no associ- ation is usually found (e.g., Hathaway and Monachesi, 1963; Polk, Frease, and Rich- mond, 1974; Hindelang, Hirschi, and Weis, 1981~.~4 When criminal participation is re- stricted to serious offenses, social class differences emerge in one major study Hat user! self-report measures (Elliott and Huizinga, 1983), and this association persists after convolving for race. Win official data (e.g., juvenile court or police recorcis), He cIass/serious crime relation- ship is fairly s~ong, especially in He pre-1970 studies (e.g., Reiss and Rhodes, i3Many investigators have examined the class/ crime issue with self-report data (e.g., Nye, 1958; Akers, 1964; Hirschi, 1969; Williams and Gold, 1972; Johnson, 1980; Krohn et al., 1980~. For a detailed review of studies considered by the panel, see Visher and Roth (Appendix A). However, some studies using other measures of criminal behavior, principally aggregate "incidence" rates, have re- ported differences by class group (e.g., Elliott and Voss, 1974; Hindelang, Hirschi, and Weis, 1981:194; Elliott and Huizinga, 19831. Other impor- tant reviews on this topic appear in Tittle, Villemez, and Smith (1978), Hindelang, Hirschi, and Weis (1979, 1981), and Clelland and Carter (1980~. i4In the Racine, Wisconsin, cohort study, which had official data on broadly defined police contacts (including investigations, suspicion, and informa- tion-gathering), Shannon (1982a) found social status to be unrelated to number of police contacts; how- ever, participation rates by social status could not be computed from published data. CRIMINAL CAREERS AND CAREER CRIMINALS 1961; Gold, 1966; for another review, see Tittle, Villemez, and Smith, 19781.~5 Re- cent evidence, however, is limited be- cause individual official records usually do not include individual-level social class measures, and arrest statistics are not clisaggregated by this variable. Some existing data sets presumably contain of- ficial-record data that would provide fur- ther information about the relationship between participation in serious offenses and social class (e.g., McCorc3, 1979; Hin- delang, Hirschi, and Weis, 1981; Shan- non, 1982a; Thornberry and Farnworth, 1982), but the appropriate analyses have not been reported in the literature. The strongest evidence for a negative association between social class and crim- inal participation appears in research us- ing ecological (area) measures of social class (e.g., Lander, 1954; ChiTton, 1964; Shaw and McKay, 1969; Wolfgang, Figlio, and Sellin, 1972~. Indeed, until 1950, ecological correlations were the only basis for conclusions about social class and criminal behavior (Hinclelang, Hirschi, and Weis, 1981: 1841. However, comparisons between these studies and those with individual social class indica- tors must be made cautiously. For one ~5Hindelang, Hirschi, and Weis (1981) refer to Hirschi (1969) as another study with a moderate class/official-record relationship (correlation of -.21), but participation rates by social class are not reported in the original source. In three British studies (Wadsworth, 1979; Farrington, 1983a; Ouston, 1984) and one study with data from Den- mark (Van Dusen et al., 1983) the class/crime rela- tionship is particularly strong. i6Using regression analysis and follow-up data from the 1945 Philadelphia cohort initially collected by Wolfgang, Figlio, and Sellin (1972), Thornberry and Farnworth (1982) found a strong association between individual social status and both the fre- quency of officially recorded serious (e.g., index or violent arrests) and nonserious (e.g., total arrests) adult criminal behavior, but participation rates by social class were not reported.

