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Social Structure and Crime Control Among Macrosocial Units Author(s): Allen E. Liska and Mitchell B. Chamlin Source: American Journal of Sociology, Vol. 90, No. 2 (Sep., 1984), pp. 383-395Published by: The University of Chicago PressStable URL: http://www.jstor.org/stable/2779220Accessed: 26-03-2015 21:31 UTC

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Social Structure and Crime Control among Macrosocial Unitsl Allen E. Liska and Mitchell B. Chamlin State University of New York at Albany

Recent research, drawing on the conflict perspective, has examined the effect of the racial/economic composition of macrosocial units on the capacity for crime control (police size). This paper extends this work to actual crime control (arrest rates). The results show that there is considerable variation in arrest rates between cities and that racial/economic composition substantially affects them, independently of reported crime rates. The effects are specified by type of arrest (property and personal) and race of offender (white and nonwhite).

This paper is concerned with crime control among macrosocial units. Most research, based on deterrence theory, examines the effect of crime control on crime rates. Our research, drawing on the conflict perspective, examines the structural causes of crime control.

The conflict perspective conceptualizes crime control as an instrument used by dominant and powerful groups to control those actions and groups which threaten their interests. Turk (1969), for example, argues that culturally dissimilar groups are perceived by authorities as threats to the social and political order and that crime control can be understood as an instrument for controlling them. With the exception of various histor- ical and case studies (Chambliss and Seidman 1982), there have been few explicit empirical tests of the conflict perspective of crime control- specifically, of the threat hypothesis-at the macro level. Recently Jacobs (1979), Jackson and Carroll (1981), Liska, Lawrence, and Benson (1981), and Loftin, Greenberg, and Kessler (1981) have examined the effect of the racial/economic composition of cities and SMSAs, as an indicator of the threat perceived by authorities, on the capacity for crime control as mea-

' We would like to thank Joseph Lawrence for assistance with data collection; Larry Sherman and Paul A. Zolbe for assistance in obtaining the arrest data; and Judith Blau, Terry Blum, Ronald A. Farrell, Richard B. Felson, Reid Golden, John Logan, Kenneth Mazlen, Mark Reed, and Glenna Spitze for their comments on various drafts of the paper. Requests for reprints should be sent to Allen E. Liska, Department of Sociology, State University of New York at Albany, Albany, New York 12222.

? 1984 by The University of Chicago. All rights reserved. 0002-9602/85/9002-0006$0 1.50

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American Journal of Sociology

sured by police size and expenditures. Our research extends this work in two directions. One, it examines the effects of three dimensions of racial/ economic composition central to the studies above (percentage nonwhite, segregation, and economic inequality) on the actual volume of crime control as measured by arrests. Two, it explicitly examines three social processes (threat, power, and benign neglect) which, according to the conflict perspective hypothesis, underlie the relationship between racial/ economic composition and crime control.

PERCENTAGE OF NONWHITES The researchers above argue that nonwhites, as a culturally and racially dissimilar subordinate group, are perceived by authorities as threats to the social and political order and that police are used to control them. Although a relatively small culturally dissimilar subordinate group may not be perceived as posing much of a threat, a relatively large culturally dissimilar group constituting 20%-30% of the population may be perceived as posing a substantial threat and as a problem of social control. In particular, nonwhites are viewed as criminal threats (Swigert and Farrell 1976; Lizotte and Bordua 1980; and Liska et al. 1981). For example, Liska et al. (1981) report that, when one controls for crime rates, the percentage of nonwhites in a city substantially affects the fear of crime. Hence, we might expect a strong relationship between the percentage of nonwhites in a social unit and the level of crime control. Jackson and Carroll (1981), Jacobs (1979), Liska et al. (1981), and Loftin et al. (1981) consistently show that, when one controls for reported crime rates, the percentage of nonwhites in cities and SMSAs relates substantially to police size.

The implications of the percentage of nonwhites for the actual volume of crime control, as measured by arrest rates, are much more complex. The conflict perspective implies three distinct causal processes.

