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Journal of Marriage and Family 64 (November 2002): 833850 833

CHRISTOPHERR. BROWNING Ohio State University

The Span of Collective Efficacy: Extending Social

Disorganization Theory to Partner Violence

This research applies the social disorganizationperspective on the neighborhood-level determi-nants of crime to partner violence. The analysisbrings data from the 1990 Decennial Census to-gether with data from the 19941995 Project on

Human Development in Chicago NeighborhoodsCommunity Survey, the 19941995 Chicago ho-micide data, and data from the 19951997 Chi-cago Health and Social Life Survey. The findingsof this study indicate that collective efficacyneighborhood cohesion and informal social con-trol capacityis negatively associated with bothintimate homicide rates and nonlethal partner vi-olence. Collective efficacy exerts a more powerfulregulatory effect on nonlethal violence in neigh-borhoods where tolerance of intimate violence islow. Collective efficacy also increases the likeli-hood that women will disclose conflict in their re-lationships to various potential sources of sup-

port.

In recent decades there has been a dramatic in-crease in popular and academic interest in thecauses of violence between intimate partners. Re-search on the etiology of intimate-partner violenceinitially focused primarily on investigations of in-dividual-level dispositions to violence amongmarried men (Schultz, 1960). More recently, re-

Department of Sociology, Ohio State University, 300Bricker Hall, 190 North Oval Mall, Columbus, OH 43210([email protected]).

Key Words: collective efficacy, conflict disclosure, neigh-borhood effects, partner violence.

searchers have broadened their focus to includeviolence in nonmarital (cohabiting and dating) re-lationships (Magdol, Moffitt, Caspi, & Silva,1998) and have begun to look more closely atrelational and social-network determinants of in-timate violence (Cazenave & Straus, 1995). Yet,with few exceptions (Miles-Doan, 1998), researchon partner violence has not offered sophisticatedconceptualizations or empirical investigation ofthe community-level processes that influence theprevalence of violent relationships. The relativeneglect of the broader social context in partnerviolence research has persisted despite an increas-ingly widespread recognition of the significanceof community characteristics for a range of im-portant outcomes (Brooks-Gunn, Duncan, Kleba-nov, & Sealand, 1993a; Jencks & Mayer, 1990).

This research brings theoretical perspectives onneighborhood-level determinants of crime to bearon partner violence. It extends existing researchon this topic by (a) developing and testing a dis-tinct theoretical model, rooted in social disorga-

nization and routine activity theory, of the asso-ciation between neighborhood characteristics andpartner violence; (b) examining the effects of so-cial processes at the neighborhood level that mayuniquely affect relationship violence or may me-diate the impact of neighborhood structural char-acteristics; (c) considering both lethal and nonle-thal violence between intimate partners; and (d)addressing these questions with multilevel data onthe occurrence of violence in sexual relationships,providing an opportunity to control for individual-,relationship-, and network-level correlates of in-timate violence.

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834 Journal of Marriage and Family

Specifically, I address the following questions:First, are a communitys structural characteristics,including concentrated disadvantage, residentialstability, and ethnic heterogeneity, associated withthe prevalence of partner violence above and be-

yond individual-, relationship-, and network-levelfactors? Second, are key neighborhood-level so-cial processes, including collective efficacy andnorms of nonintervention in relationship disputes,associated with partner violence? Do these mech-anisms mediate the effects of structural character-istics on this outcome? Finally, do communitiesinfluence the likelihood of womens mobilizationof social support in response to relationship con-flict (i.e., conflict disclosure)?

THEORETICAL PERSPECTIVES ONPARTNER VIOLENCE

Social Disorganization, Collective Efficacy, andRoutine Activity Theory

The revival of interest in the community-level ef-fects of poverty on a range of adverse outcomeshas contributed to a renewed focus on social dis-organization theory (Wilson, 1987). As initiallyarticulated by Shaw and McKay (1969) and sub-sequently extended by Kornhauser (1978), the so-

cial disorganization approach suggests that neigh-borhood poverty, residential instability, and ethnicheterogeneity attenuate the community-level ca-pacity to regulate local crime. Poverty diminishesthe resources necessary to sustain basic institu-tions like the family, churches, schools, and vol-untary organizations in urban neighborhoods.Poverty also contributes to residential instabilityand ethnic heterogeneity, both of which inhibit theformation of durable relationships, weaken com-munity attachments, and complicate efforts to im-plement shared goals. In their research, Shaw andMcKay found that these structural factors contin-ued to affect crime rates regardless of ethnic andracial population succession, suggesting that ma-crolevel processes exert effects on crime indepen-dent of the characteristics of individuals whomake up disadvantaged neighborhoods.

More recently, Sampson (1997) has offered amodel that explicitly identifies the social processesthat link the structural features of neighborhoodswith crime. In his view, the prevalence and den-sity of kinship, friendship, and acquaintanceship

networks and the level of participation in com-munity-based organizations contribute to theemergence of solidarity and mutual trust, or social

cohesion, among community residents. In turn,social cohesion promotes effective informal socialcontrol, or a communitys capacity to monitor andmanage criminogenic social situations. Cohesivecommunities that can effectively mobilize to reg-

ulate local crime can be understood to have highlevels ofcollective efficacy with respect to the so-cial control of crime (Sampson, Raudenbush, &Earls, 1997).

Bursik (1988) has noted the compatibility be-tween the supervisory component of social dis-organization (and collective efficacy) theory andthe notion of guardianship developed in routineactivity theory (Cohen & Felson, 1979). Accord-ing to this view, crime requires the convergencein time and space of a motivated offender, a suit-able target, and the absence of a capable guardian.The latter component of the routine activity modeloverlaps with the concept of informal social con-trol in social disorganization theory and presumesthat neighborhoods are differentially efficacious inproviding the guardianship necessary to regulatelocal criminal activity (Bursik & Grasmick, 1993).Communities that can more effectively supervisethe interaction of potential offenders and targetsshould reduce rates of victimization (Sampson,1985, 1986), potentially including violence be-tween intimates.

Guardianship, Conflict Disclosure, andPartner Violence

An emphasis on the crime-inhibiting role of ef-fective guardianship rooted in collective efficacysuggests that socially organized neighborhoodsshould exert influence on victimization betweenintimates as well as nonintimates. Yet, partner vi-olence is potentially distinct from other forms ofviolence with respect to two factors: the monitor-ing capacity of the community and the tendencyto recognize partner violence as deviance. Withrespect to monitoring capacity, it is not clear thatneighborhood regulatory potential extends to re-lations between intimates. Intimate partnershipsare largely enacted beyond public view and aretypically not subject to capable guardianship. Tothe extent that these relationships are beyond thereach of collective supervision, neighborhood so-cial organization may not be consequential withregard to the regulation of partner violence.

Collective efficacy, however, may influence

victimization rates both directlythrough inter-vention at the site of a potential offenseand in-directlythrough management of the exposure of

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835Social Disorganization and Partner Violence

targets to potential offenders. Direct social controlmay be exercised through the management ofmens violent behavior toward their female part-ners by, for instance, the breaking up of disputesor the supervision of mens interactions with their

partners. This type of social control, however, asGelles (1983) has suggested, is complicated by therelative invisibility of interaction between intimatepartners.