OCR for page 31
PARTICIPATION IN CRIMINAL CAREERS thing, aggregate relationships do not nec- essariTy permit valid inferences to indi- viduals (see Robinson, 1950; Hannan, 19711. Urban areas that are cleaned as lower class may have higher crime rates because of a small group of very active criminals or because outsiders come into the area to commit crime. In addition, differential police surveillance and arrest practices in lower-cIass areas may con- tribute to ecological correlations between social status and crime. In discussing this issue, TittIe, Villemez, and Smith (1978) argued that census tracts a common unit of analysis in ecological studies are typ- ically quite diverse with regard to family income, and especially so during the 1950s and 1960s when most ofthe ecolog- ical research was carried out. In summary, individual social class may be empirically related to some types of serious clelinquency and adult criminal behavior when participation is measured either by self-reports or official records, but relevant research is limited, espe- cially that based on recent samples. In a review of socioeconomic class as a preclic- tor of a chiefs later clelinquency in seven studies, Loeber and Dishion (1983) con- cluded that social status was a poor pre- dictor compared with early antisocial be- havior or measures of family functioning. But low social class and low family in- come at age 14 significantly predicted convictions at ages 17-20 and 21-24 in a multivariate analysis that controller] for some family influences (Farrington, 1983a). The meaning ofthis association is far from clear, but it may be due in part to social class differentials in police detec- tion, official recording of criminal behav- ior, or victim reporting. Indicators of social status may also overlap with unmeasured! aspects of parental behavior and family structure that are consistently related to delinquency. 49 School Performance and Intelligence The relationship between participation in delinquency or adult criminal activity and various measures of school perform- ance or intelligence measured by school achievement test scores, standard IQ tests, vocabulary skills, and "school fail- ure" has been examined in many studies. In the panel's review of eight studies (see Visher and Roth, Appendix A:Table 15), the empirical association between Tow intelligence or school achievement and criminal involvement was consistent in a wide variety of samples and with both self-report and official measures of delin- quency. In general, participation decreases with higher IQ scores, grade point aver- ages, reading test scores, and other mea- sures of academic achievement. Polk, Frease, and Richmond (1974) reported that 42 percent of a general high school sample with low grades had a juvenile court record compared with 22 and 9 percent of students in the sample with average and high grapples, respectively. In some studies, the relationship between participation and intelligence/achieve- ment is independent of race (e.g., Wolfgang, Figlio, and Sellin, 1972) and social class (e.g., Reiss and Rhodes, 1961; Polk, Frease, and Richmond, 19741; it also exists in research that relates school achievement or intelligence to other mea- sures of criminal behavior, such as scales clerived from factor analysis or aggregate frequency measures (Weis, 1973; data from Hirschi, 1969, cited in Hirschi and Hinclelang, 1977; Menard and Morse, 1984~. In addition, empirical links emerge between various non(lelinquent conduct disorders, which may precede clelinquency, and measures of intelli- gence (for a review, see Butter and Giller, 19841.

OCR for page 31
50 While empirical results are consistent the search for possible explanations ofthe association between delinquency and Tow intelligence/achievement continues (see discussions in Gordon, 1976:256- 270; Hirschi and Hindelang, 1977; Wil- son and Herrnstein, 1985~. Hirschi and Hindelang argue that IQ influences de- linquent behavior primarily through its correlation with school performance, al- though the empirical evidence for their hypothesis is weak ancI is contradicted by at least one recent study (Menard and Morse, 19841. Alternatively, low scores on IQ tests may reflect a predelinquent's resistance to authority and unwillingness to make the effort needed to do well on such tests. The association between school conduct disorders and IQ is fairly well establishecI (see Butter and Giller, 1984:163-168), but no study has success- fully resolvecI the issue of how school performance, IQ, and early antisocial be- havior might interact in predicting delin- quency. In two multivariate analyses, Tow IQ emerged as a strong predictor