Violent Crime and Rural Life: A Test of Social Disorganization Theory in Virginia and West Virginia Counties

 

By Sheryl L. Van Horne

Penn State University

 

 

Abstract

 

 

Historically there has been very little attention given to crimes in rural areas. This study examines what effect 'rurality' has on structural explanations of crime and applies variables related to social disorganization at the county level, while controlling for 'rurality' and examining the role that 'rurality' plays.

It has long since been assumed that social disorganization theory applies to urban areas, but logic dictates that structural concerns can also affect rural areas.

This study examines both traditional measures of social disorganization theory, as well as variables related to the systemic reformulation of social disorganization theory, using 2000 U.S. Census data, Voter Participation Data, and the FBI's 2000 Uniform Crime Reports.

The specific structural concerns that are measured include: family disruption, unemployment, poverty, and community cohesion/participation.

 

 

Social Disorganization Theory

               Social disorganization theory has its origins in Durkheim’s (1933) concept that crime is normal when there is a breakdown of social controls; this breakdown of social controls is associated with rapid social change. Social disorganization theory arose out of a study in Chicago where Shaw and McKay (1942) found that structural processes explained delinquency. In fact, Shaw and McKay expanded Park and Burgess’ notion that cities expand and “grow radially in a series of concentric zones or rings” (Palen 1981: 107). According to Park and Burgess, the transition zones were of the utmost concern, since they resulted in residents being displaced due to the outward push of the business district. Shaw and McKay (1942) examined specific structural variables including residential mobility, poverty, ethnic heterogeneity, and family disruption and found them to be correlated to juvenile delinquency.

Since then, there have been slightly different conceptualizations of social disorganization. For example, Bursik (1988) defines social disorganization as “an inability of community members to achieve shared values or to solve jointly experienced problems’ (as cited in Osgood and Chambers 2003: 1). Bursik and Webb (1982) explain that the greater residential instability in a neighborhood, the greater the difficulty in preventing or controlling crime, since formal and informal associations within the community cannot be maintained over time. Veysey and Messner (1999: 159) explain social disorganization as operating “through the processes of value and norm conflicts, cultural change and cultural vacuums, and the weakening of primary relationships” which lead to a reduction in both internal and external social control.

Additional research has expanded the understanding of social disorganization. Kasarda and Janowitz (1974) understood the local community to be a “complex system of friendship and kinship networks and formal and informal associational ties rooted in family life and ongoing socialization processes…fashioned by the large scale institution of mass society” (329). According to their understanding of social disorganization theory, one of the most important variables is length of residency. The idea is that the longer one resides in an area the more likely they will be assimilated to the culture (Kasarda and Janowitz 1974). In their study they examined five key independent variables: population size, population density, length of residency, social class, and stage in life cycle (dichotomized as 21-49 or 50 and over) and examined their impact on local social bonds. They found that the size and population density were not as significantly related to attachment to the community as was length of residency.  According to Sampson and Groves (1989), crime occurs as a result of social disorganization in that it reduces friendship networks, leads to a reduction of involvement in the community and community organizations, and leads to a reduction in the supervision of juveniles. Social disorganization correlates to increases in the deviant associations of individuals in the community (Cattarello 2000). Stark (1987) emphasizes the importance of variables such as population density, population mobility, poverty, land usage, and building conditions when examining crime rates.

Further research has incorporated the importance of institutions. Kornhauser’s (1978) examination of social disorganization theory as a model of social control spurred a renewed emphasis in the research on social disorganization theory, and, more specifically, allowed for the emergence of the systemic reformulation of social disorganization theory. More recently, Bursik and Webb (1982) explain that the greater residential instability in a neighborhood, the greater the difficulty in preventing or controlling crime, since formal and informal associations within the community cannot be maintained over time. Even more recent research has focused on poverty as a key variable because it can influence mobility and racial heterogeneity (Bursik and Grasmick 1993).

