Jeffres, L. W., Atkin, D., & Neuendorf, K. A. - Academic Server ...

Political Communication, 19:387–421, 2002 Copyright ã 2002 Taylor & Francis 1058-4609 /02 $12.00 + .00 DOI: 10.1080/0195747029005557 4

A Model Linking Community Activity and Communication With Political Attitudes and Involvement in Neighborhoods LEO W. JEFFRES, DAVID ATKIN, and KIMBERLY A. NEUENDORF

Although people tend to mobilize around local problems and restrict their political involvement at other times, the political communication literature generally has focused on national politics and elections. This is particularly surprising in investigations of political involvement since it is at the community level that people should feel more efficacious. Also, both mass and interpersonal communication should be more significant locally given their importance in strengthening community ties. The study reported here focuses on these relationships in a community context, with a survey of six inner-city neighborhoods and six suburbs classified on status using location and census data. Results point to a much more positive role for the media in community politics. Those most likely to rely on neighborhood newspapers as sources are less disillusioned with government, suggesting that the most “grassroots” of print media are more efficacious in their impact than the other channels. Also, readership of a daily newspaper is particularly strong as a predictor of both community political involvement and faith in community civic involvement. Results of the macro analysis suggest that urban sprawl may have consequences for how media affect political involvement. In the data here, distance from the center city and stratification are closely tied—the further out the community, the higher its status. Results by neighborhood structure indicate media specialization as well as a greater dependence on media versus interpersonal influence in the political arena. Thus, we see that political involvement and attitudes are more strongly related to reading the daily newspaper in the more distant suburbs than in the center city. Keywords communication behaviors, community level, neighborhood behaviors, political attitudes, political involvement

Although people tend to mobilize around local problems and restrict their political involvement at other times, the literature on political communication generally has focused on partisan politics and elections at the national level. This is particularly surprising since it is at the community level and in day-to-day problem solving where people This article is based in part on a paper presented to the Communication Theory and Methodology Division of the Association for Education in Journalism and Mass Communication at its annual conference in Phoenix, Arizona, August 2000. Leo W. Jeffres, David Atkin, and Kimberly A. Neuendorf are Professors in the Department of Communication at Cleveland State University. Address correspondence to Leo W. Jeffres, Department of Communication, Cleveland State University, Cleveland, OH 44115, USA. E-mail: [email protected]

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should feel their involvement in political life is more effective. It is also at the local level that communication channels—both mass media and interpersonal—should be more significant given their importance in strengthening community ties (Stamm, 1985). Posing questions at the community level allows us to examine a more complex model of relationships employing both objective and subjective measures. Classic sociological models stress the impact of social structure on political processes, and parallel work in communication has emphasized structural influences on communication processes. Framing questions at this level allows us to ask to what extent social structure constrains patterns of communication and community ties, which in turn help explain the individual’s relationship to local political processes.

The Impact of Social Structure on Political Processes Structural explanations for people’s behaviors are found not only in the political domain but also in urban studies and other areas. In several classical perspectives, social structural variables are largely responsible for political processes that reflect the relationship between citizens and their government. Thus, mass society and classical sociological views stress objective conditions of social estrangement. According to Marx and Engels, people’s alienation reflected structural relationships and forces beyond their control— institutions that separated man from labor, nature, and the political community. This led people to feelings of powerlessness and normlessness, conditions in Durkheim’s (1893/ 1933) concept of anomie.1 In urban studies, macro influence is expressed in part through the linear hypothesis,2 which begins with the notion of community size, seen as affecting social diversity and related behaviors.3 In a study following this tradition, Sharp (1980) found city size related to citizen efforts to contact advocacy groups, demonstrating that social structure can affect political variables directly. The range of political behaviors subjected to scrutiny in the macro tradition is meager considering the diverse ways to describe the relationship between citizens and their government—people’s interest in politics, attitudes toward the political system, political involvement, beliefs about the system, opinions about topical issues, and reports of actual political behaviors. Political Interest Probably the most basic expression of citizens’ relationship to their government is the simple expression of interest in government and politics. For many years, observers have been dismayed at an apparent lack of interest by Americans in politics. National surveys of U.S. adults in the past decade or so have shown 10% to 15% indicating an active interest in politics, with 35% to 40% showing interest but little activity and 15% to 20% showing no interest at all.4 Although studied at the individual level, interest in politics itself is correlated with social categories such as education and status, key measures in structural models. Interest also is related to communication patterns—talking about politics and following it in the media. Attitudes Toward Political Processes and the Government People’s feelings of how connected they are to politics are captured by several concepts tapped in studies of political attitudes and beliefs: political cynicism, distrust of government, disillusionment with government, anomie, powerlessness, political alienation, and

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efficacy. These are the key political variables featured in classical structural explanations (Simmel, 1950), and they have been related to status measures at the individual level (Himmelstein & McRae, 1988; Luo, 1998). Political trust “refers to the faith people have in their government” (Citrin & Muste, 1999, p. 465), and it belongs to a group of terms reflecting citizen support for the political system.5 The extent to which citizens feel they have a minimal connection with the exercise of power is reflected in the notion of political alienation (Reef & Knoke, 1999). Lane (1962) defines alienation to refer to one’s “sense of estrangement from the politics and government of his society” (pp. 161–162). The concept’s antonym, efficacy, refers to the belief that one can have an impact on political decision making and desired outcomes.6 Efficacy and related concepts are associated with important behaviors in a democracy. People’s beliefs about their collective ability to make changes—collective efficacy—were seen as an important factor in Poland’s turn to liberal democracy and the success of collective political action (Reykowski, 1998).7 In the United States and elsewhere, political efficacy has been linked to voting and political activity (Pinkleton, Austin, & Fortman, 1998; Wollman & Stouder, 1991) and to citizen participation and mobilization (Finkel, 1987; Yeich & Levine, 1994; Zimmerman, 1989). Political Activity Citizen involvement in political processes outside of elections is most likely to occur at the community level, particularly among nonactivists. Residents tend to mobilize around local problems in their immediate communities, and restrict political involvement at other times. Whether residents get involved depends on their faith that such action is viable. Thus, we need to pay attention to political activity, as well as attitudes reflecting beliefs that the political system “works” and that people feel they count—a notion captured by the concept of political efficacy. Mobility and community integration have been linked to such political activity. Stamm, Emig, and Hesse (1997) combined four measures into a “community involvement” index that was strongly related to media use and interpersonal communication, particularly among those who were settling into the community, those who consider themselves permanent residents but who have lived there less than 5 years.8

Communication and Community Structure In the communication literature, scholars employing pluralism theory argue that changes in social structure affect patterns of communication, producing a line of impact from size to social structure to communication. Social status has been linked at the individual level to measures of social relations and interpersonal communication patterns (Logan & Spitze, 1994; Olsen, Perlstadt, Fonseca, & Hogan, 1989). Huckfeldt and Sprague (1987) note that people may choose their friends and have some control over their conversations, but these are bounded by the environment. In their study of South Bend, Indiana, both individual preference (whether or not neighbor discussants shared their voting preference) and context (preference of the neighborhood in which one lives) affected the accuracy of predicting voting preference of one’s neighbors. Straits (1991) found that people discuss politics more often with closer associates, with people of the same social status, and with politically compatible discussion partners. In addition, media themselves in the pluralistic tradition reflect the community they

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serve. The media are viewed as operating in support of the larger system, as agents of social control (Tichenor, Donohue, & Olien, 1980; Viswanath & Demers, 1999). Scholars in mass communication using the pluralism model to study mass media and communities have examined the knowledge gap (Gaziano, 1989; Gaziano & Gaziano, 1999; Griffin, 1990; Viswanath & Finnegan, 1991), the critical nature of corporate newspapers located in larger, more pluralistic communities (Demers, 1996, 1998), an increased emphasis on conflict in newspapers located in more pluralistic communities (Hindman, 1996), and a greater likelihood for newspapers to lay blame rather than to downplay environmental risks in larger communities (Dunwoody & Griffin, 1999). We also know that social status is related to media use (Gollin, 1991; see also Jeffres, 1994, pp. 230– 232) at the individual level.

