ABSTRACT

This study will examine the relationship between city-level structural factors and interracial homicide rates. Specifically, we will use data from the Supplemental Homicide Reports, the U.S. Census, and the Uniform Crime Reports to test the assumption that racial antagonism and conflict mediate the relationship between racial inequality and interracial homicide, and to assess an alternative hypothesis that draws on macro-structural opportunity theory and the routine activities perspective to understand the racial inequality-interracial homicide relationship. First, we will focus on the prevalence, the nature, and the motivation of different subtypes of interracial killing, and examine the structural predictors of those subtypes. We suggest that the motivation of the homicide, largely ignored in previous research, is the best indicator of the mechanism by which structural characteristics can influence interracial killing (homicides with expressive motives are more likely to be manifestations of antagonism and conflict than those with instrumental motives). We will then determine whether robbery rates mediate the relationship between racial inequality (and other structural characteristics) and interracial homicide. If this is the case, we argue that it is premature to suggest that racial antagonism and conflict mediate the racial inequality-interracial homicide relationship, and instead propose that the relationship may be the result of a combination of racial interaction and patterns of economic crime.

 


INTRODUCTION

Interracial homicide is one of the most discussed, yet least studied, types of violence in America. While theories abound, there has been little empirical consensus concerning an explanation for variation in rates of interracial killing. One argument is that competition for jobs and political power fuels racial antagonisms which, in turn, engender interracial violence. Studies that adopt this perspective predict that cities with greater levels of racial inequality and/or racial competition will have greater rates of interracial killings, controlling for other factors. While some empirical support for this argument has been documented (Balkwell 1990; Jacobs and Wood 1999; Parker and McCall 1999) and these studies are provocative, they do not provide a decisive test because they fail to directly measure the social psychological process hypothesized to mediate the racial inequality-interracial homicide relationship. That is, the hypothesized relationship looks like this: Racial Inequality/Competition à  Racial Hostility à  Interracial Homicide. Yet, the intervening mechanism—racial hostility—has gone largely unmeasured. This is because all of these studies have used aggregate-level data, which precludes the measurement of racial hostility, generally considered to be an individual-level measure. While it may be possible to identify aggregate measures of racial hostility independent of interracial violence, this has not been demonstrated in the literature. This being the case, there is a risk of incorrectly identifying the causal processes driving variation in interracial homicide.

The objective of the study is to empirically evaluate the causal mechanisms that have been proposed in previous research and to test an alternative hypothesis that incorporates the homicide motive. We will do this first by focusing on the prevalence, the nature, and the motivation of different subtypes of interracial killing, and by examining the structural predictors of the different subtypes. Despite a rigorous search, we were unable to locate any study that examines interracial homicide rates disaggregated by motive. We will then determine whether the relationship between macro-structural characteristics and interracial homicide can be explained, in part, by high rates of other types of crime, such as robbery. We believe this dual-pronged approach can significantly advance our understanding of the causes of interracial homicide. The goal of this study is to answer a set of questions we believe will shed light on the processes by which macro-structural factors can influence rates of interracial homicide:

 

1)                           What structural characteristics explain variation in rates of interracial homicide across U.S. central cities? For example, how are racial inequality and opportunities for interracial contact (both measured in various ways), among other factors, related to interracial killings?

 

2)                           Does the influence of these structural characteristics on interracial killing vary depending on the motive of the homicide? That is, is the effect of racial inequality (and other factors) larger or smaller if the interracial homicide occurs during an economically-motivated crime (versus during an argument or fight)?

 

3)                           How do rates of other types of criminal behavior (e.g., robbery) influence rates of interracial homicide? Can variation in rates of non-lethal economically-motivated criminal behavior explain, in part, the relationship between macro-structural characteristics and interracial homicide?

 

We elaborate the logic of these questions and the theoretical basis for our predictions below.