Even more recently the term collective efficacy has been used to refer to neighborhoods that are not socially disorganized. Taylor (2001: 128) describes a neighborhood high in collective efficacy as one where “residents will work together on common, neighborhood-wide issues, will get along somewhat with one another, and will take steps to supervise activities of youth or teen taking place in the immediate locale”. Taylor (2001: 128) mentions too that an area with collective efficacy has informal social control and organizational participation. The levels of social control that play a role in social disorganization are private, parochial, and public (Bursik and Gasmick 1993). Private controls are those that are exercised by parents, family, and friends, while parochial controls are those exercised by acquaintances and neighbors, and public controls are those having to do with outside influences such as governmental agencies. Bursik and Grasmik (1993:17) describe the parochial level controls as described by Hunter (1985) as functioning through “the effects of the broader local interpersonal networks and the interlocking of local institutions such as stores, schools, churches, and voluntary organizations”.

               There are a number of studies that have found a relationship between incivilities, such as “untended property” or “untended people and behavior” (Wilson and Kelling 1985). Specifically these incivilities include graffiti, broken windows, winos in doorways, and the presence of illegal drug activities (Covington and Taylor, 1991; Lewis and Salem, 1981; Rohe and Burby 1988). Such conditions have been referred to as “signs of crime” (Skogan and Maxfield 1981), “early signs of danger” (Stinchcombe et al. 1980), disorder (Skogan 1990), a “preclude to trouble” (Skolnick 1966), and “cues to danger” (Warr 1990). Thus, such conditions are important, and they may be relevant to a study of social disorganization, being indicators of disorganization themselves.

 

 

The Shift in Importance of Rural Crime

Historically, social disorganization theory has been applied predominantly to urban areas. Sampson and Groves (1989) tested 238 British neighborhoods and found that the four specific components of social disorganization are low economic status, population heterogeneity, high mobility of residents, and broken homes and disrupted families. Rural areas of the country have been historically presumed to be relatively organized in numerous informal ways, although recently there is research to indicate that in areas of social disorganization, that disorganization is correlated to crime. Rural communities have typically been thought of as “small, unconcentrated and relatively isolated from the influence of large metropolitan centers” (Miller and Luloff 1981: 610). Bottoms (1994: 648) indicates that, “one of the most obvious of such influences [on criminal behavior] is whether one lives in an urban or a rural environment”. Thus, the primary focus of research on social disorganization theory has been at the neighborhood level within urban areas.

Yet, most people do not live in urban areas. Hobbs (1994) notes that 88 percent of the American communities have fewer than 10,000 people. Additionally, research has shown that crime rates in the United States have been declining, but further investigation reveals that since 1980 violent crimes have become a greater proportion of crime in Appalachia (Cameron 2001: 2).[1]  In the early 1980s the rural homicide rates were higher than homicide rates in most U.S. cities (Wilkinson 1984), although homicide is still relatively unusual in most non-Metropolitan areas. 

The central Appalachian region, including many counties of West Virginia and Virginia, have experienced strong levels of out-migration (Duncan 2001 60-86), underemployment, a decline of two-parent families (Friedman & Lichter 1998: 91-109), and significant economic underdevelopment (White 1987: 47-66).  Each of these variables is related to a significant component of social disorganization theory and may help explain violent crime rates in rural and non-metropolitan areas of Virginia and West Virginia. Across the country there have been rural areas with high violence and homicide rates (Montell 1986). In examining rural crime trends over time, they have sometimes followed the patterns of the cities, but have occasionally not. For example, from 1966 to 1997 violent crime in urban areas increased until about 1991 then declined, whereas in rural areas there was a constant increase throughout that period (Weisheit and Donnermeyer 2000). In addition, Weisheit and Donnermeyer (2000: 314) note that while rural murder rates did not change significantly for that period of time, larceny, rape and aggravated assault rates tripled, and robbery, burglary, and motor vehicle theft rates doubled. It is also possible that crime rates in urban areas affect surrounding non-urban areas since geographic regions do not operate in a vacuum and the boundaries between places may be more artificial than real. Fischer (1980) examined violent crime data from California counties and concludes that changes in rates in rural counties were preceded by changes in the rates of urban counties, after first diffusing to smaller cities. Thus, studying non-metropolitan crime is important to improving our understanding of crime generally, and to address important policy implications of such information.