To clarify these processes, it may be useful to think of the total arrest rate as composed of the rates for whites and nonwhites weighted by their proportions of the city population. Conflict theory assumes that nonwhites have a substantially higher arrest rate than whites because, relative to whites, they are less able to resist arrest and because authorities share common stereotypes linking them with crime. Therefore, as the percentage of nonwhites increases, the total arrest rate of a city should increase (power hypothesis). Statistically, this is a compositional or an aggregate effect.

The threat hypothesis underlying the recent work on police size suggests that a high percentage of nonwhites produces an emergent property, "perceived threat of crime," which increases arrest rates through increas-

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ing pressure on police to control crime. For, if increasing the size of the crime control apparatus is one response to a perceived threat of crime, then pressuring the existing police apparatus to control crime would seem to be an equally logical response. Hence, the threat hypothesis suggests that the percentage of nonwhites affects the total arrest rate because it affects the actual arrest rate of nonwhites and perhaps of whites as well.

The conflict perspective also suggests that the percentage of nonwhites may affect arrest rates by constraining the racial composition of crime. For nonwhites, as for all social categories, as their percentage in the population increases, the proportion of their in-group to out-group interaction in everything from marriage to crime increases (Blau 1977); so, as the percentage of nonwhites increases, the ratio of intra- to interracial crimes increases for nonwhite offenders and decreases for white offenders. For nonwhite offenders intraracial crime may have a lower arrest rate than interracial crime. It may be viewed by both victims and police as more a personal and family problem than a matter requiring official intervention. Nonwhite victims may be less prone to report it to the police, and when they do report it, they frequently may be unable to legitimate their complaint as a crime and to pressure police to allocate resources to resolve it. Thus, the percentage of nonwhites may negatively affect their arrest rate (the benign-neglect hypothesis). For white offenders, because intraracial crime involves higher- as well as equal-status victims, the implications of the ratio of intra- to interracial crime on arrest rates is not so clear.

In sum, the conflict perspective suggests three related but distinct causal processes underlying the effect of the percentage of nonwhites on arrest rates. The net effect of the percentage of nonwhites on the arrest rate depends on the relative strengths of these causal processes.

SEGREGATION Spitzer (1975) argues that the segregation of problematic groups into urban ghettos functions as a vehicle of social control, thereby reducing the need for a large crime control apparatus; and Liska et al.'s (1981) research shows a substantial inverse relationship between racial segregation and police size per capita in major U.S. cities. Extending this thesis to the actual volume of crime control is quite straightforward because the threat and benign-neglect hypotheses make the same prediction: an increase in the segregation of problematic populations (nonwhites) decreases the arrest rate. However, the hypotheses assume that different causal processes underlie the effect. The threat hypothesis suggests that, by reducing the threat of crime perceived by authorities, the segregation of nonwhites reduces the pressure on police to control crime, thereby

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decreasing the arrest rate, especially that of nonwhites. The benign- neglect hypothesis suggests that, by increasing the ratio of intra- to interracial crime for nonwhite offenders, the segregation of nonwhites decreases the pressure on police to control crime, thereby decreasing the arrest rate, especially that of nonwhites.

ECONOMIC INEQUALITY Conflict theorists argue that economic stratification or inequality accentuates economic conflict, which in turn increases the threat perceived by the dominant class, and that the greater the conflict, economic stratification, and perceived threat, the greater the disposition of the dominant class to use coercion to maintain a social order favorable to its interests (Chambliss and Seidman 1982). Therefore, the greater the income inequality, the greater the level of crime control.

We have been able to locate only a few studies bearing directly on this proposition. Jacobs (1979) reports a substantial relationship between income inequality and police size for major SMSAs; however, Loftin et al. (1981), in a study of cities, are unable to replicate these findings. As to the actual volume of crime control, for states Jacobs (1978) reports a relationship between income inequality and the certainty of punishment, and for SMSAs Williams and Drake (1980) find a relationship between income inequality and arrest rates. These findings must be viewed with caution, because other important variables, such as reported crime rates and racial composition, are not controlled. Our research extends this research by examining the effect of income inequality on arrest rates, with racial composition and reported crime rates controlled.