 

THEORETICAL BACKGROUND

Explanations for interracial homicide have emerged from two different perspectives. One approach, informed by Blau’s (1977) macrostructural opportunity theory and elements of the general criminal opportunity perspective, focuses on opportunities for intergroup contact as a central factor influencing interracial violence. This perspective argues that interracial homicide, like interracial marriage, is a byproduct of intergroup contact. The likelihood of killing someone, or marrying someone, of another race is significantly influenced by the amount of interracial contact in a given area. According to Blau, opportunities for such contact are shaped, primarily, by the fundamental properties of urban social structure. For example, one such property is racial inequality. Inequality refers to the differences among persons with respect to status characteristics such as education, income, wealth, and prestige. Inequality has a distinctive effect on associations when it is correlated with group membership. For example, when race is strongly correlated with socioeconomic status, opportunities for contact between members of different groups are likely to be infrequent. Macrostructural opportunity theory therefore proposes that racial inequality will reduce opportunities for contacts between members of different races, which, in turn, reduces the probability of interracial associations. As a result, racial inequality will be negatively related to interracial homicide. Likewise, other factors that directly affect opportunities for interracial contact—such as racial residential segregation and racial heterogeneity—are also hypothesized to influence interracial homicide.

Recent advances extend Blau’s theoretical framework by incorporating insights from the criminal opportunity perspective (Messner and South 1992). This approach derives largely from the routine activities perspective (Cohen and Felson 1979), which argues that for a successful criminal victimization to occur, a motivated offender must come into contact with a suitable target in the absence of guardians who could intervene and prevent victimization. The criminal opportunity perspective suggests that routine activities (e.g., employment status or living in a racially heterogeneous area, etc.) that encourage members of different races to interact more frequently are likely to influence levels of interracial killings.

Another explanation for interracial homicide focuses less on opportunities for intergroup contact and more on the motivation for intergroup homicide. Of importance here is the extent to which structural conditions operating in urban areas contribute to competition and conflict between racial groups. Social psychological processes such as frustration-aggression, racial antagonism, black rage, and stress-anger-displacement are used to explain the observed relationships between macro-structural characteristics such as racial inequality and interracial homicide (Balkwell 1990; Jacobs and Wood 1999; Olzak et al. 1996). For example, Blau and Blau (1982) posit that racial inequality leads to strong pressures to commit violence and that this process derives from the inherent contradiction between ascriptive inequality and democratic values. Key to this argument is the fundamental principle in democratic societies that rewards should be distributed in accordance with merit and effort. Thus, persons who receive meager rewards because of their race are likely to develop feelings of resentment, frustration, and hostility, which are likely to be expressed through aggression. This perspective predicts that racial inequality will be positively related to interracial homicide.

Empirical research that has examined the relationship between racial inequality and interracial homicide has been inconsistent. Messner and South (1992) find reasonably strong support for macrostructural opportunity theory; cities with extreme socioeconomic differentials between blacks and nonblacks have relatively low levels of interracial homicide, controlling for other factors. Messner and South argue that this is so presumably because the consolidation of race with socioeconomic status inhibits the formation of interracial associations. On the other hand, Parker and McCall (1999) and Jacobs and Wood (1999) find a positive relationship between racial inequality (measured in various ways) and interracial homicide, and conclude that economic inequalities rooted in ascribed positions likely create alienation, despair, and conflict—all of which are associated with higher levels of intergroup violence, and most consistently, with black interracial homicide.

One major concern with the empirical literature is that the relationship between racial inequality and rates of homicide in conflict-based explanations often suggests specific social psychological processes, most of which are not tested in structural analyses of interracial killings. Given the difficulty with measuring such processes, particularly in national studies, this is understandable. Still, the implied micro-macro linkage has not been adequately analyzed which raises questions about its validity. While the proposed study does not measure the social psychological assumptions that underpin conflict-based explanations of violence, it contributes to the debate in two ways. First, we examine a thus far unexamined aspect of the racial inequality-interracial homicide relationship: motive of the homicide. Second, we determine whether rates of robbery mediate the influence of racial inequality on interracial homicide.