Additionally, it is important to criminology and criminological theory to test and retest theories. A theory that applies to a more diverse area or population is a better theory. Osgood and Chambers (2000: 82) note that “the rural-urban dimension is itself an essential aspect of communities, and our current theories of communities and crime would be far more useful if they apply to the entire range of this dimension”. Osgood and Chambers (2003) reiterate the fact that applying theory to different types of places make the theory much stronger. There has been, and continues to be, an association between urban areas and crime. Certainly, crime occurs in rural areas as well and it is important to understand the trends throughout the United States, not just in urban areas.

Although a few tests of social disorganization theory have been applied to rural areas, there is still much to be examined. Of the few studies focusing on crime in rural areas that exist, some focus on youth violence (Osgood and Chambers 2000), while some focus on rural areas in Australia (Jobes et al. 2004). Social disorganization theory has been used to analyze homicide rates among American Indians on reservations (Bachman, 1991). A few more recent studies have applied social disorganization theory to rural areas with success. For example, in one study in Australia researchers found that some structural aspects of rural places were linked to crime (Jobes et al. 2004). Donnermeyer and Jobes (2000: 461) note that social disorganization theory “has been especially important in helping to bring rural areas into the mainstream of criminological research and theory in the past decade.” Arthur (1991) found that unemployment, poverty, public aid, and race were related to both property and violent crime rates in 13 rural Georgia counties. While not a study focusing completely on crime in rural areas per se, Osgood and Chambers (2003) examined the relationship between youth violence and social disorganization theory in non-Metropolitan counties in Florida, Georgia, Nebraska, and South Carolina. Thus, tests of social disorganization theory in rural areas are important not only in explaining crime, but also in that they have been instrumental in putting rural crime on the map as something in need of study and concern.

 

 

Methods

This analysis aims to answer whether violent crime in Virginia and West Virginia counties of the country can be explained by examining structural variables, namely by using social disorganization theory, and to what extent such variables correlate to violent index crimes (defined as murder, rape, robbery, and aggravated assault). Additionally, this research seeks to examine whether the systemic reformulation is a better predictor of violent crime than the traditional model of social disorganization model. Studies examining the role of structural correlates of crime have traditionally focused on four independent variables- population homogeneity, residential mobility, poverty, and family disruption.

The systemic reformulation of social disorganization theory notes that neighborhoods are not isolated; rather, they are part of a larger network. Thus, the systemic reformulation focuses attention on system components to examine the patterns of exchange and the ties among the components of the system. The main claim of this reformulation is that through those regulatory networks, the regulatory capacity of neighborhoods become actualized. Hence, this research examines variables such as education, employment, as well as voter participation to determine the extent to which participatory norms (going to school, being employed in the workforce, being married, and voting) are correlated with violent crime.

The unit of analysis for this project is counties in Virginia (n=135) and West Virginia (n=55). The Uniform Crime Reports from 2000 and 2000 Census data were examined to determine the relationship between rurality and violent crime, using the concepts of social disorganization theory and its recent systemic reformulation.  The independent variables that were examined include concentrated disadvantage, residential mobility, the dissimilarity index, family disruption, rurality, social disorder, and the systemic reformulation variables: unemployment, education, and voter participation.

Concentrated Disadvantage

A number of studies examining the structural correlates of crime indicate that there are certain areas that are highly impoverished, with many female-headed single parent households with children under 18, a high percentage of the population living in poverty, a higher concentration of minorities, and a higher rate of inequality of GINI household incomes. A number of studies have found that family structure correlates with higher crime rates (see for example Sampson1986). Numerous studies of social disorganization theory examine “family disruption” defining it as the percentage of female headed households with children under 18 (Osgood and Chambers 2000: 93).  Rountree and Warner (1999) examined crime in Seattle, Washington and found that violent crime rates are lower when there are fewer female-headed households. As Sampson and Groves (1989) indicate socioeconomic deprivation leads to a reduction in community attachment and weakened social ties. Sampson (1995) reviewed numerous studies that examined the impact of poverty on crime rates, and found that when poverty was combined with residential mobility, it is associated with an increase in violent crime. So, a principle components factor was created to include the variables related to concentrated disadvantage, which include: population homogeneity (calculated as percent minority), the GINI index on household income, the percent living in poverty (calculated as the percent of individuals in the county living below the poverty level), and the percent of single female-headed households with children under 18. This makes sense since each of these have strong factor loadings and are empirically overlapping.