Indirect social control of intimate partnerships,however, reduces violence not through the man-agement of mens behavior but through the re-moval of the targets of that behavior. This formof guardianship occurs through womens efforts tomobilize community resources and the responsesof communities to these mobilization efforts. First,social environments may be perceived by womento be more or less supportive or effective in man-aging partner violence. To the extent that sociallyorganized communities appear more capable ofproviding useful resources to combat the threat ofviolence, they may be more likely to elicit thedisclosure of conflict and violence in intimatepartnerships from women who are experiencingthese things. Disclosure to potential sources ofsupport is a critical mechanism by which womenleverage the social control capacities of their en-vironments (Bowker, 1983; Fagan, 1992). In a

study of 1,000 currently or formerly batteredwomen, Bowker (1986, 1993) found that the dis-closure of intimate violence to informal sourcesof support, including friends, family, the partnersrelatives, and neighbors, offered women in violentrelationships access to important resources. Infor-mal social networks provided personal support,advice, shelter, and social pressure on batterers todesist. Disclosure to formal sources of support,including police, physicians and nurses, the cler-gy, legal representatives, social service or coun-seling agencies, womens groups, and batteredwomens shelters, was also an important strategyused by women to combat the threat of intimateviolence (Bowker, 1993).

In turn, communities in which women are em-bedded may be differentially efficacious in inter-vening on behalf of women in violent or poten-tially violent partnerships. The same mechanismsthat contribute to the regulation of childhood andadolescent problem behavior and to the manage-ment of public forms of violencedense net-works, social trust, community attachment, and re-

sulting expectations for social control activityare also likely to be implicated in the localguardianship of women who are experiencing the

threat of intimate violence. Socially organizedcommunities may more successfully regulate part-ner violence by steering women away from po-tentially violent partners or by providing womenwith viable avenues for exiting abusive relation-

ships.This protective dimension of informal social

control and its potential implications for partnerviolence are not explicitly acknowledged in recentdiscussions of social disorganization theory.Sampson et al. (1997), for instance, view the im-pact of collective efficacy on neighborhood vio-lence as existing relative to the tasks of super-vising children and maintaining public order (p.919) but not relative to the control of violenceamong intimates. Yet, tests of the social disorga-nization perspective often employ dependent var-iables that capture violence between intimates(e.g., homicide [Sampson et al., 1997]). Such testscannot determine whether the association betweendisorganization and violence applies only to non-intimates. Consequently, an extension of the su-pervisory assumptions of social disorganizationtheory to partner violence is both theoreticallyconsistent and empirically plausible.

Normative Orientations TowardPartner Violence

The potential for community intervention in vio-lent relationships is called into question, however,by a second concern: The extension of social dis-organization theory to partner violence involvesthe questionable assumption that the control of vi-olence among intimates is a shared value at thecommunity level. Even if the span of collectivesupervision extends to intimate relationships, vi-olence between intimate partners may not be rec-ognized as deviant in some communities andtherefore would not trigger the mobilization of so-cial control. Thus, the hypothesis that noninter-vention norms surrounding intimate relationshipsexplain community variation in partner violencemust be considered when social disorganizationtheory is extended to this outcome. Social orga-nization may exert an inhibitory effect on partnerviolence only where violence between intimates isnot considered a private matter.

In sum, although partner violence is in somerespects distinct from other forms of violence, theextension of the social disorganization model to

include this outcome nevertheless appears war-ranted. First, the model proposed here hypothesiz-es that the mechanisms facilitating the social con-

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trol of partner violence overlap substantially withthose that characterize collective efficacy with re-spect to the supervision of adolescent and publicviolence. However, the neighborhood-level socialcontrol of partner violence may operate indirectly

through the community-level capacity to elicit dis-closure of conflict in intimate relationships andmanage the exposure of women to potentially vi-olent men. Second, communities may vary withregard to the extent to which they agree that vi-olence between intimates should be subjected toinformal social control. Thus, norms of noninter-vention in family or intimate relationships maymute the regulatory effect of collective efficacy.

Individual-Level Predictors of Partner Violence

A multilevel investigation of partner violencemust consider not only community-level influenc-es on partner violence prevalence but also indi-vidual-level determinants that may be correlatedwith macroprocesses. Most previous research hasexamined individual- and neighborhood-level pro-cesses separately, potentially obscuring theirunique influences on partner violence. Moreover,the majority of individual-level research on theetiology of partner violence has focused on men.This tendency has stemmed in part from the typ-

ically inconclusive results of research on women.Investigations of partner violence experienceamong women have generally failed to uncovermore than a few consistent individual-level pre-dictors of a womans likelihood of being involvedin a violent relationship (Hotaling & Sugarman,1986; Magdol, Moffitt, Caspi, & Newman, 1997;OLeary, Malone, & Tyree, 1994; see Moffitt andCaspi, 1999, for a recent exception).

The relatively limited empirical research onwomen has tended to emphasize demographic, lifecourse, relational, and network factors that maycontribute to intimate-partner violence experience.Both survey data and official data have highlight-ed the role of race and ethnicity in the distributionof partner violence. Rates of intimate-partner vi-olence among African Americans (Goetting,1989; Hampton, Gelles, & Harrop, 1987) and La-tinos (Straus & Smith, 1990), for instance, areconsistently higher than those among non-LatinoWhites. In addition to race/ethnicity, one of themost consistent life course predictors of involve-ment in a violent partnership is age. Women in

their late teens and in young adulthood are mostlikely to be exposed to intimate partners who posethe strongest risk of violent behavior (Elliot, Hui-

zinga, & Morse, 1986). Adversity during onesearly life course, including poor family relationsand adolescent problem behavior, may also be as-sociated with the likelihood of experiencing vio-lence on the part of a partner. In a prospective

longitudinal study of a New Zealand birth cohort,Moffitt and Caspi (1999) found that parent-childrelations (attachment, conflict, and discipline pat-terns) and physically aggressive delinquent of-fenses were associated with victimization duringearly adulthood.

Features of womens contemporary relation-ships and social networks may also be consequen-tial with regard to the onset of violence. Womenwho are poor or financially dependent on theirpartners may be at greater risk of violence becauseof the higher costs associated with relationshiptermination (Hotaling & Sugarman, 1986). Maritalstatus has been linked to violence independent ofeconomic factors, with married couples having thelowest risk and cohabitants having the highest(Stets & Straus, 1995). In addition, the features ofthe social networks in which relationships are em-bedded have also been hypothesized to be an im-portant social determinant of partner violence (Ca-zenave & Straus, 1995). Fagan (1993), forinstance, suggests that network configurationsmay indicate the relative balance of gendered so-

cial influence in a relationship. Men who are em-bedded in subcultures that are primarily male maybe more susceptible to normative orientations thatsupport the use of violence in intimate relation-ships. Similarly, women who function with rela-tively less informal network-based support mayhave difficulty mobilizing social resources tomanage a violent partnership. The potential rele-vance of these factors to victimization risk amongwomen calls for their simultaneous considerationin analyses of community contexts effects onpartner violence. Only multilevel data on partnerviolence can meet this requirement.

HYPOTHESES

Social disorganization theory links concentrateddisadvantage, residential stability, and ethnic het-erogeneity with variations in social organizationand the collective capacity to control local crime.As noted, ethnic heterogeneity is viewed as astructural feature of communities that may impedecommunication among residents. I explore the im-

pact of the concentration of Latino and foreign-born residents within communities as a measureof potential barriers to communication within Chi-

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cago neighborhoods. A foundational hypothesis,then, links structural factors with the prevalenceof female victimization by a male partner. Hy-pothesis 1 is as follows: Structural features of ur-ban communitiesconcentrated disadvantage,

residential stability, and immigrant concentra-tionare associated with the prevalence of inti-mate homicide at the community level and in-volvement in a violent partnership at theindividual level (above and beyond relevant in-dividual-, relational-, and network-level factors).

A second set of hypotheses addresses theunique, mediating, and interactive effects of col-lective efficacy and normative orientations onpartner violence: (2a) Collective efficacy is a sig-nificant negative predictor of intimate-partner ho-micide at the community level and of involvementin a violent partnership at the individual level(above and beyond relevant individual-, relation-al-, and network-level factors); (2b) collective ef-ficacy partially mediates the association betweenstructural factors and partner violence; and (2c)collective efficacy interacts with noninterventionnorms in its effect on partner violence such thatthe regulatory effect of collective efficacy is stron-gest when nonintervention norms are less preva-lent.