Concerning point one, findings from a number of studies underscore the importance of disaggregating by motive when determining the structural characteristics of homicide (Kubrin forthcoming, Kubrin and Wadsworth forthcoming; Parker and McCall 1999; Peterson and Krivo 1993; Williams and Flewelling 1988). The motive of the homicide is especially critical for understanding interracial killings because it is our best indicator of the underlying social psychological processes that fuel lethal violence. We argue that altercation-based or other expressive interracial homicides, more so than robbery or other instrumental homicides, better reflect the causal mechanisms (e.g., racial hostility) that have been proposed in previous research. If these causal processes are accurate, the relationship between racial inequality and interracial homicide will be stronger for expressive altercation-based killings than for instrumental homicides motivated by economic gain.

Point two assesses another possible explanation for the variation in rates of interracial homicide. This approach may be included under the umbrella of macrostructural opportunity theory, and draws from ideas utilized in the routine activities perspective. We posit that high rates of interracial killing may be the result of an interaction between high rates of interracial contact and high rates of interpersonal crime (e.g., robbery), which intentionally or unintentionally, can lead to homicide. Put simply, some cities may have more interracial killings because they have higher rates of robbery and because blacks and whites interact more frequently in public spaces. Robbery creates a context in which an interaction between two people (independent of race) is likely to turn violent. Thus the combination of high rates of interracial interaction with high rates of robbery creates an increased likelihood, independent of racial conflict or antagonism, of interracial homicide.

If it is the case that robbery rates are strong predictors of interracial homicide, and may in fact mediate the influence of macro-economic factors on interracial killing, we suggest that attributing high interracial homicide rates to social psychological processes stemming from antagonistic race relations is premature. While this explanation cannot be ruled out (or confirmed) without empirically measuring the processes, a more suitable explanation may be related to the calculation used to choose a suitable target for a predetermined criminal offense. In this study, we propose two empirical models (described below) that will address these issues.

 

METHODOLOGY: DATA, MEASURES AND ANALYSES

Supplemental Homicide Reports: We propose to use race-adjusted Supplemental Homicide Report (SHR) data from 1985-1995 to generate rates of overall and subgroup-specific interracial homicide for the U.S. central cities with populations of over 100,000 in which African-Americans make up at least 5% of the population. Our interest in computing race-specific measures imposes this selection criterion to ensure reliable estimates of racially disaggregated homicide rates (Krivo and Peterson 2000; Parker and McCall 1999). The SHR data are collected and compiled by the FBI as part of the UCR Program, and provide incident-level details on the location, age, sex, and race of the victims and offenders, the victim-offender relationship, weapons used, and the circumstances of the homicide (Fox 2001). Race-adjusted data are used in order to address important missing data issues discussed by Williams and Flewelling (1988) (for an explanation of why this is necessary, see Appendix B).

Consistent with past research, our unit of analysis is the central city. Parker (1989) suggests that the central city is the most appropriate level of aggregation for two reasons. First, given the geopolitical process by which SMSAs (a larger level of aggregation) are designated, these units can be very heterogeneous. Such heterogeneity can mask meaningful relationships between structural characteristics and patterns of behavior. Central cities tend to be more homogenous in patterns of land use and the distribution of human activity. Second, homicide is, for the most part, a central city phenomenon. Parker’s (1989:994-95) analysis shows that roughly 80 percent of the homicides took place within the boundaries of the central city.

            In creating rates of interracial homicide, we limit our analysis to murders and non-negligent homicides with a single victim and single offender. This approach is consistent with previous research (Kovandzic et al. 1998; Messner and South 1992; Miethe and Drass 1999; Parker and McCall 1999). SHR data only have information on the first victim and offender in cases where there are multiple victims and/or offenders, making it impossible to determine the characteristics (by which to classify the homicide) for the second and subsequent victims and/or offenders.