Residential Mobility

One of the key variables historically in the application and understanding of social disorganization theory is residential mobility. The more transitory people in a community, the less cohesiveness in that community, the less unified the community, and the greater likelihood of competing norms and lack of assimilation to community norms. Sampson and Groves (1989: 787) found that residential stability was more important than urbanization with respect to its impact on friendship networks. Residential mobility was calculated as the percentage of individuals who have resided in a county different from their current residence in the past five years. The percent of residents born in the state was another proxy for residential mobility.

Dissimilarity Index

               The racial difference of household composition could be an indicator of differences in norms and values that might lead to more disorder.  A few studies (Osgood and Chambers 2000; Sampson and Groves 1989; Warner and Pierce 1993) examine dissimilarity in their examinations of social disorganization theory. This indicator ranges from 0 (no dissimilarity) to .5 (the most dissimilarity). A score of zero would indicate more ethnic homogeneity, while a .5 would indicate the most ethnic heterogeneity. This score is calculated by the following formula: 1-∑(pi2) where pi is the proportion of households that are white or nonwhite (Blau 1977; Osgood and Chambers 2000).

Family Disruption

Divorce is a violation of the participatory norms of a society which results in the reduction of parochial level controls. Additionally, the departure of the spouse from the neighborhood reduces informal controls. Thus, the percent of people in an area who were currently divorced or legally separated was calculated.

Rurality

               This was defined as the percent of the population living in rural areas according to Census data. Specifically, the number of individuals living in rural areas was divided by the total number of people living in that county.

Unemployment

               Unemployment is operationalized as the percent of the population over 16 who were unemployed. 

Education

               Individuals are socialized by the educational system to conform to societal expectations. While not a perfect assumption, the fact that someone completed high school indicates that they are more committed to community institutions like the labor market and the schools themselves. Additionally, students learn compliance in the schools as well as better problem-solving techniques so that they want to avoid violence and can. Therefore, the percent of individuals over 25 years old who completed high school was calculated for each county.

Voter Participation

               Voting can also be an indicator of participatory norms. This is a variable that is not often utilized, although there are some studies in which it has been related to crime rates (Coleman 2002). Voter participation is operationalized as the percent of residents over 18 who voted in the 2000 election.

Social Disorder

Another possible indication of social disorganization is disorderly crimes, so an index of crimes of disorder was also analyzed to determine its role in understanding violent index offenses. The crimes that are included in the disorder index are: prostitution and commercialized vice, disorderly conduct, vagrancy, drunkenness, DUIs, liquor law violations, vandalism, drug sales, and drug possession. This relates to the Broken Windows Theory (see Wilson and Kelling 1985), but it such low-level disorder can have an impact on the general disorganization of the community. Additionally, there are numerous studies that backs the claim that social disorder can lead to an increased fear of crime, which in turn can cause people to withdraw from society and, therefore, weaken informal controls.

 

 

Results

               Between the 190 West Virginia and Virginia counties, there were 74 Metropolitan areas, 34 non-metropolitan areas that were adjacent to the metropolitan areas, 29 counties that were non-metropolitan and not adjacent to metropolitan areas, and 53 rural counties. This set of analyses were performed on all counties in Virginia and West Virginia, while the second set examined rural counties only.