In sum, in an extension of past work on police size, our research examines the effect of racial/economic composition on actual crime control (arrest rates) as it operates directly and indirectly through its effect on the capacity for crime control (police size).

PROCEDURES The sample is part of a sample of 109 cities, originally selected because their residential segregation levels have been calculated since 1940. Arrest data are available for 76 of these cities, approximately one-half of all cities over 100,000 in population.

Crime Control The volume of crime control is measured by arrest rates (ratio of arrests to population) for both property (robbery, larceny, burglary, and auto theft)

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and personal (homicide, aggravated assault, and rape) index crimes. Put- ting these arrests into personal and property categories minimizes incon- sistencies in classification among police departments. For example, a rape could be misclassified as an assault but is unlikely to be misclassified as a larceny.

Capacity for Crime Control Capacity is measured by the number of police employees per capita (Fed- eral Bureau of Investigation 1972). Civilian clerical employees are included in the measure because they free uniformed personnel for the immediate task of crime control.

Racial/Economic Composition Racial residential segregation is measured by the Dissimilarity Index, which describes the extent to which the racial composition of city blocks reflects the racial composition of the city as a whole (Sorenson, Taeuber, and Hollingsworth 1975). Income inequality is measured by the Gini index, which expresses the average difference in income between all pairs of individuals in a city relative to the average income of that city (Blau 1977).

Control Variables Population size, the percentage of poor people (measured as the percentage of families below the "poverty line"), and reported crime rates are included as "control" variables. Urbanism theory suggests that a large population is associated with increased reliance on formal means of social control, a traditional Marxian perspective suggests that the poor are least able to resist arrest, and deterrence theory implies that reported crime rates affect crime control. Since theory and research also suggest that these variables are related to the dimensions of racial/economic composition discussed here, their omission from the analysis might bias estimates of the effects of these dimensions on arrest rates.

Analysis Regression analysis is used to estimate the direct effect of the causal variables on arrest rates and their indirect effect on them through their influence on police size. Because of the time lag involved in budget decisions, police size is measured two years later (1972) than the other causal variables (1970). The 1972 budget reflects decisions made sometime in

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late 1971, which can only be based on information (reported crime rates) for 1970 or before. To maintain the logical temporal order between police size and arrest rates, the latter are also measured in 1972.

The equations were first estimated using cross-sectional OLS. Yet, even with the two-year time lag between arrest rates and reported crime rates, this estimation method does not disentangle their effects. If arrest rates decrease crime rates, a lag measure of crime rates (1970) may be affected by past levels of arrest rates, and cross-sectional OLS may yield biased estimates of the effect of reported crime rates (1970) on arrest rates (1972). Therefore, we also estimated the equations using dynamic (cross- lag) OLS and simultaneous equation (2SLS) methods. The dynamic (cross-lag) analysis estimates the effect of the causal variables (1970) on arrest rates (1972) with a lag measure of arrest rates (1967) in the equation, thereby controlling for the effects of arrest rates on reported crime rates. The 2 SLS analysis uses instrumental variables to yield a measure of reported crime rates (1970) purged of the effect of arrest rates. Exploiting the panel design of this research, the analysis uses a lag measure of reported crime rate (1965) as an instrument, thereby circumventing the locating of suitable instruments, a major problem in this research area (Kessler and Greenberg 1981). Because all three estimation methods yield extremely similar estimates, only the cross-sectional OLS estimates are reported in the tables.

RESULTS The analysis proceeds as follows. First, because the conflict perspective suggests that the income inequality effect is contingent on the type of crime (personal or property), the equations are estimated separately for property and personal arrest rates. Second, to isolate the contextual from the aggregate effect of percentage of nonwhites, the property and personal arrest rate equations are estimated separately for whites and nonwhites. Third, in order to examine explicitly the extent to which the benign-neglect process mediates the effects of segregation and the percentage of nonwhites, the robbery equation is estimated for a subsample of cities for which inter- and intraracial robbery rates can be measured.