A third hypothesis addresses the impact of

community social organization on womens re-sponses to violence. Specifically, these modelsconsider the impact of collective efficacy on theindividual-level likelihood of relationship conflictdisclosure. Hypothesis 3 is as follows: Neighbor-hoods with high levels of collective efficacy pro-mote womens disclosure of conflict in intimaterelationships to potential sources of support, in-cluding friends, family, the family of the womanspartner, and institutions (above and beyond rele-vant individual-, relational-, and network-levelfactors).

METHOD

The city of Chicago offers two key advantages fora study of partner violence. First, Chicago hasbeen demonstrated to be roughly comparable toother northern urban settings in terms of intimate-partner violence rates (Block, 1987). Second, in-dependent data collection efforts have resulted ina wealth of information with which to explore thecorrelates of partner violence. Four data sources

were used in the analysesthe 1990 DecennialCensus, the 199495 Project on Human Devel-opment in Chicago Neighborhoods Community

Survey, Chicago homicide data (Block & Block,1993), and the 19951997 Chicago Health andSocial Life Survey. The Project on Human De-velopment in Chicago Neighborhoods (PHDCN)Community Survey consists of a probability sam-

ple of 8,782 residents of Chicago and focuses onrespondents assessments of the communities inwhich they live. The survey grouped Chicagos865 census tracts into 343 neighborhood clusters(averaging roughly 8,000 people) that maintainrelative population homogeneity with respect toracial/ethnic, socioeconomic, housing, and familystructure characteristics. Respondents were giventhe following definition of neighborhood: Byneighborhood . . . we mean the area around whereyou live and around your house. It may includeplaces you shop, religious or public institutions,or a local business district. It is the general areaaround your house where you might perform rou-tine tasks, such as shopping, going to the park, orvisiting with neighbors. Neighborhood clusterswere also defined on the basis of ecologicallymeaningful boundaries such as railroad tracks andfreeways. The community surveys three-stagesampling strategy selected city blocks withinneighborhood clusters, dwelling units withinblocks, and respondents (one 18-year-old or olderadult per household) within dwelling units. The

community survey sampling strategy ensured thatthe number of cases collected per neighborhoodcluster (a mean of about 25) would be sufficientto estimate neighborhood characteristics on thebasis of aggregated individual-level data. Thecommunity survey achieved a final response rateof 75%.

The Chicago homicide data consist of recordsof homicide victims by geographic location for thecity of Chicago for 19651995. These data pro-vide information on the characteristics of the vic-tim and the offender, including the nature of theirrelationship. The 19951997 Chicago Health andSocial Life Survey consists of a probability sam-ple of noninstitutionalized adults aged 18 to 59residing in Cook County, Illinois (the responserate was 71%). The data include a cross-sectionof the city of Chicago (N 502). In addition toextensive life history data, the survey contains amodule on the respondents most recent sexualpartnership that collects a wide variety of infor-mation, including the respondents experienceswith violence. The analyses were performed only

for female respondents residing in the city of Chi-cago who were involved in heterosexual relation-ships at the time of the interview (N 199, or

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74% of the total sample of women for the city ofChicago). The sample included residents of 77Chicago neighborhood clusters.

Independent Variables

Measures of neighborhood-level structural char-acteristics were constructed with data from the1990 Decennial Census. On the basis of theoryand extensive prior investigation (Land, McCall,& Cohen, 1990; Sampson et al., 1997), principalcomponents analyses were performed on threeclusters of variables tapping key dimensions ofneighborhood structure. The concentrated disad-vantage component combined the percentages ofsubjects who were living below the poverty line,receiving public assistance, unemployed, underage 18, and African American, as well as the per-centage of female-headed households. The resi-dential stabilitycomponent combined measures ofhousing tenure (the percentage of subjects whohad not moved since 1985) and the percentage ofhouses occupied by owners. The immigrant con-centrationcomponent combined the percentage ofLatino participants with the percentage of foreign-born subjects. Principal component scale scoreswere estimated for each of the 77 neighborhoodsincluded in the analyses. Comparisons of means

for the census variables used in the principal com-ponents analyses indicate that the Chicago Healthand Social Life Survey neighborhood subsampleclosely approximates the social composition of thecity as a whole.

Collective efficacy was operationalized bycombining measures of social cohesion with mea-sures of informal social control. The social cohe-sion scale was constructed from a cluster of con-ceptually related items from the Project on HumanDevelopment in Chicago Neighborhoods Com-munity Survey measuring the respondents levelof agreement (on a 5-point scale) with the follow-ing statements: (a) people around here are willingto help their neighbors, (b) this is a close-knitneighborhood, (c) people in this neighborhoodcan be trusted, (d) people in this neighborhoodgenerally dont get along with each other, and(e) people in this neighborhood do not share thesame values. The informal social control scalewas constructed from respondent assessments ofthe likelihood that their neighbors could be count-ed on to intervene in various ways if (a) children

were skipping school and hanging out on a streetcorner, (b) children were spray-painting graffition a local building, (c) a child was showing

disrespect to an adult, (d) there was a fight infront of your house and someone was being beat-en or threatened, or (e) because of budget cuts,the fire station closest to your home was going tobe closed down by the city. The aggregation

method is described in the Analytic Strategy sub-section.

To examine the effect of community-level non-intervention norms, a neighborhood-level measureof attitudes about family violence was included inthe model. The community survey asked respon-dents whether they agreed with the statement,Fighting between friends or within families isnobody elses business. Responses were givenon a 5-point Likert scale, with higher values rep-resenting higher levels of agreement.

Neighborhood-level controls included the fe-male populations of Chicago neighborhood clus-ters and the prior (19911993) intimate-partnerhomicide rate (for the analysis of intimate-partnerhomicide) as well as a measure of violent victim-ization aggregated to the neighborhood level (forthe analysis of nonlethal severe violence). Violentvictimization was included to capture environ-ments that may model violence as an adaptive re-sponse. Communities in which violence is preva-lent may transmit this behavioral orientation tomultiple contexts, including family and intimate

relationships (Massey & Denton, 1993; Miles-Doan, 1998). The victimization measure wasbased on an item from the community survey ask-ing the respondent, While you have lived in thisneighborhood, has anyone ever used violence,such as in a mugging, fight, or sexual assault,against you or any member of your householdanywhere in your neighborhood? Neighborhoodscores for violent victimization as well as familyviolence tolerance were adjusted for neighbor-hood social composition in a manner similar tothat used for the collective efficacy scale (de-scribed below).

Individual-, relationship-, and network-levelcharacteristics were constructed from the exten-sive modules on life histories and current rela-tionships in the Chicago Health and Social LifeSurvey. Demographic measures included the re-spondents race/ethnicity (White, African Ameri-can, Latina), age (1829 years vs. 3059 years),and education (whether the respondent finishedhigh school). A measure of the respondents per-sonal income (less than $10,000 vs. $10,000 or

more) was also included to capture both the ex-perience of poverty and potential economic de-pendency in a current intimate relationship.

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Life history variables identified as potentialmarkers of risk for entry into violent relationshipsinclude the experience of being touched sexuallyduring childhood. Respondents were asked: Be-fore you were 13 years old, did anyone touch you

sexually? Any woman who respondedyesto thisquestion was coded as having had an early sexualexperience. Childhood sexual experiences havebeen shown to be highly correlated with bothphysical abuse and neglect (Widom & Amos,1994). Additional measures of life course adver-sity examined in separate models (not shown) in-cluded the structure of the family of origin (intactvs. nonintact), whether the respondent left homebefore age 17, whether the respondent had beenpregnant as a teenager, and whether the respon-dent had experienced jail time. None of these var-iables was a significant predictor of victimization,and all of them were dropped from the final mod-els.