Community Structure and the Relationship Between Communication and Political Participation The political communication literature has demonstrated the importance of both interpersonal communication and mass media as influences in partisan election processes.9 McLeod et al. (1996) show the importance of traditional and nontraditional media forms in elections and democratic processes, and Pfau, Diedrich, Larson, and Van Winkle (1995) found interpersonal communication dominating all other communication modalities in influencing voters’ perceptions of candidates during the distant phase of primaries. Other studies have found people alternating between media and interpersonal sources, as audiences use each as a reality check against the other, depending on the topic and circumstances (Chaffee, 1972; O’Keefe & Atwood, 1981). Clearly, people’s evaluations of candidates, issues, and parties are influenced by what their neighbors say as well as mass media. Mass and interpersonal communication channels also are influential outside of the election context, particularly in the formation of public opinion and general social attitudes that affect the political arena. Smith (1987) found that newspaper coverage of issues affected public evaluation of government services, and Guo and Moy (1998) found media affecting political interest and political knowledge.10 The spiral of silence theory also links interpersonal communication in public contexts with media coverage and opinion formation.11 Both mass and interpersonal communication variables are important for political processes, but interpersonal communication variables seldom have been measured in studies focusing on political involvement, political efficacy, and associated concepts. Willnat (1995) found political efficacy related to political outspokenness, and Austin and Nelson (1993) examined the influence of family communication on efficacy. Political attitudes and efficacy often are linked to media use. Treating media behaviors as dependent variables, Tan (1981) found that political participation and political efficacy predicted media use for Whites, and Newhagen (1994) found efficacy predicting call-in to a political TV show. McLeod and Perse (1994) found print media use correlated with political efficacy, but no relationship was found for watching the news on television; strong linkages between perceived utility indicators (community involvement, political interest, and instrumental media orientation) and newspaper use led them to conclude that people for whom public affairs knowledge is important and useful turn to newspapers for information.12 The literature does not explore how macro variables affect the relationship between communication and political participation. Since structural models exist for both sets of


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variables, one could argue that the relationship between measures of communication and political behaviors at the individual level is merely a reflection of the community structure. However, such an explanation ignores the complexity of both phenomena and the potential number of variables represented by each. Ultimately it is an empirical question, although a study that looked at macro and micro explanations for community ties and social relations provides some clues. Sampson (1988) used a national sample of 10,905 residents in 238 localities in Great Britain to examine friendship ties and community attachment. He sought to examine macrosocial determinants of community social organization and effects of community structure on individuals. The major prediction was that length of residence and community residential stability would be positively related to one’s local friendships, community attachment, and participation in local activities. Results showed that collective levels of attachment are lowest in communities with residential mobility, higher urbanization, density of youth, and high levels of fear about crime. Rates of total leisure and social activity were explained by three community characteristics: residential stability, urbanization, and levels of fear. Looking at the effect of community structure on individuals, he found that length of community residence was the largest predictor of individual local friendships, as hypothesized. However, residential stability also had an impact, positively affecting local friendship ties— so both the context and individual-level variables had an impact. An extension of this to studies of communication and political participation would suggest that structure is important but not the only factor. Shifting our focus from the societal level to the community allows us to examine structural and individual-level explanations in a model that includes not only the communication and political variables suggested by the literature but also social structure and relations. The community context is infrequently examined in studies of the complex set of influences on people’s political attitudes and behavior. Friedland and McLeod (1999) note that the community is the ideal substantive unit for investigating complex social structures: “It is the smallest whole unit that remains large enough to contain the multiple levels of action that are meaningful for understanding integration” (p. 222).

A Community-Level Model of Relationships Communities can be viewed as a set of overlapping systems that include a communication network and a social structure, as well as the full array of political variables that interest scholars during and between elections. The model in Figure 1 places in an array a complex set of relationships between variables based on the literature in political science, communication, sociology, and urban studies. The model includes the following ingredients: social structure, social relations and neighborhood behavior patterns, neighborhood communication, community attachments, and political variables representing people’s connections to their government. At the end of the model are political variables reflecting an interest in politics and faith in community involvement, activities showing community political involvement, and attitudes demonstrating disillusionment with government. The model, which includes both macro variables and those measured at the individual level, directs us to consider influence in two ways. One focuses on the relationships among competing influences as they predict the criterion political variables. Another shifts analyses to the community level, asking whether these relationships and influences persist in communities of different structures. These theoretical concerns are raised in several research questions and hypotheses based on the literature examined.

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Social Structure Macro Variables

Demographics/ Social categories

Community location (city/suburb) Community status

Gender Education Income Age

Involvement in local activities Neighboring Perceptions of community solidarity/cohesion Community attachment Perceptions of neighborhood quality of life

Communication Pattern Interest in community news Channel dependency for local news Strength of neighborhood communication pattern Interpersonal communication pattern Mass media use

Political Variables Attitudes & Activity Community political involvement (activity) Political attitudes: Faith in community involvement Disillusionment with government

Figure 1. Key variables.

Social Structure First in the model are macro measures of social structure, which are seen as constraining community attachments and communication variables and potentially affecting political attitudes and behaviors directly. The macro variable to which influence is generally attributed in political communication research is status, whether operationalized as power in studies employing the pluralistic perspective or as community social status, a concept parallel to that at the individual level. A host of social categories other than social status have been found to influence political efficacy at the individual level, including education, gender, age, religion, ethnicity, language, residence, and economic status.13 Size and location of communities often have been taken as indicators of social structure (see Demers, 1996; Tichenor, Donohue, & Olien, 1980). The nature of the neighborhood social structure at any given point in time potentially has a strong impact on the nature of its communication system and politics. In the study reported here, two measures of macro structure—social status and location—are examined for their impact on individual-level behaviors. Research Question 1: How do political attitudes and behaviors reflecting citizens’ connections to politics differ by community social structure? Social Structure and Communication The literature shows status related to media use and to some interpersonal communication patterns, as described above. We would expect proportionally less communication with neighbors and more communication with those outside neighborhoods among people of higher socioeconomic status (SES). However, in contemporary society modern transportation, mobility, and mass media help overcome obstacles of physical distance to social associations (Blau, 1977, p. 4; see also Blum, 1985). Extending our expectations to the community context, we would expect a community’s social status to have a strong positive relationship with status measures at the individual level, but the extent to which it constrains communication variables—both interpersonal and mass communication