Property and Personal Arrest Rates Property and personal arrest rates are normally distributed with means of 11.0 and 1.8, and standard deviations of 5.5 and 1.1, respectively, per 1,000 population. Clearly, the chance of being arrested for an index crime is significantly higher in some cities than in others.

Table 1 presents the cross-sectional OLS estimates of the effects of the

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TABLE 1

CROSS-SECTIONAL ESTIMATES OF TOTAL ARREST RATES

PROPERTY PERSONAL

v3 B v B

Populationa ........... .06 .064 - .05 - .010 Police sizea ............. .18 - .986 .15 .163 Poor (%) ............... -.16 -.259 -.03 -.010 Crime ratea ............ .29 .112** .34 .218** Income inequality ....... .25 43.59** .17 6.09* Segregation ............ - .30 - . 180** - .28 - .034** Nonwhite (%) .......... .34 .136** .35 .028**

R2 . . . ..37 .54

a B's are expressed in population units per 100,000, in police per 1,000 population, and in crimes per 1,000 population.

* 1.5 times SE. ** 2.0 times SE.

causal variables on arrest rates. The first and second columns present the standardized (,B's) and unstandardized (B's) coefficients for property arrest rates, and the third and fourth columns present those for personal arrest rates. The correlation matrix was examined for evidence of mul- ticollinearity. Only a few correlations exceed .50, the correlation of .61 between the percentage of nonwhites and of poor people being the strongest. When we reestimated the equations deleting percentage of poor people, the findings did not change significantly from those presented in table 1. The effect of each variable on arrest rates was also estimated by the decrease that occurs in the R2 when it is deleted from the equation; the findings rank the causal variables in the same relative order as do the ,B's in table 1.

The results are clear. The cross-sectional, dynamic, and simultaneous equation estimates all show that only income inequality, segregation, percentage nonwhite, and reported crime rates substantially affect arrest rates. Consistent with the conflict perspective, the effect of income inequality is somewhat stronger for property arrest rates than personal ones, whereas the effects of the other causal variables are about equal for both arrest rates, and the effects of income inequality, segregation, and the percentage of nonwhites are clearly independent of the effect of reported crime rates. Interestingly, police size does not positively affect arrest rates; there are therefore no indirect effects of racial/economic composition on arrest rates through police size, although our research, like past research, shows that racial/economic composition does affect police size.

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Racial Subsamples The observed positive effect of the percentage of nonwhites is difficult to interpret. It may be because nonwhites have a higher arrest rate than whites and therefore, as the percentage of nonwhites increases, the total arrest rate increases (power hypothesis); or it may be because the percentage of nonwhites positively influences not only the arrest rate of nonwhites but even that of whites (threat hypothesis). This is a special case of the classic problem of isolating compositional and contextual effects. The contextual effect is examined here by estimating the effect of the percentage of nonwhites on arrest rates of whites and nonwhites separately, thereby controlling for compositional effects.

The equations were again estimated using cross-sectional, dynamic, and simultaneous equations methods. As before, because the estimates are so similar, we report only the cross-sectional estimates here (table 2). As we expected theoretically, the effects of population size, reported crime rates, income inequality, and the percentage of poor people do not differ significantly among the racial subsamples, although the effect of police size becomes inconsistent, dependent on the type of crime and race. The focus of the racial subsample analysis, however, is on the effect of the percentage of nonwhites. The threat hypothesis suggests that it should be positive, but the benign-neglect hypothesis suggests that it should be negative; both hypotheses suggest that the effect, positive or negative, should be stronger for nonwhites than whites. The estimates support the benign-neglect hypothesis, showing that it is negative and substantially and statistically significant only for nonwhites. In fact, the percentage of nonwhites is the most important variable in the nonwhite equations and about the least important variable in the white equations.