In addition to marital status and relationshipduration (i.e., years since first sexual event), keyrelationship characteristics included the type andextent of conflict in the relationship. The latterwere measured through a series of items inquiringinto areas representing possible sources of conflictin the respondents relationship. These areas in-cluded sex, money, drinking, drugs, the relatives

of the respondents partner, the respondents rela-tives, and friends. A summary measure of thenumber of conflict sources reported by womenwas constructed along with a separate indicator ofwhether sexual jealousy was a key source of re-lationship conflict (this item was not included inthe summary conflict measure). The sexual jeal-ousy item was included independently in modelsof severe violence to capture male aggressionrooted in jealous or controlling orientations to-ward women (Holtzworth-Munroe & Stuart,1994).

Unfortunately, the cross-sectional nature of thedata precluded the time ordering of some inde-pendent variables with reference to the dependentvariable. For instance, conflict may increase in theaftermath of violence. Indeed, the conflict mea-sures may, to some extent, measure physical ag-gression itself. However, they were included tocapture otherwise unmeasured individual and re-lationship factors that increase conflict. Withoutsuch controls in the model, it would be more dif-ficult to assess the extent to which any associa-

tions between community-level factors and part-ner violence are caused by the selection ofconflict-prone individuals or relationships into dis-

advantaged communities. With these controls, themodels presented below offer relatively conser-vative estimates of neighborhood effects on part-ner violence.

Finally, an individual-level measure of network

embeddedness was included to tap the genderednature of social interaction patterns. Coupled so-cial interaction anchored primarily on the malepartners network may indicate more embedded-ness in male (and potentially violence-tolerating)microlevel subcultures. Isolation from sources ofnetwork support may also limit womens oppor-tunities to escape or manage partner violence. So-cial network embeddedness (with respect to thepartner) is represented by a dichotomous variablethat measures the extent to which the respondentinteracts with her own family and friends (1) ver-sus the extent to which she interacts primarilywith her partners family and friends or lacks so-cial interaction (social isolation) (0). A measureof the number of years the respondent lived in theneighborhood was also included to measureneighborhood embeddedness.

Models of conflict disclosure include key de-mographic background factors, controls for thelevel of conflict experienced and the occurrenceof violence in the relationship, neighborhoodcharacteristics, and measures of the opportunity to

disclose conflict. The latter measures are consid-ered because some women may have a wider net-work of friends and family members to whom todisclose conflict, and this may be correlated withcommunity characteristics. Although several mea-sures of egocentric network extensity were con-sideredthe respondents number of friends, thenumber of the respondents relatives living in Chi-cago, the number of the respondents partners rel-atives living in Chicago, and the number of peoplein the respondents neighborhood she knows ortalks to regularlyonly the respondents numberof friends achieved significance in models of con-flict disclosure. Thus, other disclosure opportunityvariables were dropped from the final models.

Dependent Variables

The analyses presented here focused on the vic-timization of women by men in intimate relation-ships. A focus on womens victimization acknowl-edges the disproportionate injury sustained bywomen who experience violence by a partner and

the relatively large proportion of female homicidevictims who experience lethal violence by an in-timate partner (up to 50% vs. less than 5% of male

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homicide victims) (Bachman & Saltzman, 1995;Kellerman & Mercy, 1992). Limitations on thesize of the sample of men in the Chicago Healthand Social Life Survey, as well as questions re-garding the extent to which men may underreport

more severe violence (Stets & Straus, 1991), con-tributed to the decision to focus exclusively onwomens reports of victimization in the analysesof nonlethal severe violence.

An important issue in the measurement of in-timate-partner violence concerns differences in thetypes of partner violence captured by national sur-veys compared with those represented by selectsamples taken from battered womens shelters orpolice records. Johnson (1995) and Johnson andFerraro (2000), for instance, have argued thatlarge population-based surveys are likely to cap-ture relatively less severe and typically mutual sit-uational couple violence. Shelter, clinical, andcriminal justice samples, on the other hand, willtend to overrepresent more extreme cases ofinti-mate terrorism.The latter cases are more likely toinvolve chronic and severe violence (includinghomicide) by men against their partners. To ad-dress this possibility, I use survey data to examinerelatively severe but more typical partner vio-lence, and I also examine the most extreme formof partner violenceintimate-partner homicide.

The analyses presented here focused on threeoutcome variables: the number of women mur-dered by male partners within Chicago neighbor-hoods, the occurrence of nonlethal severe violenceagainst a woman by her current partner within thelast year, and the disclosure of relationship conflictto potential sources of support in the last year.First, intimate homicides involving a female vic-tim and an offender who was classified as a boy-friend, ex-boyfriend, spouse, or ex-spouse (Block& Christakos, 1995) were summed for each neigh-borhood for 19941995. For 19941995, therewere no incidents of intimate-partner homicidesagainst women in the vast majority of neighbor-hoods (84.3%); one such incident occurred in12.5% of the neighborhoods, and two occurred in3.2% of the neighborhoods. To test for the pres-ence of spatial dependence among neighborhoodclusters, I used the Huber-White variance correc-tion clustering on community area. Communityareas are aggregations of census tracts that encom-pass roughly 40,000 residents. This test allowederrors among the roughly five neighborhood clus-

ters within each community area to be correlated.The results of this analysis were virtually the sameas those described below.

Second, a subset of items from the ConflictTactics Scale was used to construct a measure ofnonlethal severe violence in intimate relationships(Straus, 1995). Female respondents were coded ashaving experienced severe violence if a partner

was reported to have hit the other with a handor fist, hit the other with something hard,beat the other up, threatened the other with aknife or gun, or used a knife or gun in thelast 12 months. The classification of severe vio-lence reproduces as closely as possible that usedby Straus and Gelles (1995) in an effort to captureacts of violence that are more likely to lead toinjury. Analyses reproducing the models present-ed below to obtain a measure ofany relationshipviolence (including violent incidents during whichthe respondents partner threw something at therespondent or pushed, grabbed, or shoved her) inthe last year yielded substantively similar results.The Chicago Health and Social Life Survey usedself-administered questionnaires to maximize va-lidity and reliability in its collection of informa-tion concerning violence in intimate relationships.

Table 1 reports means and standard deviationsfor variables in the analysis. The proportion ofChicago Health and Social Life Survey respon-dents who reported having experienced severe vi-olence in the last year was .085, and the propor-

tion reporting any violence was .166. Using datafrom the 1985 National Family Violence Survey(NFVS)and somewhat different operationaliza-tions of severe and minor violenceStraus andGelles (1995) reported that the proportion ofwomen in cohabiting or marital relationships whoexperienced any severe violence by their partnerwas .034, and that the proportion experiencingany violence was .116. Beyond differences in op-erationalization, the Chicago Health and SocialLife Survey estimates may be elevated in com-parison with those of the NFVS because they in-clude violence in dating relationships as well asin cohabiting and marital relationships and arebased on an urban population. The higher rate ofsevere violence in the Chicago Health and SocialLife Survey sample, however, should providesome confidence in the validity of the measure-ment strategy.