            Given the relative rarity of interracial killings disaggregated by motive, this research users data from 1985-1995 in order to increase the number of interracial killings with different motives, a common practice in the literature (Jacobs and Wood 1999; Kubrin forthcoming; Kubrin and Wadsworth forthcoming; Morenoff and Sampson 1997; Parker and Pruitt 2000). This is necessary, as creating rates from fewer years would result in many cities having few or no recorded interracial homicides, thus skewing the distributions toward zero.[1]

            We will use the race-adjusted SHR data to compute thirteen city-level outcome measures representing various rates of inter- and intraracial homicide. These include five non-motivation-specific measures including the total rate of interracial homicide (based on blacks killing whites [B-W] and whites killing blacks [W-B]), the rates of B-W, B-B, W-B, and W-W homicide. The remaining eight motivation-specific outcome variables include the rates of B-W, B-B, W-B, and W-W financially-motivated and non-financially-motivated homicides.

Census Data: We regress the overall and subtype-specific homicide rates on the structural characteristics and crime rates of U.S. central cities. Information on the structural characteristics comes from the 1990 U.S. Census. Measures representing region, overall income inequality, racial inequality, interracial contact, as well as overall and racially disaggregated measures of population size, poverty, per capita income, unemployment levels, and female-headed households will be included in the analyses. Region will be measured as a series of dummy variables. As in previous research, overall income inequality is measured using the Gini Index of Family Income Concentration (Kovandzic et al. 1998, Parker and McCall 1999). There will be three measures of racial inequality that reflect racial differences in education, income, and employment opportunities (Messner and Golden 1992). Racial income inequality is operationalized as the ratio of white to black median income. The ratio of white to black median years of schooling for the respective populations aged 25 and over serves as an indicator of educational inequality. Lastly, the ratio of white to black unemployment rates is used as a measure of inequality in employment opportunity. Depending on the correlations between these measures and results from collinearity diagnostics, it is likely that the three indicators of inequality will be combined using factor analysis. To measure levels of interracial interaction, we use indicators of racial heterogeneity (Lieberson 1969:851), residential segregation (index of dissimilarity), and exposure and isolation indices (p*) (Massey and Denton 1993). Total and racially disaggregated measures of the other variables will also be computed from the census data.

Uniform Crime Report Data: To examine the influence of rates of financially-motivated crime on interracial homicide, central city robbery rates will be generated from the 1989-1991 UCR, and will be included in some analyses discussed below.

 

Models and Analyses

            The two sets of models to be tested are both aggregate level models that use the central city as the unit of analysis. In the first set of models, we disaggregate homicide by both the race of the offender and victim as well as the circumstances under which the homicide took place. The circumstance of the homicide (e.g., robbery, argument) is a good indicator of the motive behind the killing.[2] This disaggregation process will be used to create dependent variables representing the rates of a variety of different types of interracial and intraracial homicide (e.g., B-W financially motivated, B-W non-financially motivated, etc.).

If interracial homicide stems from a process in which macro-structural forces encourage social psychological processes such as frustration-aggression, black rage, or racial antagonism, we would expect the factors driving these processes to have a stronger influence on expressive or non-financially motivated killings than instrumental or financially-motivated killings. We would also expect these factors to influence interracial killing more strongly than intraracial killing. To test whether the structural characteristics discussed above are more strongly related to expressive than to instrumental killings, and to interracial vs. intraracial homicide, we will run a series of regressions with various race and motive specific homicide rates as the dependent variables and employ a standard test for coefficient differences across equations (Kubrin forthcoming; McNulty 2001; Paternoster et al. 1998). Figure 1 offers a graphical representation of some equations that will be tested.