The benign-neglect hypothesis further suggests that the effect of the percentage of nonwhites should be stronger for personal crimes, where victims can frequently identify the race of the offender, than for property crimes, where they cannot. However, the P's (table 2) provide little support for this hypothesis. This may occur because robbery, where victims can identify the race of the offender, is classified as a property crime because it is directed toward property rather than people, which is a major distinction in the income inequality hypothesis. To address this issue further, the equations for nonwhites were estimated for each specific arrest rate. The findings are consistent with the benign-neglect hypothesis.2 For auto theft, burglary, and larceny, where victims cannot

2 For rape, where the victim can also identify the race of the offender, the ,( is only - .11. We are suspicious of this finding, because the total model explains only 3% of the variance in the arrest rate, whereas for the other crimes it explains from 18% to 47%.

390


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generally identify the race of the offender, the P3's for the percentage of nonwhites are - .19, - .21, and - .35, respectively; for assault and robbery, where victims generally can identify the race of the offender, the P3's are -.41 and -.47, respectively; and for homicide, where victims (before they die) and witnesses can sometimes identify the race of the offender, the ,3is -.41.

National Crime Survey Subsample The benign-neglect hypothesis assumes (1) that the percentage of nonwhites and segregation decrease the arrest rate of nonwhites because for nonwhites these variables increase the ratio of intra- to interracial crimes and (2) that nonwhites are arrested less often for intraracial than for interracial crimes. Unfortunately, this process cannot be directly tested with official crime and arrest data because the race of offenders and victim is not recorded. This has been reported for the 26 cities of the National Crime Survey (NCS), 25 of which are included in our sample. The NCS interviewed about 20,000 households in each city from 1972 to 1974 (approximately the years during which our data were collected) and asked the crime victims to identify the race of the offender. This is possi- ble for robbery, rape, and assault. From this data intraracial and interracial crime rates and the proportion of intra- to interracial crime can be estimated. We examined only robbery for nonwhites because the robbery data are thought to be much more reliable than the rape and assault data (Hindelang 1978) and because the proportion of robbery which is intraracial for white offenders is too small to affect white arrest rates significantly.

Because this subsample consists of only 25 cities, the limited degrees of freedom require that the analysis be limited to the following crucial variables: intraracial and interracial robbery rates, the percentage of nonwhites, and segregation. Using OLS, we first estimated the extent to which the percentage of nonwhites and segregation influence the racial composition of robbery. In support of the benign-neglect hypothesis, the ,3 estimates show that both moderately increase the intraracial robbery rate (.27 and .26, respectively) and strongly decrease the interracial robbery rate (- .63 and - .39, respectively), thereby substantially increasing 3 It can be argued that there is a definitional negative correlation between the percentage of nonwhites and the nonwhite arrest rate. Contemporary opinion seems to be that this is not the problem it was once thought to be, especially when, as is the case here, the ratios are theoretical variables, not just constructions for the purpose of standardi- zation (Long 1979). In addition, a definitional correlation cannot account for the fact that the effect of the percentage of nonwhites is strongest for those crimes where the victim can identify the race of the offender-exactly where the benign-neglect hypothesis suggests that it should be strongest.

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Crime Control

the ratio of intra- to interracial crime for nonwhite offenders. Next, we estimated the effects of intraracial robbery, interracial robbery, segregation, and the percentage of nonwhites on the robbery arrest rate. Again, the ,3 estimates support the benign-neglect hypothesis. The effect of interracial robbery (.47) is four times stronger than the effect of intraracial robbery (.12), and a substantial portion of the total negative effect of both segregation and percentage of nonwhites on the robbery arrest rate is mediated through the interracial robbery rate, reflecting the benign- neglect process. Generally, the findings suggest that the percentage of nonwhites is important mostly because it constrains the racial composition of robbery, as its indirect effect through interracial robbery (-.30) is about double its positive direct effect (. 16); and that segregation is important mostly because it reduces the perceived threat of crime, as its direct effect (- .32) is about double its indirect effect (-.18) through interracial robbery.

Of course, these findings must be viewed with caution. Because the subsample is small, the analysis is limited to cross-sectional OLS estimates of equations including only a few variables. Yet the findings provide consistent support for the benign-neglect interpretation of the findings for the full sample.