 

Table 1. Traditional and Systemic Reformulation Results for all Virginia and West Virginia Counties

 

Variables

Model 1

Traditional

Model 2 Traditional + Disorder

Model 3 Systemic

Model 4 Systemic + Disorder

 

B

β

B

β

B

β

B

β

Concentrated disadvantage

.435***

.552***

.423***

.536***

.306*

.368*

.284*

.342*

Moved within last 5 years

.013

.149

.013

.144

.015

.164

.014

.155

Born in state

-.004

-.076

-.004

-.074

-.003

-.073

-.003

-.061

Disimilarity index

-.939*

-.201*

-.904*

-.194*

-.867

-.217

-.762

-.191

Divorce

.137***

.265***

.136***

.263***

.111**

.214**

.114**

.222**

Urban population

.001

.047

.001

.029

.004

.161

.003

.145

Disorder index

 

 

.073

.054

 

 

.131

.097

Unemployment

 

 

 

 

.013

.069

.016

.084

Education

 

 

 

 

-.003

-.033

-.001

-.014

Voter Participation

 

 

 

 

-.746

-.074

-.762

-.075

R2

.381

.383

.299

.308

F score

(6,183) 18.736

(7,182) 16.119

(9,147) 6.98

(10,146) 6.49

***p<.001; **p<.01; *p<.05

               The first model examines concentrated disadvantage, percent of the population that moved within the past 5 years, the percent of the population that had moved within the last five years, the percent of the community born in state, the dissimilarity index, the percent divorced, and the percent of the population living in urban areas. This model is similar to the traditional formulation of social disorganization theory, although it takes social disorganization theory to a higher level, by examining the principle components score of multiple factors indicating concentrated disadvantage, as well as a dissimilarity index that examines the proportion of households occupied by white versus non-white occupants.  The second model adds social disorder to the multiple regression. The third model examines the systemic reformulation of social disorganization by adding indicators for educational, employment and voter participation. Finally, the last model adds social disorder to the regression. All of the models were significant, but the proportion of variation in violent crime rates that is accounted for by the independent variables differs slightly in each model, ranging from .299 to .383. The best model appears to be the traditional model that also examined the effects of social disorder on violent crime rates.

Only three of the variables examined were significantly correlated to the natural log of violent crime in the analyses of all counties: concentrated disadvantage, the dissimilarity index, and the percent divorced. The most significant relationship was between concentrated disadvantage and violent crime rates in the first two models and between divorce and violent crime rates in the second two models.  Because of the skewed nature of the variable and the assumptions of multiple regression that assume a normal distribution, the natural log of social disorder was calculated. While it was hypothesized that social disorder would explain violent crime, it appears that adding the variable adds to the variance explained by the models; however, social disorder was not statistically significant in either model.

Interestingly enough, the dissimilarity index became insignificant when the systemic variables were added to the model. This indicates that the racial similarities or differences may be more about differences in education, employment, or voter participation than race. In other words, there may be significant racial differences in educational attainment, employment, and/or voter participation.

 

Table 2. Traditional and Systemic Reformulation Results Regressions Run on Rural Counties Only

Variables

Model 1

Traditional

Model 2 Traditional + Disorder

Model 3 Systemic

Model 4 Systemic + Disorder

 

B

β

B

β

B

β

B

Β

Concentrated disadvantage

.626***

.741***

.700***

.828***

.561*

.663*

.637**

.754**

Moved within last 5 years

-.002

-.010

-.007

-.041

-.010

-.062

-.008

-.049

Born in state

-.004

-.066

-.006

-.087

.000

.010

-.003

-.045

Disimilarity index

-1.953**

-.516**

-2.187***

-.578***

-1.739

-.460

-2.104*

-.556*

Divorce

.149**

.293**

.120

.235

.134*

.262*

.112

.220

Disorder index

 

 

-.294

-.203

 

 

-.273

-.189

Percent unemployment

 

 

 

 

.015

.120

-.008

-.041

Education

 

 

 

 

-.006

-.029

 

 

Voter Participation

 

 

 

 

-2.113

-.196

-1.001

-.093

R2

.378

.411

.395

.416

F score

(5,47) 5.721

(6,46) 5.351

(8,44) 3.591

(8,44) 3.916

***p<.001; **p<.01; * p<.05

               All of the above models were statistically significant, although some only at the .01 level. This is most likely due to the relatively few cases and higher number of variables. By examining the r-square, it becomes obvious that social disorder adds to both models’ explanation of variance to an even greater extent than the previous set of models run on all Virginia and West Virginia counties. Even though the disorder index is not statistically significant, the models that include social disorder explain a greater percent of the variance when social disorder is included. The models that included the systemic reformulation of social disorganization theory have higher r-squares as well, suggesting that they are slightly better models for explaining violent crime rates. In the fourth model that examined the systemic reformulation and social disorder, education had to be removed because including it added too many variables, lost the statistical power of the model, and decreased the significance of the model. 