of juvenile convictions along with poor parenting and antisocial behavior (Farrington, 1983a), but was not significant in another study once school variables and social class were controlled (Wolfgang, Figlio, and Sellin, 1972~. Thus, what we know at present is that Tow intelligence and weak school performance appear to be closely intertwined, and several studies have shown them to be strong predictors of serious delinquency and adult criminal behavior (Loeber and Dishion, 1983), but any causal structure among these factors is not yet established. Substance Abuse The relationship between substance abuse and criminal activity is widely thought to be firmly established, sup- portecl by empirical research as well as CRIMINAL CAREERS AND CAREER CRIMINALS informal observations of criminal justice operations. But this relationship is much more complex than it initially appears, especially when "criminal activity" is de- fined in terms of criminal career dimen- sions. The distinction between participa- tion in criminal behavior (D) and the frequency of that behavior (A) is particu- larly important when discussing sub- stance abuse. We examine here the rela- tionship of criminal participation and substance abuse, that is, whether drug users are more likely to be involved in crime than non-users. In the next chapter, on active offenders, we review the re- search on whether drug-using criminals commit crimes more frequently than non- using criminals (see also Wish and Johnson, Volume II). The panel did not consider much of the research on substance abuse and criminal participation, which has focused on juve- niles, their use of marijuana or alcohol, and their involvement in relatively minor criminal behavior (e.g., small thefts, school crime, vandalism) (see Burkett and lensen, 1975; Wechsler and McFadden, 1976; Kellam, Ensminger, and Simon, 19801. But the available evidence on par- ticipation in serious criminal activity sug- gests that drug users, especially multiple drug users, are much more likely to be involved than non-users (e.g., Johnston, O'Malley, and Eveland, 1978; Elliott and Huizinga, 19841. Table 2-3 presents data from a national sample of youths aged 11-17 in 1976 and 1~21 in 1980 (Elliott and Huizinga, 1984~. The self-reportecl participation rates for felony assault, fel- ony theft, and robbery increase dramati- cally as drug use becomes more serious, from no (lrug use to alcohol only, alcohol and marijuana, and multiple drugs. Data of this type, however, cannot an- swer the frequent question whether sub- stance abuse leads persons into crime. A longitudinal study of both criminal in- volvement and drug use is needed to sort

OCR for page 31
PARTICIPATION IN CRIMINAL CAREERS TABLE 2-3 Current Criminal Participation Rates, 4, by Drug User Types (percent) 51 Crime Typea Drug User Typeb 11-17 yearsC 15-21 yearsC Felony assault No drugs 12.7 4.1 Alcohol 18.3 5.2 Alcohol/marijuana 33.8 13.5 Multiple drugs 51.7 24.2 Felony theft No drugs 6.3 2.3 Alcohol 18.6 4.4 Alcohol/marijuana 32.4 13.5 Multiple drugs 55.2 27.3 Robbery No drugs 4.0 0.8 Alcohol 5.7 0.4 Alcohol/marijuana 6.8 2.8 Multiple drugs 22.4 6.4 aThese crime types are actually clusters of related offenses. Felony assault is composed of aggravated assault, sexual assault, and gang fights; felony then includes auto theft, theft over $50, breaking and entering, and bought stolen goods; robbery encompasses strong-a~ming students, teachers, and others. bBased on self-reports of drug use in the preceding year. Since the researchers wished to focus on non- experimental drug use, use of the specific drug at least four times was a definitional requirement. CActive participation rates for the preceding year, d. SOURCE: Data from Elliott and Huizinga (1984:Tables 1 and 2), for first and finch waves of longitudinal study. Out the causal relationship between sub- stance use and criminal activity. Table 24 presents such data on youths aged 11-19 from the National Youth Survey (Elliott and Huizinga, 19841. Although the measure of criminal activity is not strictly based on participation, the ciata are relevant here. In this particular sam- ple, the predominant pattern among drug users who are also delinquent was for initial drug use to follow delinquency or to occur simultaneously, rather than for drug use to prececle delinquency. This study concluded that both substance abuse and criminal behavior may be a result of similar social and individual fac- tors, principally ineffective socialization in the home, involvement with clelin- quent peers, and school-related clifficul- ties (see also Elliott, Huizinga, ant] Ageton, 19851. In another study (Robins and Wish, 