Our second analytic approach treats the total rate of interracial homicide, the rate of B-W homicide, and the rate of W-B homicide as the dependent variables. These rates will be regressed on a number of structural characteristics identified in previous research (Jacobs and Wood 1999; Messner and Golden 1992; Parker and McCall 1999). After attempting to replicate the analyses of previous studies, we will add variables measuring central-city level rates of robbery. The degree to which the effects of macro-structural factors representing racial inequality are attenuated when robbery rates are included in the models offers insight into the process by which structural forces influence interracial homicide. Significant attenuation would suggest that it is the frequency of economically motivated criminal behavior, driven by structural characteristics, that influences interracial homicide. Support for such a finding casts doubt upon, or at least calls into question, explanations that focus on social psychological processes stemming from racial antagonism. Figure 2 offers a graphical representation of this model.

 

PROJECT ORGANIZATION AND TIMELINE

The project will span 1 year from May 1, 2003 - April 30, 2004. The tasks and timeline are as follows: 1st Phase: Data cleaning and the construction of variables. City-level structural characteristics will be created from 1990 Census data and racially and motivationally disaggregated homicide variables will be constructed from the race-adjusted SHR data. We will also perform a thorough review of the literature on interracial homicide. These activities are to be carried out in May and June of 2003. 2nd Phase: Data analysis will be conducted. We will run descriptive analyses first to determine the distribution of rates of disaggregated interracial homicide, and determine their correlates. This disaggregation will be based on victim and offender race and homicide motive. We will then run series of regression analyses that correspond to the conceptual models presented earlier. These activities are to be carried out from July-November of 2003. 3rd Phase: Writing the final report. We will write a final report detailing the study and the major findings. We will also submit our data and supporting documentation. These activities are to be carried out in December 2002 and January 2003. 4th Phase: We will write two to four papers, depending upon the results, which will be submitted to scholarly journals such as Criminology, Journal of Research on Crime and Delinquency, and Homicide Studies for publication. We also intend to submit an abstract to present the major findings at the 2005 American Society of Criminology Conference (abstracts are due in March 2004). Finally, we will present our findings and meet with BJS staff to discuss follow up research. These activities are to be carried out from February-April 2004.

 


 

FIGURES


REFERENCES

 

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70.

 

Blau, Peter M. 1977. Inequality and Heterogeneity. New York: Free Press.

 

Blau, Judith R. and Peter M. Blau. 1982. “Metropolitan Structure and Violent Crime.”

American Sociological Review 47:114-128.

 

Block, Carolyn and Richard Block. 1992. “Overview of the Chicago Homicide Project.” In C. 

Block and R. Block (Eds.), Questions and Answers in Lethal and Non-Lethal Violence: Proceedings of the First Annual Workshop of the Homicide Research Working Group (pp. 97-122). Washington, DC: National Institute of Justice.

 

Cohen, Lawrence C. and Marcus Felson. 1979. “Social Change and Crime Rate Trends.”

American Sociological Review 44:588-607.

 

Fox, James Alan. 2001. Uniform Crime Reports [United States]: Supplementary Homicide

Reports, 1976-1999. ICPSR 3180.

 

Jacbos, David and Katherine Wood. 1999. “Interracial Conflict and Interracial Homicide: Do

Political and Economic Rivalries Explain White Killings of Blacks or Black Killings of Whites?” American Journal of Sociology 105:157-190.

 

Kovandzic, Tomislav, Lynne M. Vieratis, and Mark R. Yeisley. 2001. “The Structural

Covariates of Urban Homicide: Reassessing the Impact of Income Inequality and Poverty in the Post-Reagan Era.” Criminology 36:569-597.

 

Krivo, Lauren J. and Ruth D. Peterson. 2000. “The Structural Context of Homicide: Accounting

for Racial Differences in Process.” American Sociological Review 65:547-559.

 

Kubrin, Charis E. Forthcoming. “Structural Covariates of Homicide Rates: Does Type of

Homicide Matter?” Journal of Research in Crime and Delinquency.

 

Kubrin, Charis E. and Tim Wadsworth. Forthcoming. “Identifying the Structural Correlates of

African-American Killings: What Can We Learn from Data Disaggregation?” Homicide Studies.