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patterns and their relationships with other variables, such as community activity and political variables, is an open research question. Thus, we would expect differences in communication patterns by community social structure. Research Question 2: How do communication patterns differ by community social structure? Social Structure, Social Relations and Neighborhood Behavior Patterns A community’s social structure also can affect residents’ social relations, although empirical evidence on the relationship between neighborhood characteristics and social relations is mixed. There are a number of variables here that often are blurred from study to study, including concepts of neighboring and neighborhood activities or involvement; the former generally refers to patterns of caring, assistance, and friendship between neighbors, while the latter generally is employed to discuss residents’ involvement in community groups or organizations but could extend to cover a much broader sense of people’s utilization of their community resources. In recent literature, the concept of “social capital” often has been operationalized to include several of these concepts. Bleiker (1972) notes that in a Massachusetts study of a complex, heterogeneous urban area, the nature of personal relations was not adequately explained by proximity, age, or social class. Greider and Krannich (1985) found data refuting the popular notion that primary neighboring interaction declines with the onset of rapid population growth and heterogeneity. Silverman (1986) found that the correlation between urbanism and neighboring was an artifact of how neighboring is defined.14 Given these relationships, social structure would be expected to affect neighborhood behavior patterns. Research Question 3: How do community attitudes and behavior patterns (neighboring and engaging in neighborhood activities) differ by community social structure? Neighborhood Communication and Community Attachments People are linked to their community through local media that inform them about their environment and interpersonal networks that link them to neighbors and open them up to opportunities for sharing their political beliefs and exposing them to beliefs of others. Greer (1962) notes the importance of communication—interpersonal and mass media— for interdependent social groups to coordinate their behavior in cities. Doheny-Farina (1996) argues that one’s sense of community arises out of interactions that take place in local contexts such as school board meetings and similar events. Community linkages have been related to media use since Robert E. Park’s (1929) work in Chicago more than a half century ago. Four different ties to a community were related to media use by Viswanath, Finnegan, Rooney, and Potter (1990). Collins-Jarvis (1992) found that community identification predicted community newspaper use. Stamm (1985) found people’s use of newspapers linked to their integration into a community (Stamm & Guest, 1991). Blau (1977, p. 38) notes the importance of neighborhood for social interaction (see also Jeffres, 2002). Jeffres and Dobos (1995) found people’s perceptions of the quality of life in their communities related to media use. In general, we would expect neighborhood communication to be positively related to neighborhood activity and to neighborhood feelings; the two sets of variables are most likely mutually reinforcing across time.

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Leo W. Jeffres et al. Hypothesis 1: Neighborhood interpersonal and mass communication behaviors will be positively related to (a) neighborhood behavior patterns (neighboring and engaging in neighborhood activities) and (b) community attachments.

Importance of Communication Processes for Political Attitudes and Involvement No one has related involvement in communication networks at the community level with such political variables as efficacy, although some studies have produced results relevant to our discussion of such democratic processes; for example, Dougherty (1988) examined participation in community organizations and its impact on political and personal efficacy, and McLeod et al. (1996) found measures of neighborhood communication positively correlated with local political interest and with community knowledge. Despite considerable study of the relationships between communication variables and people’s political attitudes and behaviors, these processes have not been examined at the neighborhood level where the focus is on local neighborhood involvement. The literature reviewed points to newspaper reading—particularly attention to news—as the most important media behavior. In addition, interpersonal communication has been linked to several political behaviors through spiral of silence research. Extrapolating from these, we frame the following hypothesis: Hypothesis 2: Media use and interpersonal communication at the community level will be related to political involvement and political attitudes at the community level. Community Attachments People are moved to political action at the local level when some of their identity is linked to the community in which they live, and those who live in a neighborhood the longest have the strongest investment. In the Sampson (1988) study, residential stability had independent but less powerful effects on collective attachment to community as well as participation in local social activities.15 Thus, we need to examine the affective link between residents and their community. Such affective ties certainly are related to one’s pattern of communication and community relations. Rothenbuhler, Mullen, DeLaurell, and Ryu (1996) found community involvement related to community attachment, which was measured using items tapping whether residents feel a part of the community, are proud of the community, are happy living there, and how they would feel if they had to move. Heller (1989) notes that community group attachments are at the core of selfidentity and self-efficacy. Based on this literature, we frame the following expectations for neighborhood relationships. Hypothesis 3: Involvement in neighborhood activities will be positively related to political involvement and political attitudes. Hypothesis 4: Neighborhood attachment will be positively related to political involvement and political attitudes. Residents’ affective attachment to the neighborhood appears to fit into a mutually supportive pattern of strong communication links and community activity. The stronger one’s neighborhood activity, the greater one’s opportunity for interpersonal communication and the greater the perceived utility of neighborhood newspapers (i.e., perceived


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potential for uses and gratifications). These measures of community communication are expected to strengthen both neighboring and neighborhood affect. Clearly, those with the strongest interpersonal links are more likely to engage in neighboring, and reliance on the neighborhood newspaper for local news should enhance neighborhood affect. Since the relationship between neighborhood communication patterns and residents’ community attachment, behaviors, and involvement is seen as reinforcing, we pose the following research question to sort out the strength of competing influences on political attitudes and involvement posed in the preceding hypotheses. Research Question 4: Do communication variables and measures of community attachment, behaviors, and involvement compete as influences on political attitudes and involvement?

Testing a Community Model The variables are arrayed in a model that fits the bivariate relationships articulated by the literature but makes some choices to reduce the complexity. Looking at similar v ariables, McLeod et al. (1996) focused on community integration and democratic processes. Here, we also focus on the community as a system but separate both mass and interpersonal communication variables from measures of neighborhood activity and attachments so we can see how they fit into an overall system that also includes the macro variable, community social status, two measures of individual social status— education and income—and partisan identification (see Figure 1). The community model also allows us to ask how social structure affects relationships among individual-level variables. The focus here is on the relationships between communication and political variables noted above—that media use and interpersonal communication are related to political involvement and political attitudes. Thus, we add the following research question. Research Question 5: Does community structure (status, location) affect the hypothesized relationships between communication variables and political involvement and attitudes? The variables in the model are operationalized in the next section.

Method In the fall of 1999, different inner-city neighborhoods and suburban communities from a major midwestern metropolitan area were selected in a project examining relationships between the nature of the communities and behavioral patterns within them. Six city neighborhoods, three first-ring suburbs, and three outer-ring suburbs were selected and U.S. Census data matched with the communities to allow for classification in subsequent analysis. The survey interview schedule operationalized variables that reflect concepts in communication; neighborhood attachments, perceptions, and activities; and political involvement and attitudes. Together, the census data and survey allow us to test two sets of relationships: (a) between community social status classifications based on census data and location and survey measures (community attachments, attitudes, and behaviors; mass and interpersonal communication variables; and political attitudes and behaviors) (the first three research questions) and (b) between the different sets of survey measures operationalizing the concepts described above (the four hypotheses and

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the fourth research question). In addition, using the macro variable of community status as a dummy variable allows us to use both sets of variables to test a path model employing selected measures. A sample of residents from each of the 12 neighborhoods was drawn for a survey conducted by the Communication Research Center in the fall of 1999 using a CATI (computer-aided telephone-interviewing) system. Interviewers introduced the study as a “survey of residents from your community about local problems and how they keep up with what’s going on in their neighborhood. ” A total of 389 residents were interviewed, about 30 from each of the 12 neighborhoods. A variety of items were included to measure the concepts, as described below. Macro Variables The two macro variables, neighborhood status and location, were operationalized as follows. For location, neighborhoods were categorized as central city, first-ring suburbs, or outer-ring suburbs. The sample included six central city neighborhoods, three firstring suburbs, and three outer-ring suburbs. Neighborhood status arrays the communities into three equal groups of four neighborhoods based on mean income according to census data. The location and status variables do not correspond to each other perfectly, although they are closely related.16 Neighborhood Activity Several variables operationalize neigborhood behaviors and community attitudes and attachments. Neighborhood Activity. Respondents were asked to use a 5-point scale ranging from “almost never” to “all the time” to indicate how often they did various things in their neighborhood, including going to shops and banks, attending a church or religious institution, going to the public library, walking down a neighborhood street, going to a fraternal club or hall, going to a neighborhood park, eating at a neighborhood restaurant, going to a neighborhood pub or bar, visiting a recreation center, visiting a neighborhood school, and going to meetings of neighborhood groups such as block clubs or other organizations. These items have been used in several studies (see Jeffres, 2002) to measure neighborhood activities across various contexts. The items were summed for a scale of neighborhood activity (a = .64). Neighboring. Respondents were asked to use the same 5-point scale to indicate how often they and their neighbors entertain one another in their homes or yards. A second item asked how many of the people they knew in the 10 houses or apartments closest to theirs. Both items are modifications of those in Wallin’s Scale for Measuring Women’s Neighborliness (Wallin, 1953). The two items are highly correlated (r = .35, p < .001), but a scale based on standardized responses to the two items has an alpha of only .52, so the items are examined independently in analyses. Neighborhood Attachment. Respondents used a 0–10 scale (0 = completely disagree, 5 = neutral, and 10 = completely agree) to indicate the extent to which they agreed with the following three items: “I enjoy living in this neighborhood ”; “I feel involved in my community”; and “If I had to move, I’d really miss my neighborhood. ” The items were