1977), the median age of initi- ation for serious alcohol problems ant! barbiturate ant! amphetamine use (16.3 years) was later than the median age at initiation for juvenile arrests (15.2 years). Studies of drug addicts, which show that a history of criminal behavior preceded ad- cliction, also appear to support this view (see Wish and Johnson, Volume II; Rob- ins, 1979; Friedman ant] Friedman, cited in Kaplan, 1983~. Employment The relationship between unemploy- ment and participation in criminal activ- ity has been a source of considerable controversy. Presumably, a disorganized life-style is associated with both unstable employment and involvement in crime, but the specific causal relationships have not been fully explored (for one recent attempt, see Thornberry and Christen- sen, 19841. In a comprehensive review of 25 studies using aggregate (lata, Freeman (1982) concludecl that there is no solid evidence Mat unemployment affects

OCR for page 31
52 TABLE 2-4 Temporal Order of Drug Use and Delinquency Involvement in Drug Use and Delinquency Percent of Total Sample (1976-1978) . No drug usea and no delinquencyb 46.0 Drug use and no delinquency 26.5 Alcohol Alcohol and marijuana Alcohol, marijuana, and other drugs No drug use and delinquency Initial drug use before delin quency involvement 4.4 Alcohol Alcohol and marijuana Alcohol, marijuana, and other drugs Initial drug use after delinquen cy involvement Alcohol Alcohol and marijuana Alcohol, marijuana, and other drugs Initial drug use and delinquency involvement occur in same year Alcohol Alcohol and marijuana Alcohol, marijuana,~and other drugs Other, not classifiable 8.9 8.0 3.7 4.3 t0.1' aDrug use is defined as use of the specific drug at least four times in the preceding year, or use of each drug at least four times for multiple drug use types. bDelinquency involvement is defined as engag- ing in 12 or more self-reported delinquent of- fenses and at least 2 index offenses in the preced- ing year. SOURCE: Elliott and Huizinga (1984:Table 9). criminal behavior (see also Cantor and Land, 19851. However, the panel's re- view of research based on individual ciata did find some consistent patterns (see Visher and Roth, Appendix A). In particular, the association of unem- ployment with criminal participation ap- pears to be different for adults than for school-age youths, possibly because un- employment may have different mean CRIMINAL CAREERS AND CAREER CRIMINALS ings for the two age groups. Unemployed or erratically employed adults are more likely to be involved in criminal activity than those with stable employment, and in one study this relationship persisted even when controls were introcluced for criminal history and drug use (Viscusi, `~8.6) 19831. An unstable work record at age 18 (7 i) was also a significant predictor of a con viction record at age 21-24, even control -ling for antisocial and delinquent behav ior at earlier ages (Farrington, 1983a). In contrast, full-time employment appears to influence school-age youths adversely, `0.6) t3.9' (a 5) with higher fractions of employed youths, LO ~ ~ especially at ages 1~17, than others cur- rently participating in serious offenses (Elliott et al., 1983, 19851. Unfortunately, (4 7) research on the effects of school-age em (2 i) ployment is scarce, and some studies only report mean arrest data or seriousness measures, rather than participation rates.~7 Taken together, analyses of unemploy- (2 6) ment and crime suggest that employment may Inhibit criminal participation In adult years, while employment during adolescence may be associated with crim- inal activity, perhaps because it separates teenagers from parental supervision and gives them funds to buy drugs and alco- hol. The research that shows different 17The studies reviewed by the panel vary in their measures of criminal behavior (e.g., active partici- pation, cumulative participation to age 25), and the respondents in these studies range from a represen- tative sample in the National Youth Survey (Elliott et al., 1983), to 2,000 young black men in three highly urban settings (Viscusi, 1983), to a study of 400 British youngsters followed for more than 15 years (Farrington, 1983a). The study by Viscusi used a broader definition of criminal activity than the others: respondents were asked whether they had participated in any of 10 specific criminal acts in- cluding the category "any other illegal activities" (1983:16). Three studies do not report participation rates by employment status (Bachman, O'Malley, and Johnston, 1978; Shannon, 1982a; Thornberry and Christensen, 1984), but their results are consis- tent with the findings discussed in the text.