Third, the likelihood of conflict disclosure wasexamined to explore the relationship betweencommunity social organization and communica-tion with potential sources of social support. The

Chicago Health and Social Life Survey asked re-spondents whether they had spoken with any ofseveral possible sources of support about conflict

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TABLE1. DESCRIPTIVESTATISTICS FORVARIABLES IN THEANALYSIS(N 199)

Variable M SD Min Max

Independent variablesDemographic background

Race

WhiteAfrican American

0.2910.462

0.4560.500

00

11

LatinaAge

1829 years3044 years4559 years

0.211

0.3070.4720.221

0.409

0.4620.5000.416

0

000

1

111

Income of$10,000Touched sexually during childhoodLess than high school educationMarital status

Dating

0.2660.1210.186

0.353

0.4430.3260.390

0.479

000

0

111

1CohabitingMarried

Jealousy as source of conflictNumber of conflict sourcesRelationship duration (years)Years resident in the neighborhood

0.1610.487

0.3171.0709.387

11.236

0.3680.501

0.4661.1799.096

10.984

00

000

11

53849

Social embeddednessRespondent spends free time mostly:

With mutual friends, familyWith partners friends/familyAlone/socially isolated

0.6680.2010.131

0.4720.4020.338

000

111

Disclosure opportunityNumber of friends

0123

0.1070.0650.278

0.3090.2470.449

000

111

49102020

Dependent variablesSeverity of violence

0.2310.1780.142

0.4230.3830.350

000

111

No violenceLow: threw something, pushed, shoved, grabbedHigh: hit, beat up, threatened, used knife/gun

Conflict disclosure

0.8340.0800.085

0.3730.2730.280

000

111

FriendsFamilyPartners friends/relativesInstitution

0.4800.3660.2230.141

0.5010.4830.4870.352

0000

1111

in their intimate relationships. Although conflictwas not explicitly tied to the occurrence of vio-lence, this outcome is nevertheless theoreticallyinteresting because it captures communication re-garding relationships that may be at risk of vio-lence as well as those that have become violent.Sources of support include friends, the respon-dents relatives, the respondents partners rela-tives, police, the clergy, marriage or couples coun-selors, staff at battered womens shelters, social

workers, hotlines, doctors, and other sources. Al-though the data do not distinguish between sourc-es inside and outside the neighborhood, the am-

biguity of the dependent variable wouldpresumably mute the effects of neighborhood var-iables to the extent that these factors would notinfluence decisions on whether to inform individ-uals outside the neighborhood. Because rates ofdisclosure to sources other than friends and familywere low, these other sources were combined intoa single measure of disclosure to an institutionalsource. The four disclosure sources are combinedin a single item-response model described in the

Analytic Strategysubsection.Only respondents who were in relationships at

the time of the interview were asked about the

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level of violence characterizing their relationshipsand whether relationship conflict was disclosed.Because these measures captured any occurrenceof violence or conflict disclosure in the last year,longer relationships would have had more expo-

sure to the risk of violence. To address this prob-lem, the analyses controlled for the length of therelationship. In addition, all models of nonlethalviolence and conflict disclosure were checked forselectivity bias using probit models with sampleselection (Heckman, 1979). Selection equationswere specified for models of nonlethal severe vi-olence, any violence, and the dichotomous disclo-sure items. Selection equations (N 66) includedmeasures of collective efficacy, neighborhood tol-erance of family violence, age (1829 vs. 3059),and the number of sexual partners prior to the lastyear (2, 3 to 10, and 11 or more vs. 0 or 1) aspredictors of the likelihood of the respondentshaving a sexual partner in the last year. However,multiple specifications of the selection equationwere considered. Corrections for sample selectionresulted in negligible changes in the coefficientsof interest and did not alter the substantive con-clusions of the analyses. Final models were esti-mated using hierarchical logistic regression with-out corrections for sample selection.

Analytic Strategy

For the analyses presented here, I used hierarchi-cal linear model (HLM)adjusted neighborhood-level measures of collective efficacy and nonin-tervention norms in the context of ordered logitmodels of intimate-partner homicide rates, two-level logistic regression models of the occurrenceof violence on the part of the respondents currentpartner, and three-level Rasch models of conflictdisclosure to external sources of support. Hierar-chical nonlinear models account for dependenceamong cases clustered within level 2 units, de-compose variance in the dependent variable acrosslevels of analysis, and can be extended to incor-porate Rasch measurement models as a separatelevel in the analysis. For analyses of the ChicagoHealth and Social Life Survey subsample, how-ever, within-neighborhood subsamples are small(ranging from 1 to 8 with a mean of 2.6). Con-sequently, variance components should be inter-preted with caution. The hierarchical models ofsevere violence and conflict disclosure presented

below were also estimated as single-level modelswith robust variance estimates. The magnitudesand significance levels of coefficients were quite

similar, enhancing confidence in the fixed effectsestimates presented below. This section briefly de-scribes the construction of the neighborhood-levelsurvey-based indicators and the justification forthe use of the multilevel Rasch approach for con-

flict disclosure.The measure of collective efficacy used in the

analysis was constructed with a three-level HLM(Bryk & Raudenbush, 1992; Sampson et al.,1997). Following Sampson et al., at level 1, a lin-ear item-response model adjusts individual-levellatent collective efficacy scores for missing dataand measurement error, taking into account thedifficulty level of items for which a response wasprovided. At level 2, neighborhood collective ef-ficacy scores (intercepts in between-individualmodels) are adjusted for the social composition ofChicago neighborhoods through the inclusion ofcontrols for gender, age, race/ethnicity (Black orLatino vs. White), education, employment status(employed vs. not employed), marital status (nev-er married, separated, or divorced vs. married),home ownership, years resident in the neighbor-hood, and number of moves in the last 5 years.At level 3, adjusted neighborhood intercepts varyrandomly around the neighborhood grand mean.The empirical Bayes residual from the level 3model constitutes the collective efficacy score to

be employed as an independent variable in sub-sequent analyses of partner violence and conflictdisclosure. A two-level strategy (including thesame battery of individual-level controls) wasused to construct neighborhood-level measures offamily violence tolerance and violent victimiza-tion.

The choice of model specification for the anal-ysis of conflict disclosure was driven both by hy-potheses regarding the dynamics of communica-tion concerning relationship conflict and by theneed for a useful data reduction technique. Thechoice of a multilevel Rasch model (Cheong &Raudenbush, in press; Johnson, Raudenbush, &Sampson, 2001; Raudenbush & Sampson, 1999)was rooted in the observation that womens dis-closure of relationship conflict is more frequentwhen the contact or potential source of support isless formal and more familiar (Bowker, 1986,1993), suggesting the possibility that conflict dis-closure is sequentially organized. Thus, conflictmay be initially disclosed to friends with whomthe respondent has more frequent contact and then

to family members with whom interaction mayoccur on a less frequent but nevertheless relativelyintimate basis. Communication with more rela-

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tionally distal members of the partners familymay follow communication with the respondentsown family and friends. Finally, formal sources ofsupport, including the police, social workers, bat-tered womens shelters, and others, may be mo-

bilized in response to relationship conflict.Accordingly, the analyses presented below fit

a three-level Rasch model with random interceptsto a series of four dichotomous indicators of con-flict disclosure (to family, friends, partners fami-ly, and formal sources of support). The model em-ploys the logic of the original ability-testingapplication of the Rasch model with each conflictdisclosure target constituting an item, with a cor-rect response occurring when an individual indi-cates having disclosed conflict to a potentialsource of support. Item difficulty is the relativeformality of the conflict disclosure target, andability can be understood in this context as therespondents latent disclosure propensity. Themodel takes the following form: First, let Yijktakeon a value of unity if the ith conflict disclosureitem is endorsed by respondent j of neighborhoodk(otherwise,Yijk 0), and let ijkdenote the prob-ability that Yijk 1. At level 1, the log odds ofendorsement on response i are modeled as fol-lows:

3

ij kln D ,

jk p pi jk 1 p1ij kwhere jk is the intercept, Dpijkare grand-mean-centered indicator variables representing the con-flict disclosure items (with disclosure to friends asthe omitted reference item), and p reflects therelative formality of disclosure item p.At level 2(between individuals), individual demographicbackground, relational, and network characteris-tics are included in models of conflict disclosurepropensity (adjusted intercepts from the level 1

equation) as follows:

Q

r ,jk 0k q qjk jk q1

where 0k is the intercept, Xqijis the value of per-

son-level predictor q for individual j in neighbor-hood k, q is the effect ofq on individual js ex-pected disclosure propensity score, and rjk is anindependent, normally distributed error term withvariance 2. Finally, adjusted intercepts