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standardized and summed for a scale of neighborhood attachment (a = .76). These items come from Jeffres, Cutietta, Lee, and Sekerka (1999) and include items used by Stamm (1985) and Rothenbuhler et al. (1996). Perceived Community Solidarity. Respondents used the same 0–10 scale to indicate the extent to which they agreed with the following items taken from Fessler’s (1952) scale tapping perceived community solidarity: “Real friends are hard to find in this community”; “I feel like I belong in this neighborhood ”; “This neighborhood lacks real leaders”; “Almost everyone is polite and courteous to you in this neighborhood ”; and “People work together to get things done in this neighborhood. ” Because of low reliability, the items were factor analyzed, and two dimensions emerged. The first factor— labeled neighborhood camaraderie—accounted for almost 40% of the variance and reflected positive attachment and feelings of working together; the items loading on this factor were “I feel like I belong in this neighborhood ”; “Almost everyone is polite and courteous to you in this neighborhood”; and “People work together to get things done in this neighborhood. ” The factor score was used to represent this variable (a = .72). The two items loading on the second factor were “This neighborhood lacks real leaders” and “Real friends are hard to find in this community.” This factor accounted for 23% of the variance. Since the alpha for a scale based on these two items was only .37 and they do not represent conceptual coherence, the items are analyzed independently when included in analyses. The bivariate correlation is .23 (p < .001). Perceived Neighborhood Quality of Life. This was a single item: “I’d like you to imagine a scale from 0 to 10, with 0 being the worst place to live and 10 being the best place to live. On this scale, how would you rank the neighborhood in which you live?” This item has been used in a variety of studies (Jeffres & Dobos, 1993; Andrews, 1986; Campbell, Converse, & Rodgers, 1976). Neighborhood Affect. A scale of neighborhood affect was constructed using standardized scores of neighborhood camaraderie, perceived neighborhood quality of life, and community attachment (a = .78). Communication Patterns Neighborhood Communication. Three items were used to tap the strength of one’s involvement in the neighborhood communication network. Responses to each were standardized before they were summed for the scale (a = .65). First, respondents were asked to use a 5-point scale to indicate how often they talk over the fence or sit on the porch in their neighborhood. Second, they were asked how many of the 10 closest neighbors they knew well enough to say hello or good morning to when they met them on the street. Third, respondents were asked to use a 0–10 scale where 0 meant they completely disagreed, 5 was neutral, and 10 meant they completely agreed with the following statement: “I spend more time talking with my neighbors than most people do.” 17 Interest in Neighborhood News and News Sources. A single item was used to ascertain residents’ interest in neighborhood news: Respondents were asked “How interested are you in news about what’s going on in the [name] neighborhood? On a 0–10 scale where 0 means you’re not at all interested, 5 is neutral, and 10 means you’re very interested,

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what number expresses how interested you are?” Then respondents were asked to use a 5-point scale ranging from almost never to all of the time to indicate how often they get neighborhood news from (a) other people in the neighborhood, (b) local community organizations, (c) neighborhood newspapers such as [name], (d) from the [name of largely suburban weekly chain], (e) the [name of metro daily], and (f) from radio or television. Responses to the two items representing the importance of community newspapers were standardized and added for a scale (a = .62). Although the importance of people and organizations as news sources were correlated (r = .29, p < .001), the index based on them was unreliable (a = .45); similarly, the importance of the metro daily and of local broadcast media as sources of neighborhood news were correlated (r = .37, p < .001), but the index was not sufficiently reliable (a = .54). Thus, these variables were examined individually when included in analyses. Interpersonal Communication Links. Respondents were asked to think about the number of people they had talked with “today” in different contexts, including: within their household, relatives in the neighborhood, others in the neighborhood (see item above), people at work (if they worked outside the home), people elsewhere in the city, and people they talked with by telephone, both local and long distance. The items were standardized and factor analyzed using principal components and varimax rotation; two factors emerged. The first factor, which accounted for 29% of the variance, included all communication outside the family and relatives—work, neighborhood, community, and telephone. These items were summed for a public interpersonal communication index (a = .62). The other items were dropped from further analysis. Mass Media Use. Respondents were asked how many hours of TV they watched yesterday, how many hours they listened to the radio, how many days last week they read a newspaper, the number of different magazines read regularly, the number of books read in the past 6 months, the number of borrowed or rented videos watched in the past month, and the number of times they went out to see a movie in a theater in the past month. The individual measures of media use are examined initially, but the medium that the literature confirms is the most important for political behavior—newspaper reading— is featured in multivariate analyses. Political Variables Faith in Citizen Involvement. This variable reflects the concept of political efficacy. Respondents used the same 0–10 scale cited above to indicate how much they agreed with the following statements: “I am usually interested in local elections”; “People like me have much to say about government”; and “The average person can get nowhere by talking to public officials.” The items were taken from Schuessler’s (1982) Faith in Citizen Involvement subscale, part of his Social Life Feelings Scales.18 However, the reliability for a scale employing all three items showed that the third item—“The average person can get nowhere by talking to public officials”—did not fit, and it was removed. The alpha for the final two-item scale was .68. Community Political Involvement. Respondents were asked whether they had done five things, and the number was summed for this scale: contacted your city council representative about something, written a letter to a public official, discussed civic problems frequently with more than one person, contributed money to a political candidate, and


399

worn a button or posted a sign for a political candidate (a = .61). These items were modified from Miller’s scorecard for community services activity (see Miller, 1991, pp. 424–425). Disillusionment with Government. Using the same 0–10 scale, respondents indicated how much they agreed with the following two statements: “Most politicians are more interested in themselves than in the public” and “I have little confidence in the government today.” Responses were standardized and added for the scale (a = .62). Both items were taken from Schuessler’s (1982) Disillusionment with Government subscale, part of his Social Life Feelings Scales. Demographics. Standard items were used to ascertain respondents’ marital status, age, education, and household income.

Results and Analysis The respondents included 389 persons, 46% men and 54% women. The sample matches the demographics of the communities surveyed,19 and the partisan identification reflects the heavily Democratic district. Some 27% said they were strong Democrats, 23% leaned toward Democrats, 24% were independents, 12% leaned toward Republicans, and 6% were strong Republicans. Political partisanship was unrelated to any of the measures of political involvement or political attitudes, so it was excluded from the model. Macro Differences: Research Questions 1 to 3 The first three questions asked whether the sets of individual-level political, communication, or community variables would vary by macro variables representing community structure. Table 1 breaks down political variables by both macro variables, location and status. We find that only the measure of reported involvement in political activities produces statistically significant results; the further out from the center, the higher the level of community involvement and the higher the community status, the higher the involvement. Differences between communities by location and status approach significance for the scale combining faith in community civic involvement and community political involvement; however, the trend is no longer linear, with middle-status and first-ring communities demonstrating the lowest level of involvement. Communication variables are broken down by community location and status in Table 2, where we find that interest in neighborhood news is highest in the low-status communities, followed by the high-status communities and, lastly, middle-status communities (p < .02). First-ring suburbs also show the lowest interest in neighborhood news relative to the other two groups, but the overall ANOVA only approaches statistical significance.20 An examination of channel dependence for community news shows that community newspapers assume a greater importance the further out a community’s location and the higher the status; however, only the difference by location is statistically significant. People are more important sources of neighborhood news in low-status communities and the central city neighborhoods, followed by outer-ring suburbs and high-status communities; the pattern by status is statistically significant. Organizations are more important in middle-status communities, but the difference only approaches significance. The scale tapping strength of neighborhood communication varies for both macro measures. The highest level is achieved in central city neighborhoods, followed

400

Leo W. Jeffres et al. Table 1 Relationships between community structure and political variables Macro variables Neighborhood location

Neighborhood status

Central city

First ring

Outer ring

Low status

Middle status

High status

Faith in community civic involvement

–.01 (F = .89, n.s.)