               In terms of the variables themselves, the principle components factor score for concentrated disadvantage was consistently associated with violent crime rates. However, when adding institutional variables like voter participation rates and unemployment rates, the significance of concentrated disadvantage, including poverty, the GINI household index, and female-headed households with children under 18 was reduced. 

 

Discussion

Since much of the country is not urban, it is important to know whether the same theories of crime that were originally tailored to urban sectors of the country can be applied to non-urban areas of the United States, and other countries. Since social disorganization theory helps explain violent crime in rural areas of Virginia and West Virginia, a tool to help reduce crime in rural areas by attempting to increase cohesiveness by reducing poverty rates and other structural components of crime. This analysis suggests the primary focus of crime prevention efforts should be on areas with high concentrations of disadvantage. That is, areas with high poverty rates, higher rates of female- headed households with children under 18, and areas with higher concentrations of minorities. Rural areas of Virginia and West Virginia should also pay attention to divorce rates and higher household proportions of ethnic heterogeneity.

Clearly, any research design has limitations. This research has a few significant limitations. First, since the analysis examines crimes using official data any problems with differential enforcement and reporting of crime exist. Additionally, it is a cross-section which may only tell one what has happened at that one point in time, not what might exist in the future or what has happened in the past. However, since social disorganization theory concepts are correlated to violent crime rates, further investigation is necessary to determine what other variables may be correlated to violent crime rates, if there are better indicators of the various concepts of social disorganization. Finally, a test of social disorganization theory is best at the neighborhood level; however, much of the research on rural areas indicate that each county has a different culture and that there is generally a significant amount of similarities within towns in such counties. Additionally, census tract data has been criticized because it does not necessarily differentiate between neighborhoods. Thus, county level data, while not ideal, still can tell us a great deal about applications of social disorganization and may be most applicable for rural analyses.

 

Conclusion

               Social disorganization theory applies to rural areas as well as non-rural areas. The variables associated with the systemic reformulation of social disorganization seem to play a greater role in rural areas. Clearly, this research contains a very small sample and further research needs to be undertaken to examine if this is true in all rural areas.

While many rural areas may be less disorganized, as early researchers presumed it is important to understand what sociological variables correlate with this disorganization and in what areas. The counties of one state may have high correlations between a small percent of the population graduating from high school and violent crime, while counties of another state show no significant correlation. Surely educational attainment is correlated to the labor force and what skills are necessary to maintain employment and remain above the poverty line.

There is a definite need for more research that is needed with respect to rural crime. This study is only the beginning. Additional research should examine different types of crimes and the structural correlates of such crimes. Furthermore, qualitative analyses should be conducted that examine in greater detail why relevant variables affect crime rates. Further research should concentrate more on the systemic reformulation of social disorganization theory since it appears to be a better predictor of violent crime rates. Additional variables that measure collective efficacy should also be examined further.

 

 

 

 

 

 

References

Arthur, J. A. (1991), ‘Socioeconomic Predictors of Crime in Rural Georgia’, Criminal Justice Review, 16: 29-41.

Bachman, R. (1991), ‘An Analysis of American Indian Homicide: A Test of Social Disorganization and Economic Deprivation at the Reservation County Level’, Journal of Research in Crime and Delinquency 28/ 4: 456-471.

Blau, P.M. (1977) Inequality and Heterogeneity: A Primitive Theory of Social Structure, New York: Free Press.

Bottoms, A. (1994), ‘Environmental Criminology’, in M. Maguire, R. Morgan, and R. Reiner, eds., The Oxford Handbook of Criminology, 585-658. Clarendon, London.