0k are

modeled at the neighborhood level:S Z u .0k 0 s sk k

s1

Here, 0k is the disclosure propensity score for

neighborhoodkadjusted for individual, relational,and network characteristics,

0is the grand mean,

skis the value of covariate s (including collectiveefficacy and family violence tolerance scores) for

neighborhoodk, s is the effect of covariate s onneighborhood disclosure propensity, and uk is anindependent, normally distributed error term withvariance. Accordingly, the intraclass correlation(ICC) for disclosure propensity is /

2.To ensure that the Rasch specification of conflict

disclosure was appropriate, the four disclosureitems were independently analyzed with softwarespecifically designed to estimate item-responsemodels (Linacre & Wright, 1998; Wright & Stone,1979). Consistent with expectations, item difficul-ties were ordered in the hypothesized sequence:Disclosure to friends was most frequent, followedby disclosure to the respondents family, to therespondents partners family, and, finally, to for-mal sources of support. Although respondentsscores were somewhat skewed toward nondisclo-sure, item scores were well distributed across arange of logit values, indicating the absence ofitem clustering and large gaps in the scale. More-over, fit statistics provided strong evidence of theappropriateness of the Rasch specification. Stan-dardized item outfit statisticssensitive to unex-

pected behavior on the part of the respondent foritems far from the respondents ability levelranged from0.6 to 0.1, well within the expectedrange of2.0 to 2.0. Person outfit statistics iden-tified only four cases for which standardizedscores were greater than 1.99. These were casesin which respondents had disclosed conflict onlyto a formal source (one case) or to family and aformal source (three cases) but not to friends orto the partners family. The exclusion of these cas-es did not change the results of the analyses. Thus,independent assessment indicates the appropriate-ness of the Rasch specification for modeling con-flict disclosure.

RESULTS

The analyses begin with an investigation of themacrolevel determinants of intimate homiciderates across Chicago neighborhoods based on thecombined 1990 census, Project on Human Devel-opment in Chicago Neighborhoods CommunitySurvey, and Chicago homicide data (Table 2).

Model 1 includes measures of female popula-tion size and social composition. Both populationand concentrated disadvantage are positively and

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TABLE2.INTIM

ATE-PARTNERHOMICIDE(FEMALEVICTIMIZATION)BY

NEIGHBORHOOD

CHA

RACTERISTICS(N

343)

Independ

entVariable

Model1

Coefficient

SE

Model2

Coefficient

SE

Model3

Coefficient

SE

M

odel4

Coefficient

SE

Femalepopulation

Concentrateddisadvantage

Residentialstability

Immigrantconcentration

Collectiv

eefficacy

1.0003**

1.889**

0.963

1.101

0.0001

0.187

0.199

0.210

1.0003*

1.303

1.270

1.007

0.481**

0.0001

0.227

0.223

0.217

0.234

1

.0003*

1

.307

1

.266

1

.017

0

.482**

0.0

001

0.2

27

0.2

24

0.2

20

0.2

34

1.0003

*

1.088

1.278

1.021

0.532*

0.0001

0.326

0.225

0.228

0.246

Noninter

ventionnorms

Violentvictimization

Intimate-partnerhomiciderate(19911993)

Cutpoin

t1

Cutpoin

t2

df

LR2

3.020**

4.827**

421.1

5

0.514

0.592

3.075**

4.921**

531.3

5

0.524

0.604

0

.960

3

.079**

4

.926**

631

.41

0.1

73

0.5

25

0.6

04

0.966

1.190

1.069

3.363*

*

5.219*

*

833.5

1

0.174

0.163

0.084

0.614

0.685

Note:Effectsofindependentvariablesareex

pressedasoddsratios.

Standarderrorsremaininlogform.

*p

.05.

**p

.01(two-tailed).

significantly associated with intimate-partner ho-micide. An increase of one standard deviation inthe concentrated disadvantage scale increases theodds of falling into a given homicide count vari-able category or above 89%. Residential stability

and immigrant concentration, however, are notsignificant predictors of intimate-partner homicideat the neighborhood level.

With the introduction of collective efficacy inModel 2, the odds ratio for concentrated disad-vantage is substantially reduced and rendered non-significant. The negative effect of collective effi-cacy on intimate-partner homicide against womenis robust to alternative model specifications. Thepresence of norms of nonintervention in familydisputes and its interaction with collective efficacy(data not presented) are not significant predictorsof partner homicide; nor is violent victimizationor the 19911993 intimate-partner homicide rate.The magnitude of the association between collec-tive efficacy and intimate homicide (Model 4) issubstantialan increase of one standard deviationin collective efficacy results in a 47% reductionin the odds of the number of intimate-partner ho-micides meeting or exceeding a given level withinChicago neighborhoods.

Of the three social composition variables em-phasized by social disorganization theory, only

concentrated disadvantage is associated with inti-mate-partner homicide. This result is contrary tothe expectations of Hypothesis 1 with respect tothe effects of residential stability and immigrantconcentration. However, consistent with Hypoth-eses 2a and 2b, the effect of concentrated disad-vantage is mediated by collective efficacy, whichexerts a powerful negative effect on intimate-part-ner homicide rates in Chicago communities. Thus,social organization plays an important role in thedistribution of lethal partner violence at the ma-crolevel. Finally, the effect of collective efficacyon intimate homicide is not conditioned by normsof nonintervention (Hypothesis 2c).

Does the association between collective effi-cacy and partner violence hold at the individuallevel (i.e., controlling for individual-level factorswith which neighborhood social organization maybe correlated)? Hierarchical logistic regressionanalyses predicting womens involvement in non-lethal but severely violent relationships were per-formed on the combined census, Project on Hu-man Development in Chicago Neighborhoods,

and Chicago Health and Social Life Survey dataand are reported in Table 3. The ICC for the un-conditional two-level model indicates that 14% of

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TABLE 3. HIERARCHICALLOGITMODELS OF SEVEREVIOLENCE ONINDIVIDUAL, RELATIONSHIP, NETWORK, ANDNEIGHBORHOOD CHARACTERISTICS(N 199)

Independent Variable

Model 1

Coefficient SE

Model 2

Coefficient SE

Model 3

Coefficient SE

Individual/relational/network characteristicsRace (vs. White)African AmericanLatina

Age (1829 vs. 3059)

0.1750.7993.600*

0.9080.7840.583

0.2060.6183.688*

0.9400.8160.606

0.2870.8298.093**

1.0190.8440.624

Touched sexually in childhoodLess than high school educationPersonal income of$10,000MarriedRelationship duration

2.4301.3471.1120.7920.919

0.8100.6790.8090.6390.378

1.9660.7991.0900.8810.990

0.7550.6790.8370.6180.403

4.6880.9192.0040.8461.076

0.9821.0870.8750.6990.428

Years resident in neighborhoodFree time with mutual friends/familyJealous conflictNumber of conflict sources

Neighborhood characteristics

0.9890.5822.9301.992**

0.0190.5490.6170.244

0.9900.6182.8921.952**

0.0220.5900.6650.245

0.9571.3066.234**2.056**

0.0330.7780.6830.231

Concentrated disadvantageResidential stabilityImmigrant concentration

1.4781.0681.863

0.5340.2790.462

1.4950.9691.679

0.6410.5840.647

Collective efficacyNorm of noninterventionNonintervention Collective EfficacyViolent victimization

0.226**2.450*3.438**1.324

0.6550.3950.4570.368

ConstantNeighborhood variance component

2.895**0.602

0.874 3.034**0.350

0.986 5.712**0.026

0.967

Note: A population average model with robust standard errors is used. Effects of independent variables are expressed asodds ratios. Standard errors remain in log form.