–.09

.10

.03 (F = 1.2, n.s.)

–.11

.08

Community political involvement

–.11 (F = 4.3, p < .02)

–.04

.24

–.13 (F = 4.2, p < .02)

–.08

.20

Disillusionment with government

.16 (F = 1.6, n.s.)

–.17

–.12

.25 (F = 2.3, p < .10)

–.20

–.04

Political variables

Note: The macro variable neighborhood location includes six central city neighborhoods, three first-ring suburbs, and three outer-ring suburbs. Neighborhood status arrays the communities into three equal groups of four neighborhoods based on mean income according to census data. The dependent variables are all standardized variables. The number of cases varies slightly for neighborhood location (central city neighborhoods, 194; first-ring suburbs, 94; outer-ring suburbs, 101) and for neighborhood status (low status, 133; middle status, 125; high status, 131).

by outer-ring suburbs and then first-ring suburbs (p < .001); a linear relationship is found for community status (i.e., the higher the status, the lower the strength of neighborhood communication). Media use differences appear for specific media, particularly the two most important ones for news, newspapers and television. The further out and the higher the status of the community, the more frequent the newspaper reading. Also, the amount of time spent watching TV is highest in the central city and low-status neighborhoods and lowest in the first-ring and middle-status neighborhoods .21 No differences are found for public interpersonal links, but communication with family and relatives is highest in the central city and lower-status communities, most likely a reflection of larger families and proximity to relatives in those neighborhoods . The third research question asked how neighborhood behavior patterns differ by community structure. As Table 3 shows, the level of neighborhood activities is greatest in the suburbs and higher-status communities and lowest in the central city and lowstatus neighborhoods. The reverse is found for neighboring, which is highest in the central city and low-status communities and lowest in the suburbs. The measure of perceived community solidarity labeled “neighborhood camaraderie” shows a linear relationship with both macro variables; thus, the further out and the higher the status of the neighborhood, the greater the perceived solidarity of the community. The same pattern is found for perceived quality of life. Differences for community attachment follow the same pattern but are not statistically significant. The combined measure of neighborhood affect—reflecting both neighborhood attachment and perceived quality of life in the community—again shows the same relationship: The further out and the higher the status, the greater the level of neighborhood affect. With the exception of neighboring, the differences are consistent with the urban literature.


401

Table 2 Relationships between community structure and communication variables Macro variables Neighborhood location

Neighborhood status

Central city

First ring

Outer ring

Low status

Middle status

High status

.06 (F = 2.7, p < .07)

–.21

.07

.17 (F = 3.9, p < .02)

–.18

.01

–.28 (F = 2.3, p < .10)

.15

.39

–.18 (F = 8.5, p < .001)

–.08

.24

People

.10 (F = 1.6, n.s.)

–.15

–.06

.28 (F = 2.3, p < .10)

–.20

–.09

Organizations

–.04 (F = .45, n.s.)

.08

–.01

.07 (F = 2.6, p < .08)

–.17

.09

Metro daily

–.01 (F = .03, n.s.)

.02

–.01

–.01 (F = .39, n.s.)

.06

–.05

Radio-television

.04 (F = 3.1, p < .05)

.14

–.20

.05 (F = 1.4, n.s.)

.07

–.12

Strength of neighborhood communication

.45 (F = 8.4, p < .001)

–.68

–.26

.63 (F = 9.7, p < .001)

–.05

–.60

–.10 (F =5.1, p < .01)

–.09

.27

–.13 (F = 5.3, p < .01)

–.11

.23

.09 (F = 3.6, p < .03)

–.24

.05

.22 (F = 5.8, p < .01)

–.19

–.05

No. magazines read

–.02 (F = 1.1, n.s.)

.13

–.07

–.06 (F = .44, n.s.)

.06

.01

No. books read

–.08 (F = 3.2, p < .04)

.23

–.07

–.19 (F = 4.2, p < .02)

.17

.03

No. videos watched

–.10 (F = 3.0, p < .05)

.21

.00

–.15 (F = 3.5, p < .03)

.18

No. films watched

.06 (F = 1.7, n.s.)

.17

–.05

–.09 (F = .85, n.s.)

.04

.05

–.05 (F = .43, n.s.)

.05

.05

.01 (F = .05, n.s.)

–.02

.02

.15 (F = 4.5, p < .02)

–.17

–.16

.28 (F = 8.4, p < .001)

–.10

.00

Interest in neighborhood news Channel dependence for community news Community papers

Mass media use Days read newspaper Hours watch TV

Interpersonal communication links Public interpesonal Private-family, relatives

Note. The dependent variables are all standardized variables.

–0.1

402

Leo W. Jeffres et al. Table 3 Relationships between community structure and communication variables of respondents Macro variables Neighborhood location

Community variables of respondents

Neighborhood status

Central city

First ring

Outer ring

Low status

Level of neighborhood activities

–.90 (F = 6.0, p < .01)

.93

.88

–1.2 (F = 5.6, p < .01)

.68

.61

Neighboring variables Freq. entertain neighbors

.12 (F = 3.5, p < .05)

–.13

–.12

.16 (F = 4.1, p < .02)

.02

.18

Percent neighbors know

.14 (F = 5.7, p < .02)

–.28

–.02

.22 (F = 5.2, p < .01)

–.09

–.14

Perceived community solidarity Neighborhood camaraderie

–.13 (F = 3.9, p < .05)

.06

.20

–.18 (F = 4.1, p < .02)

.01

.18

Friends hard to find

.03 (F = .28, n.s.)

–.07

.00

.08 (F = 1.1, n.s.)

–.10

.02

Neighborhood lacks leaders

.04 (F = .44, n.s.)

–.08

.01

.15 (F =2.5, p < .08)

–.13

–.03

Community attachment

–.17 (F = 1.1, n.s.)

.04

.28

–.13 (F = .77, n.s.)

–.10

.22

–.27 (F = 15.8, p < .001)

.22

.32

–.40 (F = 18.5, p < .001)

.11

.30

–.58 (F = 6.6, p < .01)

.46

–.73 (F = 6.7)

.01

Perceived quality of life in neighborhood Neighborhood affect (attachment + perceived quality of life

1.1

Middle status

High status

1.0

Note. The community variables of respondents are standardized scores.

Communication’s Relationship With Neighborhood Variables The first hypothesis predicted that measures of mass and interpersonal communication at the community level would be positively related to both neighborhood behavior patterns (neighboring and engaging in neighborhood activities) and community attachments. Table 4 shows that interest in neighborhood news was correlated with all but two of the nine variables measuring community behaviors and attitudes. As the literature predicts and the data confirm, the greater one’s interest in community news, the higher the neighboring, the greater one’s involvement in activities, the greater the perceived camaraderie in the neighborhood, the higher one’s attachment to the community, the higher the perceived

403

.18*** –.12* .05 .06 .03 .11* .04

–.05 –.10* .08 .00 –.06 .08 –.04

.29**

.12* .11* .04 .07 .04 .00 .05 –.02

.18**

.04

.63**

.20** .29** .17** .03 .00

.19**

C

.12* .09 .03 .10† .06 –.05 –.08

–.01

.01

.34**

.18** .21** .20** .10* .07

.24**

D

–.10* .06 .00 .00 –.12* .01 –.04

.01

.04

–.13*

–.12* –.15** –.10* –.03 .04

–.02

E

.08 .15** .04 .11* .04 .02 –.03 –.04

–.09† –.05 .06 –.11* –.07 .04 –.04

.03

.39**

.18*** .31** .26** .10† .08

.33***

G

–.03

–.01

.02

–.10† .04 –.06 –.06 –.06

–.02

F

.08 .06 .04 .07 .01 .05 .01

–.04

.09†

.08

.06 .11* .10* –.04 –.02

.12*

H

.17*** .04 .09† .08 .05 –.02 –.04

.03

.06

.33**

.17*** .24** .24** .08 .04

.28***

I

Note. A: level of neighborhood activities; B: neighboring: entertainment; C: neighboring: percent neighbors know; D: perceived solidarity: neighborhood camaraderie; E: perceived solidarity: friends hard to find; F: perceived solidarity: neighborhood lacks leaders; G: community attachment; H: perceived quality of life in neighborhood; I: neighborhood affect. †p < .10; *p < .05; **p < .01; ***p < .001.