DISCUSSION This paper, drawing on the conflict perspective and extending studies of police size, examines the effect of racial/economic composition on arrest rates directly and indirectly through its effect on police size.

The analysis shows that the police size effect is inconsistent, varying by type of crime and race, and that it is frequently insignificant substantively and statistically. An explanation for the findings may lie in the allocation of police resources. Organizational theory suggests that, as police departments grow, a greater proportion of their personnel is absorbed by admin- istrative duties, making a lesser proportion directly available for crime control. In fact, Wilson and Boland (1978) report that police size explains only 23% of the variance in the number of police units on the street. Whatever the explanation, in this paper it is important to emphasize that the observed effect of racial/economic composition on arrest rates is not mediated by police size.

Generally, the analysis provides support for the conflict perspective on crime control, showing that the racial/economic composition of cities substantially affects arrest rates.

Economic inequality moderately affects arrest rates for both whites and nonwhites for both personal and property crimes. The findings seem to support the conflict perspective thesis that income inequality accentuates

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economic conflict and the greater the economic inequality and conflict, the greater the disposition of dominant groups to use coercion to maintain a social order favorable to their interests. Yet, more research is required to document that this process underlies the income inequality effect, because, although the formulation and enforcement of numerous laws may be explained in terms of ruling class interests (Chambliss and Seidman 1982), the control of urban street crime seems to be in the interests of all economic classes. Indeed, it may be even more in the interests of the blue- collar and lower-middle than of the upper class, which can afford to re- side in relatively safe neighborhoods, locate businesses in these neighborhoods, and insure its property against theft.

A segregation effect is clearly evident for both races for property and personal arrests, supporting both the threat and benign-neglect hypotheses of the conflict perspective. The analysis of the NCS subsample provides further support for the benign-neglect hypothesis, showing that a substantial portion of the segregation effect on nonwhite arrest rates is mediated through its effect on the racial composition of crime. Yet, a substantial direct effect remains, suggesting that other processes, such as perceived threat, may also be operating.

The effect of the percentage of nonwhites is a function of both compositional and contextual effects. Although the total effect cannot be precisely partitioned into these effects without data on both individual and social units, the analysis of the arrest rate disaggregated by race suggests a negative contextual effect for nonwhites; as the percentage of nonwhites increases, the arrest rate of nonwhites decreases. Note that this theoretically significant contextual effect is obscured when the total arrest rate is not disaggregated by race. Because nonwhite arrest rates are so much higher than white arrest rates (five times higher for property and six for personal), an increase in the percentage of nonwhites increases the total arrest rate, even though it actually substantially decreases the nonwhite arrest rate. The contextual effect of the percentage of nonwhites supports the benign-neglect hypothesis. Additional support for this process is given in the analysis of NCS cities, which shows that the negative effect of the percentage of nonwhites on the nonwhite robbery arrest rate is completely mediated through its effect on the racial composition of robbery.

In sum, arrest rates are a significant social fact, varying considerably among U.S. cities. Our analysis shows that this variation reflects to a large extent the economic/racial composition of cities, independently of police size and reported crime rates, thus providing support for the conflict perspective. By disaggregating the sample by race and type of crime and by examining a subsample of cities where the racial composition of robbery can be measured, the analysis further examines power, threat,

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and benign-neglect processes assumed to underlie the effect of economic/ racial composition on arrest rates.

REFERENCES

Blau, Peter M. 1977. Inequality and Heterogeneity. New York: Free Press. Chambliss, William J., and Robert B. Seidman. 1982. Law, Order and Power. Read-

ing, Mass.: Addison-Wesley. Federal Bureau of Investigation. 1972. Uniform Crime Reportsfor the United States.

Washington, D.C.: Government Printing Office. Hindelang, Michael J. 1978. "Race and Involvement in Crimes." American Sociolog-

ical Review 43 (February): 93-109. Jackson, Pamela Irving, and Leo Carroll. 1981. "Race and the War on Crime."