 

LaFree, G., Drass, K.A., & O’Day, P. (1992). Race and Crime in Postwar America:

Determinants of African-American and White Rates, 1957-1988. Criminology 30:157-188.

 

Lieberson, Stanley. 1969. “Measuring Population Diversity.” American Sociological Review

34:850-862.

 

Macmillan, Ross and Rosemary Gartner. 1999. “She Brings Home the Bacon: Labor-Force

Participation and the Risk of Spousal Violence Against Women.” Journal of Marriage and the Family 61:947-958.

 

Massey, Douglas S. and Nancy A. Denton. 1993. American Apartheid: Segregation and the

Making of the Underclass. Cambridge: Harvard University Press.

 

McNulty, Thomas. 2001. “Assessing the Race-Violence Relationship at the Macro Level: The

Assumption of Racial Invariance and the Problem of Restricted Distributions.” Criminology 39:467-487.

 

Messner, Steven F. and Reid M. Golden. 1992. “Racial Inequality and Racially Disaggregated

Homicide Rates: An Assessment of Alternative Theoretical Explanations.” Criminology 30:421-447.

 

Messner, Steven F. and Scott J. South. 1992. “Interracial Homicide: A Macrostructural-

Opportunity Perspective.” Sociological Forum 7:517-536.

 

Miethe, Terance D. and Kriss A. Drass. 1999. “Exploring the Social Context of Instrumental and

Expressive Homicides: An Application of Qualitative Comparative Analysis.” Journal of Quantitative Criminology 15:1-21.

 

Miles-Doan, Rebecca. 1998. “Violence Between Spouses and Intimates: Does Neighborhood

Context Matter?” Social Forces 77:623-645.

 

Morenoff, Jeffrey D. and Robert J. Sampson. 1997. “Violent Crime and the Spatial Dynamics of

Neighborhood Transition: Chicago, 1970-1990.” Social Forces 76:31-64.

 

O’Brien, Robert M. 1987. “The Interracial Nature of Violent Crimes: A Reexamination.”

American Journal of Sociology 4:817-835.

 

Olzak, Susan, Suzanne Shanahan, and Elizabeth H. McEneaney. 1996. “Poverty, Segregation,

and the Race Riots: 1960 to 1993.” American Sociological Review 61:590-613.

 

Ousey, Graham C. 1999. “Homicide, Structural Factors, and the Racial Invariance Assumption.”

Criminology 37:405-425.

 

Parker, Robert Nash. 1989. “Poverty, Subculture of Violence, and Type of Homicide.” Social

Forces 67:983-1007.

 

Parker, Karen F. and Patricia L. McCall. 1999. “Structural Conditions and Racial Homicide

Patterns: A Look at the Multiple Disadvantages in Urban Areas.” Criminology 37:447-473.

 

Parker, Karen F. and Matthew V. Pruitt. 2000. “Poverty, Poverty Concentration, and Homicide.”

Social Science Quarterly 81:555-570.

 

Peterson, Ruth D. and Lauren J. Krivo. 1993. “Racial Segregation and Black Urban Homicide.”

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Shihadeh, Edward S. and Darrell J. Steffensmeier. 1994. “Economic Inequality, Family

Disruption, and Urban Black Violence: Cities as Units of Stratification and Social Control.” Social Forces 73:729-751.

 

Williams, Kirk R. and Robert L. Flewelling. 1988. “The Social Production of Criminal

Homicide: A Comparative Study of Disaggregated Rates in American Cities.” American Sociological Review 54:421-431.

 


APPENDIX A

 

BUDGET

(more)


APPENDIX B

 

RACE-ADJUSTED SHR DATA

The race adjustments take into account two otherwise problematic sources of missing data. First, some cities fail to submit homicide reports each year, and while counts are usually available through the UCR, the race and sex of the offender and victim, as well as other characteristics of the homicide, are unknown. The adjustment procedure estimates the characteristics of the offenders, the victims, and the crimes based on all of the known characteristics of the reported events.