Media use Days read newspapers Hours watch television Hours listen to radio No. magazines read No. books read No. videos watched No. films watched

.51** .16**

.38**

Strength of community communication

.02 .33** .10* –.02 –.03

.11*

B

.15**

.23** .29** .34** .12* .01

Channel dependency for community news Community newspapers People Local organizations Metro daily newspaper Radio-television

Interpersonal comunication links Public contexts + phone Private-family, relatives

.21**

A

Interest in community news

Communication variables

Community variables of respondents

Table 4 Correlations between communication and community variables of respondents

A Model for Involvement in Neighborhoods 403

404


quality of life, and the greater the overall neighborhood affect. A similar pattern is found for channel dependency for community news, where the importance of community newspapers and both people and community organizations as news sources is positively correlated with the community variables. Metro media channels are relatively unimportant, with one exception: Reading the daily paper is correlated with the level of neighborhood activities. The scale reflecting the strength of community communication is strongly correlated with almost all of the community variables of respondents. Almost all of the relationships persist when household income, level of education, and gender are controlled. Of the communication variables, only attention to the two major news media— newspapers and television—and the number of interpersonal communication links are related to many of the community variables. Both measures of interpersonal communication links are correlated with involvement in neighborhood activities and neighboring but none of the attitudinal or affective measures. Newspaper readership is correlated with involvement in activities, perceptions of community solidarity (positive for camaraderie and negative for perceptions that the community is unfriendly and leaderless), community attachment, and the overall measure of neighborhood affect. Watching television is negatively associated with involvement in neighborhood activities and negatively associated with entertaining neighbors at home. The pattern of relationships generally persists with demographic controls. Communication’s Relationship With Political Variables The second hypothesis predicted that mass and interpersonal communication variables would be related to political involvement and political attitudes. As Table 5 shows, with the exception of disillusionment with government, the political variables are positively correlated with interest in community news; the importance of community newspapers, local people, community organizations, and the metro daily as sources of neighborhood news; the strength of community communication; newspaper readership; reading magazines; and reading books. In addition, the number of interpersonal communication links in public contexts is positively correlated with community political involvement. When demographics (education, household income, age, and gender) are controlled, the importance of the metro daily as a source of neighborhood news is not related to faith in community civic involvement, but the correlation with community political involvement (partial r = .11, p < .05) persists, as does the negative relationship with disillusionment with government (partial r = .10, p < .06). Relationships between the political variables and media use drop for all media use variables except newspaper readership, which continues to be positively correlated with both faith in community civic involvement (partial r = .16, p < .01) and community political involvement (partial r = .21, p < .001). Relationships Between Political and Community Measures The third and fourth hypotheses predicted positive relationships between measures of political involvement and attitudes at the community level and measures of neighborhood activities and attachment. As Table 6 shows, faith in community civic involvement and community political involvement are positively correlated with most of the community variables—involvement in neighborhood activities, neighboring, positive perceptions of neighborhood camaraderie, community attachment, perceptions of neighborhood


405

Table 5 Correlations between communication and political variables of respondents Political variables





Interest in community news

.38***

.26***

Channel dependency for community news Community newspapers People Organizations Metro daily newspaper Radio-television

.24*** .21** .26** .12* .05

.29*** .24** .30** .14* –.04

–.14** –.01 –.04 –.09† –.06

.24***

.21**

.02

.07

.16**

–.06

.02

.03

Strength of community communication Interpersonal communication links Public contexts + phone Private-family, relatives Media use Days read newspapers Hours watch television Hours listen to radio No. magazines read No. books read No. videos watched No. films watched

.30*** .05 .05 .12* .11* –.14** –.02

.32*** –.07 .07 .13** .11* –.05 .09†

–.05

.03 –.05 .01 .08 –.06 –.04 –.05 –.00

†p < .10; *p < .05; **p < .01; ***p < .001.

quality of life, and the composite neighborhood affect index. When age, income, education, and gender are controlled, the positive correlation with perceived quality of life drops out, and the partial between entertaining neighbors and faith in community civic involvement becomes significant (partial r = .16, p < .05). Disillusionment with government is positively related to perceptions that friends are hard to find and the neighborhood lacks leadership. Neighborhood Status and Relationships Between Communication and Political Variables The fifth research question asks whether and how community structure (status, location) affects the hypothesized relationships between communication variables and political

406

Leo W. Jeffres et al. Table 6 Correlations between neighborhood and political variables of respondents Political variables of respondents

Community variables of respondents Level of neighborhood activities Neighboring variables Freq. entertain neighbors Percent neighbors know Perceived solidarity Neighborhood camaraderie Friends hard to find Neighborhood lacks leaders Community attachment Perceived neighborhood quality of life Neighborhood affect index (neighborhood camaraderie + community attachment + perceived neighborhood quality of life)




.24**

.33**

–.05

.07

.16**

.01

.25**

.19**

–.02

.33** –.11*

.18** –.20**

.01

–.06

–.02 .15** .24**

.40**

.27**

–.06

.14**

.09†

.03

.38**

.26**

–.03

†p < .10; *p < .05; **p < .01; ***p < .001.

involvement and attitudes. The study provides an opportunity to see whether relationships examined persist across neighborhoods of different structures. Neighborhoods were categorized as central city, first-ring suburb, and outer-ring suburb. They also were arrayed into three groups of four neighborhoods based on mean income according to census data. Here we focus on the relationships found between communication and political variables. As Table 7 shows, interest in community news is strongly related to both faith in community civic involvement and community political involvement regardless of location or status of neighborhood. However, relationships between those variables and channel dependency change somewhat with status and location. Community newspapers appear to stimulate faith in civic involvement in the central city and first-ring suburbs but not in the outer ring. The reverse is found for reliance on people for community news, which stimulates such faith in the outer-ring communities but less so in the center city. Community political involvement, however, is strongly related to use of community papers, people, and organizations as sources of news across all neighborhoods. Reliance on the metro daily is correlated with the political variables in some communities, but the

407

.16* .24* .29**

.22** .39** .23*

.15* .09 .08

.09 .06 .00

Operations

Metro daily newspaper

Radio-television

.13 –.03 .05

.07 .19* .11

.14† .34** .31***

.09 .24** .30***

.35*** .27** .08

.42*** .35***

.39** .25* –.06

.36***

.45** .32**

Status: Low Medium High

.37**

People

Channel depemdency Community newspapers

Intererst in community news


Location: Center city First ring Outer ring


–.09 .09 –.01

.13† .14 .16

.33** .34** .24*

.27** .27** .20*

.32** .25* .21*

.28** .19*

.29**


.01 –.06 –.13

–.05 .02 –.25**

–.04 –.16† .04

.09 –.09 –.12

–.16† –.05 –.20*

–.14 –.11

.05


(Table continues on next page)