*p .05. **p .01 (two-tailed).

the variance in partner violence can be attributedto the neighborhood level. Although the between-neighborhood variance component does notachieve the conventional level of significance, themagnitude of the ICC and the relatively limitedstatistical power with which to detect interceptvariation suggest that the existence of variation atthe neighborhood level cannot be ruled out.

Model 1 of Table 3 considers only individual-level predictors of partner violence. Althoughyoung adults are significantly more likely to reportviolence in their relationships, Model 1 offers noevidence that African American and Hispanicwomen are more likely to experience violent part-nerships. Indeed, apart from age, only the numberof conflict sources reported by the respondent wasassociated with victimization. These findings arein line with some previous research that achievedonly limited explanatory power at the individuallevel in predicting a womans likelihood of ex-periencing partner violence (OLeary et al., 1994).The intercept variance reported for Model 1 (0.60)

is somewhat larger than that for the unconditionalmodel (0.52).

Census-based measures of neighborhood social

composition are entered in Model 2. Althoughconcentrated disadvantage is strongly associatedwith the intimate-partner homicide rate againstwomen at the macrolevel, this measure, alongwith residential stability and immigrant concentra-tion, is not directly associated with partner vio-lence at the individual level when backgroundcharacteristics are controlled, a finding inconsis-tent with Hypothesis 1. Nevertheless, the interceptvariance for Model 2 (0.35) represents a reductionfrom that for Model 1 (0.60).

Neighborhood-level measures of collective ef-ficacy and norms of nonintervention and their in-teraction are entered in Model 3. As hypothesized,the average effect of collective efficacy is negativeand significantly associated with partner violenceindependent of individual and relationship fea-tures that increase the risk of violence. However,increasingly prevalent nonintervention norms, onaverage, lead to an increase in the likelihood ofpartner violence among women. This finding sug-gests the importance of neighborhood-level tol-

erance of intimate-partner violence above and be-yond that of collective efficacy and individual andrelational factors. Although it is unclear why non-

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intervention norms would effect nonlethal but notlethal partner violence, this finding may reflect thefact that normative tolerance of violence is notlikely to extend to homicide. These neighborhood-level effects are consistent with both the collec-

tive-efficacy perspective and institutional theoriesthat posit a normatively rooted reluctance to in-tervene in intimate relationships.

Model 3 also indicates that collective efficacyinteracts with nonintervention norms in its asso-ciation with partner violence. The positive andsignificant effect of the interaction term indicatesthat as nonintervention norms increase, the nega-tive effect of collective efficacy decreases in mag-nitude. The regulatory impact of collective effi-cacy on the prevalence of partner violence islarger when intervention in intimate relationshipsis normatively sanctioned. For instance, when in-tervention in intimate relationships is not norma-tively approved (with the nonintervention scaleset at one standard deviation above the mean), thepredicted probability of severe violence changesfrom .05 to .08 with a movement from 1 to 1standard deviation on the collective efficacy scale(with other covariates being held at their samplemeans). When intervention is approved (with thenonintervention scale set at one standard deviationbelow the mean), the same movement on the col-

lective efficacy scale changes the predicted prob-ability of violence from less than .01 to .14. Insum, neighborhood structural characteristics arenot associated with severe partner violence, chal-lenging Hypothesis 1. However, neighborhood so-cial process measures exert nontrivial, interactiveinfluences on the likelihood of womens involve-ment in a violent partnership, a finding that is con-sistent with Hypotheses 2a and 2c.

A second stage of the analysis focused on onepossible mechanism through which collective ef-ficacy may influence the prevalence of violentpartnerships: conflict disclosure. Specifically,structural characteristics, collective efficacy, indi-vidual background, relationship factors, and net-work opportunity are included in three-levelRasch models predicting the likelihood of the dis-closure of relationship conflict. Although the re-sults presented use the full sample (N 199),separate analyses were performed on a restrictedsample of respondents for whom relationship con-flict was unambiguous (those respondents who re-ported at least one of the conflict sources de-

scribed earlier, n 168). These analyses wereperformed to ensure that respondents who did notreport conflict over any of the substantive areas

considered in the Chicago Health and Social LifeSurvey (and thus potentially having no conflict todisclose) were not distorting the results of theanalysis. The pattern of significance and the mag-nitude of the coefficients were consistent with the

results presented here.Table 4 presents the results of multilevel Rasch

models omitting level 1 item severity coefficients.The ICC for the three-level model controlling onlyfor disclosure item difficulty (decomposing vari-ance at levels 2 and 3) indicates that 11% of thevariance can be attributed to the neighborhoodlevel ( 0.218,

2 1.742). Model 1 includesindividual-level characteristics and indicates thatyouth, a larger number of conflict sources, the ex-perience of violence in a relationship, and a largernumber of friends increase the likelihood of con-flict disclosure. Women aged 18 to 29 are signif-icantly more likely to disclose conflict to familymembers than are older women. Young womenmay be more predisposed to disclosing conflictbecause of changes in normative interpretations ofrelationship conflict. Consistent with the notionthat opportunity may influence the likelihood ofdisclosure, an increase in the respondents numberof friends increases communication with regard toconflict in relationships. Individual-level predic-tors included in model 1 result in a decline in the

between-neighborhood variance from 0.219 to0.112.

The remaining models presented in Table 4 in-clude structural and survey-based neighborhood-level indicators to predict conflict disclosure.Model 2 includes concentrated disadvantage, res-idential stability, and immigrant concentration,none of which significantly predict conflict disclo-sure. Structural characteristics also accounted fora modest proportion of the intercept variance.Model 3 includes measures of collective efficacyand nonintervention norms. Consistent with Hy-pothesis 3, collective efficacy exerts a significantimpact on the likelihood of conflict disclosure, in-creasing the odds of disclosure to a typical sourceof support by 57%. Nonintervention norms andthe interaction between nonintervention normsand collective efficacy (not presented) are not as-sociated with disclosure. The inclusion of collec-tive efficacy and nonintervention norms in Model3 accounts for the remaining neighborhood-levelvariance, reducing the intercept variance compo-nent from 0.079 to 0.002.

In summary, collective efficacy is a strong andconsistent predictor of intimate-partner homicideperpetrated against women, nonlethal but severe

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TABLE 4. COEFFICIENTS FOR THREE-LEVEL RASCH MODELS OF CONFLICTDISCLOSURE ON INDIVIDUAL, RELATIONAL,NETWORK, AND NEIGHBORHOOD CHARACTERISTICS(N 199)

Independent Variable

Model 1

Coefficient SE

Model 2

Coefficient SE

Model 3

Coefficient SE

Individual/relational/network characteristicsRace (vs. White)African AmericanLatina

Age (1829 vs. 3059)

1.1550.5132.316**

0.2600.3830.296

0.8840.4722.411**

0.3660.3890.316

1.0240.4972.499**

0.3500.3830.314

Less than high school educationPersonal income of$10,000MarriedAny violenceNumber of conflict sources

0.7020.7800.9542.083**1.302**

0.3060.3340.2690.2600.080

0.6720.7850.9892.034**1.306**

0.3030.3480.2720.2680.079

0.6770.6961.0792.270**1.311**

0.3110.3560.2770.2670.077

Years resident in neighborhoodNumber of friends

Neighborhood characteristics

1.0001.177*

0.0110.071

1.0001.182*

0.0120.073

0.9981.197*

0.0110.074

Concentrated disadvantage

Residential stabilityImmigrant concentration

1.283

0.9401.015

0.258

0.1510.213

1.679

0.8051.168

0.272

0.1530.233Collective efficacyNorm of nonintervention

1.565**0.855

0.1480.112

ConstantVariance components

Within neighborhoodsBetween neighborhoods

0.322

1.4150.112

0.296 0.215

1.4250.079

0.335 0.345

1.4310.002

0.336

Note: A population average model with robust standard errors is used. Effects of independent variables are expressed asodds ratios. Standard errors remain in log form.