OCR for page 31
PARTICIPATION IN CRIMINAL CAREERS directions of effects at different ages high- lights the necessity of partitioning the population uncler study into separate groups within which observable factors have consistent theoretical meanings. Unless such partitioning is done, the un- derlying relationships may be masker! by confounding effects. This possibility is particularly relevant to the relationship between employment and criminal be- havior, and it may also have an impact on other factors associates! with participa- tion. Peer Group Influences Involvement with delinquent friends is widely believed to be positively related to juvenile criminal behavior. Indeed, this concept lies at the heart of one major theory of delinquency, differential associ- ation theory (SutherIancI and Cressey, 19781. Several longitudinal studies report that association with delinquent friends is clearly related to participation in serious criminal behavior at later ages (Far- rington, 1983a; Polk et al., 19811. In Far- rington's British study, 59 percent of males who had extensive involvement with delinquent friends at age 14 had a conviction record at age 25, in compari- son with only 25 percent of other chfl- dren. Unfortunately, few empirical tests of differential association theory present data on participation in serious criminal activity and negative peer influences. Many studies examine marijuana and drug use because these activities are of- ten tier! to peer contacts (e.g., Burkett and Jensen, 1975; Kandel, 1978; Akers et al., 1979), or focus on a delinquent popula- tion and their peer contacts (see espe- cially, Reiss, Volume II; Hinclelang, 1976; Morash, 1984~. Other research has used multivariate mocleling techniques. While some of these studies report signif- icant direct effects of negative peer influ 53 ences on delinquency (e.g., Jensen, 1972; Matsueda, 1982; Elliott, Huizinga, and Ageton, 1985), the delinquency measure is usually a composite index of minor and moderately serious behaviors (but see lohnstone, 1978~. Analyses of peer influences and crimi- nal behavior indicate that involvement with many delinquent friends is a signifi- cant risk factor for participation in delin- quency. These results are consistent across a wide variety of samples, measures of delinquency and peer influences, and esti- mation techniques. Some recent research (e.g., Matsueda, 1982; Elliott, Huizinga, and Ageton, 1985) is attempting to sort out the underlying causal relationships, includ- ing the possible mediating effects of paren- tal supervision and attachment, involve- ment in conventional activities, and exposure to conventional attitudes. SUMMARY Perhaps the most striking observation about participation is the high rate at which males ever become involved in crime and even in arrest. Typically, about 15 percent of urban mates are arrested for an index offense by age 18 ant! about 25 to 35 percent will be arrester] for such an offense sometime in their lifetime. De- mographic differences in participation, as measured by arrest, are large, most strik- ingly between the sexes and less so be- tween the races. The differences in participation among demographic groups vary consiclerably with offense seriousness. When the clefi- nition of criminal behavior is broadly de- fined, participation is widespread in all demographic groups and so relative dif- ferences in participation are small. For serious offenses, for which the base rates of participation are low, the demographic differences are considerably larger. This interaction of demographic variables with changes in the scope of criminal partici

OCR for page 31
54 pation resolves only part of the discrep- ancy between some self-report studies (which indicate small and inconsistent black/white differences in "offending" when the offense threshold is extremely low) and official-record data for serious offenses, which show large differences between blacks and whites. Of more theoretical and policy signifi- cance is the fact that research on other factors associated with participation in serious offending consistently points to the same variables that have long been associated with crime: ineffective parent- ing, poor school performance, Tow mea- sured IQ, drug use, and parental criminal CRIMINAL CAREERS AND CAREER CRIMINALS ity. It is extremely difficult, however, to develop reliable measures of the relative influence of each of these variables, largely because of the complexity of the underlying relationships among them and because different studies highlight only one or a few of the variables rather than all of them. The factors that distinguish participants from nonparticipants couIcl well be dif- ferent from the factors that distinguish among participants, in terms of their offending frequency. The next chapter considers estimates of frequency and the factors associated with variation in fre- quency.