.02 –.15 –.13

–.02 –.18† –.18†

.17† .06 .20* .02 –.15† .03

–.05 –.07 .04

.00 .04 –.11

–.11 –.08 –.21*

–.03 –.08

–.05



.30*** .31** .31***

.22** .34*** .22*

.32*** .20* .31***

.20* .26**

.34***



Political variables

Table 7 Relationships between political and communication variables by neighborhood structure


408

Hours watch television

Media use Days read newspaper

Private-family, relatives

Interpersonal communication links Public contexts + phone

Strength of community communication

.08 –.10 .09

.23** .25* .46**

.05 –.01 .00

.06 .16 .01

.28** .17 .22*

Location Center city First ring Outer ring

.04 –.03 .12

.17* .27** .46***

.10 –.05 –.03

.06 .08 .08

.28*** .20* .25**

Status Low Medium High


–.07 –.13 –.03

.31** .31** .29**

.03 .14 .02

.24** .04 .10

.29** .14 .18†


–.03 –.21* .02

.23** .35*** .33**

.10 .04 .00

.28** .03 .17†

.28*** .26** .19*



Political variables

.06 –.06 –.07

–.08 .00 .01

.10 –.12 –.11

–.07 –.09 –.02

.05 –.04 –.10


.06 –.04 –.06

–.11 .03 –.03

.04 .13 –.10

–.08 –.05 –.06

.09 .02 –.12



Relationships between political and communication variables by neighborhood structure (Continued)


Table 7

408 Leo W. Jeffres et al.

409

–.12 –.06 .05

–.13 –.09 –.21*

.10 .15 .11

.12 .10 .17†

–.05 –.12 .30***

–.01 .25* .05

.00 –.09 –.12 .00 –.10 .20*

–.04 –.00 –.14†

.18* .15 .03

.18* .08 .15†

.13† .12 .18† .16* .06 .15

.01 –.04 .21*

.01 –.02 .24*

–.13† .08 .14

.04 –.11 –.08

–.04 –.07 .05

–.10 .10 –.07

.07 .03 .13

–.16† –.03 .11

.03 –.04 –.10

.00 –.18* .12

–.12 –.06 .04

.04 .08 .10

Note. The correlations represent relationships between the variables within neighborhood. For example, the correlation between interest in community news and faith in community civic involvement is .37 for center city neighborhoods, .45 for first ring suburbs, and .32 for outer-ring suburbs. Sample sizes vary slightly from the following: neighborhood location—central city neighborhoods, 194; first-ring suburbs, 94; outer ring suburbs, 101; neighborhood status—low status, 133; middle status, 125; high status, 131. Significance levels. †p < .10; *p < .05; **p < .01; ***p < .001.

–.09 .03 .20

No. films watched

.11 .13 .17†

No. books read

–.11 –.13 –.22*

.10 .15 .18†

No. magazines read

No. videos watched

–.06 .01 .29**

Hours listen to radio


410


pattern is mixed; reliance on the metro paper is negatively associated with disillusionment with government in the suburbs but not the central city. Reliance on radio and television for community news is largely unimportant. The strength of neighborhood communication is more strongly related to faith in community civic involvement and community political involvement in central city and lower-status neighborhoods. Neither of the measures of interpersonal communication links is particularly important, although the number of such links in public contexts (plus telephones) is correlated with community political involvement in the center city and low-status neighborhoods but not in the other communities. Reading a daily newspaper more frequently is correlated with both of the major political variables, but the relationships are strongest in the outer-ring communities. The other media use variable providing an interesting result is time spent listening to the radio, which is positively correlated with community political involvement and faith in community civic involvement. Since those living in the outer-ring suburbs have the longest commute, they are more likely to listen to “drive-time” programs, which may generate more attention to civic affairs through talk shows. Competing Predictors of Political Involvement and Attitudes Another research question asked how communication variables and measures of community variables at the individual level compete as influences on political attitudes and involvement. Regression was used to answer this question. Two sets of regressions were conducted; in one set, communication variables preceded the measures of community activity and attachment, while the reverse was true in the second set. In both sets, the macro-level variables were entered first, followed in some regressions by demographics. Table 8 summarizes the results for all regressions predicting the three political variables. In all pairs, communication precedes community variables in the first regressions (labeled A1 and B1), while community measures precede communication variables in the second regressions (labeled A2 and B2). A comparison of additional variance accounted for is an indication of their relative influence as predictors of political involvement and attitudes. Looking at the regressions predicting faith in community involvement, we see that communication variables explain more additional variance than do community variables in both relevant comparisons. With macro and communication variables in the equation, community variables explain an additional 5% of the variance, while communication variables explain an additional 13% when macro and community variables are in the equation. The same result is found in the second pairing (B1 with B2); with macro, demographic, and community variables already in the equation, communication variables explain an additional 7% of the variance, slightly more than the 5% additional variance explained by community variables in the same comparison. The same pattern is found when the dependent variable is community political involvement, but the reverse is found for disillusionment with government, where contributions by community variables provide the only statistically significant results; neither communication, macro variables, nor demographics is important in predicting disillusionment with government. 22 An examination of the impact of individual variables in the regressions predicting political variables reflects the pattern of correlations described above, with a few exceptions. Interest in community news makes a significant contribution in 8 of the 12 regressions, 75% of the time. Only two of the channel dependency measures are important; the importance of local organizations as sources of news accounts for a significant amount

411

.00 .21 .12 .05 .62, .38, 5.0***

Set B1c Macro variables Demographics Communication variables Community variables Multiple R, R 2, F

.00 .21

.00 .20 .13 .56, .32, 6.9***

Set A2b Macro variables Community variables Communication variables Multiple R, R 2, F

Set B2d Macro variables Demographics

.00 .27 .05 .57, .33, 6.2***

Set A1a Macro variables Communication variables Community variables Multiple R, R 2, F

R 2 change

.31, n.s. 17.6***

.31, n.s. 17.6*** 2.8*** 2.2

.25, n.s. 10.0*** 4.1***

.25, n.s. 8.1*** 3.1***

F change


.02 .13

.02 .13 .17 .05 .61, .37, 4.9***

.02 .15 .13 .55, .30, 5.5***

.02 .25 .03 .55, .30, 5.5***

R 2 change

3.2* 10.0***

3.1* 10.0*** 4.1*** 2.3*

3.5* 7.4*** 4.0

3.5* 7.4*** 1.8†

F change


.38, n.s. 1.7, n.s.

.38, n.s. 1.7, n.s. .96, n.s. 2.5**

1.0, n.s. 3.5*** .72, n.s.

1.0, n.s. .88, n.s. 3.1**

F change

(Tables continues on next page)

.00 .02

.00 .02 .05 .07 .39, .15, 1.5†

.01 .08 .03 .34, .11, 1.6*

.01 .04 .07 .34, .11, 1.6*

R 2 change


Table 8 Regressions predicting political variables from macro, communication, and neighborhood variables


.10 .07 .62, .38, 5.0***

4.3*** 1.7*

F change .12 .10 .61, .37, 4.9***

R 2 change 5.0*** 2.6**

F change


.08 .05 .39, .15, 1.5†

R 2 change

2.7** .90, n.s.