*p .05. **p .01 (two-tailed).

violence, and disclosure of conflict in intimate re-lationships to potential sources of support. Al-though neighborhood nonintervention norms werenot related to the prevalence of intimate homicideagainst women, these norms, when more preva-lent, reduce the regulatory impact of collective ef-ficacy on severe but nonlethal partner violence.Thus, both neighborhood-level processes are rel-evant to the distribution of violence between in-timate partners.

DISCUSSION

Social disorganization theorists have not extendedthe explanatory purview of their model to includeviolence between intimate partners despite stronglogical grounds upon which to extend the theory,in addition to its success in explaining rates ofcriminal activity operationalized to include inti-mate violence. The purpose of this research wasto apply social disorganization theory to violencein intimate relationships by employing data re-sources that link community characteristics to

both intimate-partner homicide rates and individ-ual-level partner violence for women in Chicago.The analyses also considered the disclosure of

conflict in relationships as a potential mechanismthrough which communities exert regulatory ef-fects on the prevalence of intimate violence.

Initial analyses investigated the relationshipbetween neighborhood characteristics and inti-mate homicide rates in Chicago neighborhoods.Consistent with social disorganization theory,community-level concentrated disadvantage wasassociated with rates of intimate homicide perpe-trated against women, although residential stabil-ity and immigrant concentration were not associ-ated with this outcome. Moreover, a measure ofcollective efficacydescribing neighborhood so-cial cohesion and informal social controlmedi-ated the association between neighborhood con-centrated disadvantage and intimate-partnerhomicide, reproducing the general pattern of as-sociation found in previous research on neighbor-hood social organization and homicide (Sampsonet al., 1997). The results of these analyses offerstrong evidence of the relevance of social disor-ganization and collective efficacy theory to lethalviolence between intimate partnerscrimes typi-

cally hypothesized to be insulated from the impactof community factors.

Community-level nonintervention norms were

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not associated with rates of intimate-partner ho-micide. Arguably, this finding is consistent withthe theoretical thrust of the normative argumentregarding tolerance of intimate violence. Althoughsome communities may support a norm of privacy

regarding conflicts within families or between in-timates, presumably this tolerance does not extendto the perpetration of lethal violence. When vio-lence or the threat of violence extends beyond acertain threshold, communities may feel obligatedto intervene.

Neighborhood characteristics were also rele-vant to the perpetration of nonlethal violenceagainst women, although a different patternemerged. When individual, relational, and net-work predictors of partner violence were con-trolled for, none of the three structural character-istics were associated with relationship violence.Although limitations in the size of the sample mayrender the detection of effects more difficult, thesefindings nevertheless challenge the expectations ofsocial disorganization theory with respect to theimpact of neighborhood structure.

In contrast, collective efficacy and noninter-vention norms were both associated with nonle-thal severe violence and interacted with regard totheir effects on this outcome. The conditional ef-fect of collective efficacy on nonlethal violence

calls for more subtle investigation of the effectsof neighborhood social organization on behaviorsthat maintain a normatively ambiguous status. So-cial disorganization theory and its more recent in-carnations rely on the assumption that consensusholds within neighborhoods regarding the value ofa crime-free environment. The assumption of ashared understanding of crime is less controversialwhen index offenses among nonintimates are con-sidered (Bursik & Grasmick, 1993). Violence be-tween family members or intimates, however, maybe subject to competing normative interpretationsthat, in turn, have consequences with regard to theinvolvement of neighborhoods in its regulation.This possibility was borne out by the positive av-erage effect of neighborhood noninterventionnorms on the prevalence of partner violence andthe dampening effect of nonintervention norms onthe regulatory impact of collective efficacy. Thus,social organization is relevant to the prevalence ofnonlethal partner violence, but only in contexts inwhich the tolerance of intimate violence is low.

In general, however, these findings are consis-

tent with the hypothesis that socially organizedcommunities are better equipped to manage theexposure of women to potentially violent men.

The impact of collective efficacy on partner vio-lence may be channeled in part through percep-tions among women that cohesive communitiesare more effective in combating partner violence.Findings from an analysis of the likelihood that

women would disclose conflict in their relation-ships to various potential sources of external sup-port are consistent with the suggestion that sociallyorganized communities promote communicationwith regard to conflict in relationships. Residencein communities with high levels of collective ef-ficacy significantly increased the likelihood thatwomen would disclose conflict in their relation-ships.

The communitys capacity to elicit the disclo-sure of relationship conflict and, in turn, to act onbehalf of women may operate as a mechanismthrough which informal social control is mobi-lized to manage the prevalence of violent partner-ships. Chronically or severely violent partnershipsmay remain private (and persist) in part becausewomen perceive their social environment as beingunable or unwilling to provide effective socialsupport. Thus, the explanation for why somewomen remain in chronically violent relationshipsmay be found as much in the available and per-ceived avenues for a successful exit from the re-lationship as in the characteristics of the men and

women involved. Indeed, apart from age and re-lationship conflict, individual characteristics didnot offer consistent explanatory power in account-ing for the prevalence of partner violence amongwomen. The relative ineffectiveness of individual-level characteristics in explaining partner violenceis consistent with results of other investigationsthat have failed to uncover consistent predictorsof womens involvement in intimate violence(OLeary et al., 1994). Although it remains un-clear whether distinct processes predict involve-ment in intimate violence for men and women(Moffitt & Caspi, 1999), a future focus on socialorganizational characteristics of communities inwhich women are embedded may give researchersmore insight into the social processes that engen-der and maintain intimate-partner violence.

Although the data resources employed here al-lowed for a multilevel analysis of partner violencewith high-quality measures of the relevant theo-retically derived causal processes, the analyseswere nevertheless hampered by inherent limita-tions. Although the Project on Human Develop-

ment in Chicago Neighborhoods Community Sur-vey and the Chicago Health and Social LifeSurvey were independent data sources collected

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in a temporal sequence that matched the hypoth-esized causal process, both were cross-sectional,and the sample size of the latter limited the sta-tistical power of the analyses. Ideally, future re-search will address these issues with larger scale

prospective data sets that can be used for a moreeffective examination of the causal linkages be-tween community structure, social organization,conflict disclosure, and violent outcomes. The ro-bust effects of collective efficacy and neighbor-hood tolerance norms in a small sample, however,highlight the strength of the association betweenthese social processes and womens involvementin violent partnerships.

Researchers interested in social disorganizationand collective efficacy models of neighborhoodcrime should reconsider the artificially narrowuniverse of outcomes to which the theory hasbeen applied. Increasingly, research is suggestingthat the scope of neighborhood effects may extendinto intimate relationships, previously consideredbeyond the reach of collective influence (Brooks-Gunn, Duncan, Klebanov, & Sealand, 1993b).Culturally pervasive conceptions of the privatenature of intimate relationships should not obscurethe potentially consequential embeddedness ofthese relationships in broader communities. Thesefindings should encourage a continued focus on

the communitys capacity to shape the formation,maintenance, and content of intimate relation-ships.

NOTE

This research was supported by a grant from the HarryFrank Guggenheim Foundation. I also gratefully ac-knowledge Robert J. Sampson and Felton Earls for pro-viding access to data from the Project on HumanDevelopment in Chicago Neighborhoods CommunitySurvey and Edward O. Laumann for providing accessto the Chicago Health and Social Life Survey. I thank

Paul Bellair, L. Phillip Schumm, Martha Van Haitsma,and Lisa Morrison for providing comments on an earlierdraft. This research was conducted with the support ofthe John D. and Catherine T. MacArthur Foundation,the National Institute of Justice, and the National Insti-tute of Mental Health. The findings reported in this pa-per do not necessarily represent the views of these or-ganizations.

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