American Sociological Review 46 June): 290-305. Jacobs, David. 1979. "Inequality and Police Strength." American Sociological Review

44:913-24. . 1978. "Inequality and the Legal Order: An Ecological Test of the Conflict

Model." Social Problems 25 (June): 5 15-25. Kessler, Ronald C., and David F. Greenberg. 1981. Linear Panel Analysis: Models of

Quantitative Change. New York: Academic Press. Liska, Allen E., Joseph J. Lawrence, and Michael Benson. 1981. "Perspectives on the

Legal Order: The Capacity for Social Control." American Journal of Sociology 87 (September): 413-26.

Lizotte, Alan J., and David J. Bordua. 1980. "Firearms Ownership for Sport and Protection." American Sociological Review 45 (April): 229-43.

Loftin, Colin, David F. Greenberg, and Ronald C. Kessler. 1981. "Income Inequality, Race, Crime, and Crime Control." Paper presented at the annual meeting of the American Society of Criminology.

Long, Susan B. 1980. "The Continuing Debate over the Use of Ratio Variable: Fact and Fiction." Pp. 37-67 in Sociological Methodology, edited by Karl F. Schuessler. San Francisco: Jossey-Bass.

S0renson, Annemette, Karl E. Taeuber, and Leslie J. Hollingsworth, Jr. 1975. "In- dexes of Racial Residential Segregation for 109 Cities in the United States, 1940- 1970." Sociological Focus 8:125-42.

Spitzer, Steven. 1975. "Toward a Marxian Theory of Deviance." Social Problems 22 (June): 638-51.

Swigert, Victoria L., and Ronald A. Farrell. 1976. Murder, Inequality and the Law: Differential Treatment in the Legal Process. Lexington, Mass.: Heath.

Turk, Austin T. 1969. Criminality and Legal Order. Chicago: Rand McNally. Williams, Kirk and Susan Drake. 1980. "Social Structure, Crime and Criminalization:

An Empirical Examination of the Conflict Perspective." Sociological Quarterly 21 (Autumn): 563-76.

Wilson, James Q., and Barbara Boland. 1978. "The Effect of the Police on Crime." Law and Society Review 12 (Spring): 366-90.

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Issue Table of ContentsAmerican Journal of Sociology, Vol. 90, No. 2, Sep., 1984Front MatterKarl Marx and the Satanic Mills: Factory Politics Under Early Capitalism in England, the United States, and Russia [pp.247-282]The Cumulative Texture of Local Urban Culture [pp.283-304]Black Family Formation and Tenancy in the Farm South, 1900 [pp.305-325]The Transition from Youth to Adult: Understanding the Age Pattern of Employment [pp.326-358]Trends in Parental Socialization Values: Detroit, 1958-1983 [pp.359-382]Research NotesSocial Structure and Crime Control Among Macrosocial Units [pp.383-395]The Dynamics of Self-Esteem and Delinquency [pp.396-410]Military Keynesianism in the United States, 1949-1976: Disaggregating Military Expenditures and Their Determination [pp.411-417]

Commentary and DebateComment on Denzin's "Note on Emotionality, Self, and Interaction" [pp.418-422]Reply to Baldwin [pp.422-427]Comment on Barrie S. Morgan's "An Alternate Approach to the Development of a Distance-Based Measure of Racial Segregation" [pp.427-428]The Utility of Distance-Based Segregation Indexes: Reply to Mitra [pp.428-429]A Defense of Rational Sociological Discourse [pp.429-431]What Is Rational, What Is Not: Reply to Mnch [pp.432-434]

Review EssayCenturies of Death and Dying [pp.435-439]

Book Reviewsuntitled [pp.440-442]untitled [pp.443-444]untitled [pp.444-445]untitled [pp.445-447]untitled [pp.448-449]untitled [pp.450-453]untitled [pp.453-455]untitled [pp.455-457]untitled [pp.457-458]untitled [pp.459-461]untitled [pp.461-463]untitled [pp.463-464]untitled [pp.465-466]untitled [pp.466-469]untitled [pp.469-471]untitled [pp.472-474]untitled [pp.474-475]untitled [pp.475-477]untitled [pp.477-480]untitled [pp.480-482]

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