The second issue arises because some killings go unsolved and there is no information on the offender. If unsolved homicides were a random selection of all homicides, the process discussed above could be used to impute missing offender information. However, this is not the case. The likelihood of solving a homicide is directly influenced by the circumstances of the crime and the relationship between the victim and offender; homicides between non-strangers are more likely to be solved than homicides between strangers. Given patterns of social interaction, interracial more so than intraracial homicides occur between strangers, and therefore represent a disproportionate number of unsolved killings. An imputation process that ignores this is likely to underestimate the frequency of interracial homicide. The race-adjusted SHR data correct for this by drawing on the available characteristics of the unsolved homicides and those of the solved homicides to impute missing offender characteristics for unsolved killings. Nearly all studies that use SHR data to examine racially disaggregated homicide rates utilize a race-adjusted count (Kovandzic et al. 1998; Krivo and Peterson 2000; Parker and McCall 1999).


 

APPENDIX C

 

 

ANTICIPATED RESULTS AND PRODUCTS

            This project will increase our understanding of interracial homicide, and the structural correlates that contribute to this form of violence. We will build on recent work by challenging the assumption that racial inequality and other structural forces are linked to higher rates of interracial killing through racial hostility and antagonism, and by offering an alternative hypothesis that incorporates the motive of the homicide—an important yet thus far unexamined aspect of the racial inequality-interracial homicide relationship. This study will also determine how rates of other types of criminal behavior such as robbery influence rates of interracial homicide. In addition to theoretical development, we believe that our findings can potentially make a substantial contribution to policy aimed at reducing both inter- and intra-racial violence.

Previous results from research conducted by the P.I.s have been published in various refereed academic journals including Journal of Research in Crime and Delinquency, Social Forces, and Homicide Studies. Results have also been presented at numerous academic conferences including the American Society of Criminology and Academy of Criminal Justice Sciences conferences. We expect that this publication and presentation record will be sustained with this project.


APPENDIX D

 

STAFF/MANAGEMENT PLAN

The research team includes two P.I.s who bring different areas of expertise and research skills to the project. Charis E. Kubrin (Assistant Professor of Sociology and Senior Fellow at the Institute on Crime, Justice and Corrections at George Washington University) has expertise in aggregate-level analyses of homicide rates, statistical methods, and has published a number of studies on race and violent crime. She has received funding from the National Science Foundation, the National Consortium on Violence Research, and the SOROS Foundation to conduct a variety of studies all of which deal with race and crime. Her two most recent publications examine the structural correlates of homicide rates, and an earlier publication examines how changes in racial composition of neighborhoods have influenced changes in violent crime rates in the last decade. Tim Wadsworth (Assistant Professor of Sociology at University of New Mexico) has expertise in individual and aggregate-level analyses of labor market participation, industrial composition, and criminal behavior. He has received funding from the National Institute of Justice to conduct studies focusing on individual employment, city and county labor market characteristics, racial segregation, and violent criminal behavior. His most recent publications examine the influence of race and poverty on violent crime.

 


APPENDIX E

 

CURRICULUM VITAE



[1] One potential problem with using homicide data that span a 10-year period is that the results of the analyses could be affected if one or more of the motive subtypes became more or less prevalent over time. Drastic overtime changes in the proportion of homicides with different motives can lead to misleading results for the structural covariates. We examined the subtypes for each year between 1985 and 1995 and found that the percentage of interracial homicides that were financially motivated ranged from 16.8% to 20.4%. This provides strong evidence that the mixture of interracial homicide types remained relatively invariant over the 10-year period.

[2] As motivation stems from the mental or emotional process of the offender (be it conscious or unconscious), researchers are rarely able to confidently identify the precise motive of any crime. However, the circumstances surrounding the crime provide enough information to categorize the offense as financially motivated or not. Thus for our purposes, circumstance acts as a very good, yet imperfect, indicator of motive.