Bursik, R. J. Jr. (1988), ‘Social Disorganization and Theories of Crime and Delinquency: Problems and Prospects’, Criminology, 26/ 4: 519-551.

Bursik, R. J. Jr. and Grasmick, H.G. (1993), Neighborhoods and Crime: The Dimensions of Effective Community Control. New York: Lexington Books.

Bursik, R. J. Jr. and Webb, J. (1982), ‘Community Change and Patterns of Delinquency’, American Journal of Sociology, 88: 24-42.

Cameron, J. G. (2001), Spatial Analysis of Crime in Appalachia, 1977-1996. ICPSR version.  Washington, D.C.: U.S. Dept. of Justice, National Institute of Justice. Ann Arbor, MI: Inter-University Consortium for Political and Social Research.

Cattarello, A. (2000), ‘Community-Level Influences on Individuals’ Social Bonds, Peer Associations, and Delinquency: A Multi-Level Analysis’, Justice Quarterly 17/ 1: 33-60.

Coleman, S. (2002) ‘A Test for the Effect of Conformity on Crime Rates Using Voter turnout’, Sociological Quarterly, 43/ 2: 257-276.

Covington, J. and Taylor, R. (1991), ‘Fear Of Crime in Urban Residential Neighborhoods: Implications of Between- and Within-Neighborhood Sources for Current Models’, The Sociological Quarterly, 32/ 2: 231-249.

Donnermeyer, J. F. and Jobes, P. C. (2000), ‘Rural Crime’, Encyclopedia of Criminology and Deviant Behavior, 461-464. New York: Routeledge.

Duncan, C. (2001),  ‘Social capital in America’s Poor Rural Communities’,  In  S. Saegert, J. P. Thompson, and M. R. Warren, eds., Social Capital and Poor Communities, 60-86. New York: Sage Foundation.

Durkheim, E. (1933), The Division of Labor in Society. Translated by G. Simon. New York: Free Press.

Fischer, C. S. (1980), ‘The Spread of Violent Crime from City to Countryside, 1955 to 1975’, Rural Sociology, 45: 416-434.

Friedman, S. and Lichter, D. T. (1998),  ‘Spatial Inequality and Poverty among American Children’, Population Research and Policy Review, 17: 91-109. 

Hobbs, D. (1994), ‘The Rural Context for Education: Adjusting the Images’, in S. M. Blaser, ed., Perspectives on Violence and Substance Use in Rural America, 5-25. Oak Brook, Illinois: North Central Regional Educational Laboratory.

Hunter, A. J. (1985), ‘Private, Parochial, and Public School Orders: The Problem of Crime and Incivility in Urban Communities’, in G. D. Suttles and M. N. Zald, eds., The Challenge of Social Control: Citizenship and Institution Building in Modern Society, 230-242, Norwood, NJ: Ablex Publishing. As cited in R. J. Bursick Jr. and H. G. Grasmick. (1993) Neighborhoods and Crime: The Dimensions of Effective Community Control. New York: Lexington Books.

Jobes, P., Barclay, C. E., Weinand, H., and Donnermeyer, J. F. (2004), ‘A

Structural Analysis of Social Disorganization and Crime in Rural Communities in Australia’, The Australian and New Zealand Journal of Criminology, 37/ 1: 114-140.

 

Kasarda, J. D., and Janoqitz, M. (1974), ‘Community Attachment in Mass Society’, American Sociological Review, 39 (June): 328-339.

 

Kornhauser, R. R. (1978), Social Sources of Delinquency. Chicago: University of Chicago Press.

 

Lewis, D. and Salem, G. (1981), ‘Community Crime Prevention: An Analysis of a Developing Strategy’, Crime and Delinquency, 27:405-421.

 

Miller, M. K., and Luloff, A. E. (1981), ‘Who is rural? A Typological Approach to the Examination of Rurality’ Rural Sociology, 46/ 4: 608-625.

 

Montell, W. L. (1986), Killings: Folk Justice in the Upper South. Lexington: University of Kentucky Press.

 

Osgood, D. W. and Chambers, J. M. (2003), ‘Community Correlates of Rural Youth Violence’, OJJDP Juvenile Justice Bulletin, Washington, DC: U.S. Department of Justice, Office of Juvenile Justice and Delinquency, May. http://www.ncjrs.org/html/ojjdp/193591/page1.html retrieved on September 29, 2005.

 

Osgood, D. W. and Chambers, J. M. (2000), ‘Social Disorganization Outside the Metropolis: An Analysis of Rural Youth Violence’, Criminology, 38/ 1: 81-116.

 

Palen, J. J. (1981), The Urban World (3rd ed.). New York: McGraw-Hill.

 

Rohe, W. and R. B. (1988), ‘Fear of Crime in Public Housing’, Environment and Behavior, 20: 700-720.

 

Rountree and Warner (1999), ‘Social Ties and Crime: Is the Relationship Gendered?’ Criminology 37/  4: 789-814.                                      

 

Sampson, R. J. (1986), ‘Neighborhood Family Structure and the Risk of Personal Victimization’, In J.M. Byrne and R.J. Sampson, eds., 25-46, The Social Ecology of Crime, New York: Springer-Verlag.

 

Sampson, R. J. (1995), ‘The Community’, In J. Wilson and J. Petersilia, eds., Crime., 193-216. San Francisco, CA: ICS Press.

 

Sampson, R. J., and Groves, B. W. (1989), ‘Community Structure and Crime: Testing social Disorganization Theory’, American Journal of Sociology, 94: 774-802.

 

Shaw, C. R. and McKay, H. D. (1942), Juvenile Delinquency in Urban Areas. Chicago: University of Chicago Press.

 

Skogan, W. (1990), Disorder and Decline: Crime and the Spiral of Decay in American Neighborhoods. New York: Free Press.

 

Skogan, W. and Maxfield, M. (1981), Coping with Crime: Individual and Neighborhood Reactions. Beverly Hills, CA: Sage Publications.

 

Skolnick, J. (1966), Justice without Trial: Law Enforcement in a Democratic Society. New York: Wiley.

 

Stark, R. (1987), ‘Deviant Places: A Theory of The Ecology of Crime. Criminology, 25/ 4: 893-909.

 

Stinchcombe, A., Adams, R., Heimer, C., Schepple, K., Smith, T., and Taylor, D. (1980), Crime and Punishment: Changing Attitudes in America. San Francisco, CA: Jossey-Bass.

 

Taylor, R. (2001), ‘The Ecology of Crime, Fear, and Delinquency: Social Disorganization Versus Social Efficacy’, In R. Paternoster and R. Bachman, eds., Explaining Crime and Criminals, 124-139, Los Angeles, CA: Roxbury.

 

Veysey, B. and Messner, S. (1999), ‘Further Testing of Social Disorganization Theory: An Elaboration of Sampson and Groves’s ‘Community Structure and Crime’ ’, The Journal of Research in Crime and Delinquency, 36/ 2: 156-174.

 

Warner, B. D. and Pierce, G. L. (1993) ‘Reexamining Social Disorganization Theory Using Calls to Police as a Measure of Crime’ Criminology, 31: 493-517.

 

Warr, M. (1990), ‘Dangerous Situations: Social Context and Fear of Victimization’, Social Forces, 68: 891-907.

 

Weisheit, R. A., and Donnermeyer J. F. (2000), ‘Change and Continuity in Crime in Rural America’, in G. LaFree, ed., The Nature of Crime: Continuity and Change, 309-358, Washington D.C.: U.S. Department of Justice.

 

White, D. (1987), ‘A Social Epidemiological Model of Central Appalachia’,  Arete, 12: 47-66.

 

Wilkinson, K. P. (1984), ‘A Research Note on Homicide and Rurality’, Social Forces, 63/ 2: 445-452.

 

b and Kelling (1985), ‘Broken Windows: The Police and Neighborhood Safety’ in A. Blumberg and E. Niederhoffer, ed., The Ambivalent Force, 220-228, New York: Holt, Rinehart & Winston.

 

 

 

              


[1] The 410 counties in Appalachia includes all 55 counties of West Virginia and 23 counties in Virginia.