F change


a Significant betas for each step in the three regressions are: faith in community involvement, interest in community news .27***, reliance on local organizations for neighborhood news .13*, strength of community communication .16**, frequency read daily newspaper .20***, no. books read .11*, no. videos watched –.11*, community attachment, .22***; community political involvement, interest in community news .13*, reliance on community newspapers for neighborhood news .11*, reliance on local organizations for neighborhood news .16*, strength of community communication .14*, no. of public interpersonal communication links .09†, frequency read daily newspaper .20***, no. books read .08†, no. films seen in theater .09†, level of neighborhood activities .10†, hard to find friends in neighborhood –.10*, community attachment .14*; disillusionment with government, reliance on community newspapers for neighborhood news –.12#. b Significant betas for each step in the three regressions are: faith in community involvement, level of neighborhood activities .12*, no. neighbors know or recognize .12*, community attachment .30***, interest in community news .22***, reliance on local organizations for community news .09†, frequency read daily newspaper .18***, no. books read .09†, no. videos watched –.11*; community political involvement, level of neighborhood activities .20***, hard to find friends in neighborhood –.12*, community attachment .21*, interest in community news .11*, reliance on community newspapers for neighborhood news .10†, reliance on local organizations for neighborhood news .14*, no. of public interpersonal communication links .10†, frequency read daily newspaper .18***, no. films seen in a theater .08†; disillusionment with government, hard to find friends in neighborhood .10†, neighborhood lacks leaders .22***. c Significant betas for each step in the three regressions are: faith in community involvement, age .44***, household income .23***, interest in community news .20***, reliance on local organizations for neighborhood news .11†, strength of community communication .14*, hours watch television .12*, no. books read .10†, community activities .11†, community attachment .20*; community political involvement, age .27***, household income .18**, education .27***, interest in community news .11*, reliance on community newspapers for neighborhood news .10†, frequency read daily newspaper .15**, no. films seen in theater .09†, community activities .13*; disillusionment with government, education –.13†, reliance on community newspapers for neighborhood news –.13†, no. books read –.13†, hard to find friends in neighborhood, .12†, neighborhood lacks leaders .16*. d Significant betas for each step in the three regressions are: faith in community involvement, age .44***, household income .23***, community attachment .22*, hours watch television .13*, no. books read .10†, no. videos watched –.12†; community political involvement, age .27***, household income .18**, education .20**, level of neighborhood activities .26***, entertain neighbors in home .15*, interest in community news .13*, dependence on local organizations for community news .12*, frequency read daily newspaper .15*; disillusionment with government, education –.13†, hard to find friends in neighborhood .12†, neighborhood lacks leaders .18**, perceived neighborhood quality of life .14†. †p < .10; *p < .05; **p < .01; ***p < .001.

Community variables Communication variables Multiple R, R 2, F

R 2 change


Table 8 Regressions predicting political variables from macro, communication, and neighborhood variables (Continued) 412 Leo W. Jeffres et al.

412


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of variance in the political variables half of the time, while community papers do so 42% of the time. In none of the regressions does dependence on either the metro daily or radio-television as sources of community news make a significant contribution; however, individual measures of media use are important—readership of the daily newspaper makes a contribution 50% of the time, while reading books, watching television, watching videos, and going out to see films appear as significant predictors several times. The two most important predictors from the pool of neighborhood variables are level of neighborhood activities, which makes a significant contribution 58% of the time, and community attachment, which makes a significant contribution 50% of the time. The two neighboring variables and perceptions of the neighborhood quality of life make contributions once each. Perceptions of the neighborhood as unfriendly and leaderless are positive predictors of disillusionment with government three fourths of the time. Interestingly, dependence on community newspapers for neighborhood news also is negatively associated with disillusionment.

Conclusions Relationships identified in this study generally are consistent with the urban literature. There is a clear pattern of relationships between major communication variables—interest in neighborhood news, channel dependency, strength of community communication, and several media use measures—and community variables of respondents—involvement in neighborhood activities, neighboring, community attachment, and so forth. Communication variables also show a consistent pattern of positive relationships with faith in community involvement and level of community political involvement but not disillusionment with government. And those most involved in their communities, most attached to their neighborhoods, and with the most positive feelings toward their community also demonstrate the strongest faith in community civic involvement and community political involvement. Those with negative feelings toward the neighborhood are the most disillusioned. In the 1970s, a stream of research credited the mass media with a series of negative effects in the political and social arenas. Television in particular was credited with creating a “videomalaise” (Robinson, 1976) largely tested in the days of Vietnam and Watergate coverage but a theme that continued with the “media cultivation” of a mean and scary world (see Signorielli & Morgan, 1990). The results here point to a much more positive role for the media in community politics. Those most likely to rely on neighborhood newspapers as sources are less disillusioned with government, suggesting that the most “grassroots” of print media are more efficacious in their impact than the other channels. Looking at reports of actual media use, we find that readership of a daily newspaper is particularly strong as a predictor of both community political involvement and faith in community civic involvement. When other relationships appear, they are positive for print media and most entertainment media (film, video). The often found negative influence of television is absent and, in one instance, turns positive—with macro variables and demographics already in the equation, time spent watching television is positively related to faith in community involvement. Some of the bivariate relationships are reduced in regression analyses, but the strength of neighborhood communication, interest in neighborhood news, and reliance on neighborhood organizations as sources of news all explain faith in community involvement, and reliance on neighborhood newspapers is a predictor of community political involvement. With the other variables in the equation, the level of mass media use still makes a significant contribution in explaining

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community political involvement, and the contribution approaches significance for faith in community involvement. These findings resonate back to some of the earliest work in communication, where, for instance, Katz and Lazarsfeld (1955) proposed a multistep flow of media effects to replace more simplistic hypodermic needle comparisons. According to that model, most people receive media effects secondhand, via the influence of opinion leaders—a process that can be traced through the neighborhood interaction variables tapped here. Katz and Lazarsfeld’s original model viewed the masses as interacting individuals, as opinion leaders in turn are influenced by more elite media. These opinion leaders are, in most contexts explored here, more active in political affairs. More recently, researchers have expanded the multistep flow by suggesting that people within different social classes make very different interpretations of media. As Straubhaar and LaRose’s (1997) summary suggests: “People tend to talk about media to people similar to themselves in education, occupation, wealth and family background. Going beyond the idea of opinion leaders, people tend to interpret media content through discussion with key groups of people called ‘interpretive communities’ ” (p. 419). Clearly, the neighboring dimensions uncovered here represent important interpretive communities. It will be important, in later work, to see how new “collective” media channels such as the Internet might change proximal notions of neighboring to encompass larger, distal communities based on common interests. But, at the most foundational level, these findings provide further grist for the earliest public service dimensions of journalism upon which the founding fathers based our democracy. The fact that reliance on neighborhood media is related to faith in community and strength of community political involvement reinforces Walter Lippman’s initial charge for the journalist: “to provide a portrait of the world upon which the common man can act.” The important role played by print media use, in particular, reinforces the notion that the very health of democracy depends on a population that is print-literate. Results of the macro analysis suggest that urban sprawl may have consequences for how media affect political involvement. In the data here, distance from the center city and stratification are closely tied—the further out the community, the higher its status. Results by neighborhood structure indicate media specialization as well as a greater dependence on media versus interpersonal influence in the political arena. Thus, we see that political involvement and attitudes are more strongly related to reading the daily newspaper in the more distant suburbs than in the center city. As sprawl grows and metro media cater more to suburban audiences, their impact is likely to be greater among the more affluent suburbanites and less so in the center city. Some media specialization also is occurring, with radio’s growing importance in the outer ring, populated by commuters who see central city problems only as they pass by on freeways. In contrast, neighborhood papers are more important in the urban core. Although few differences are found between communication variables and disillusionment with government, one is particularly noteworthy; in the outer ring, reliance on the metro daily for community news is negatively associated with disillusionment with government. In the center city, reliance on community newspapers shows the same relationship. Thus, the different print media likely specialize in the uses and gratifications they provide residents. The dependence on media among the more affluent and distant neighborhoods is reinforced by data showing that strength of neighborhood interpersonal communication is more strongly related to community political involvement and faith in civic involvement in lower-status and central city neighborhoods .


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Notes 1. As Reef and Knoke (1999) note, in the past 40 years, almost all measures of political alienation and political efficacy, key concepts in the literature, have “abandoned the original structural meaning in favor of the citizens’ subjective feelings about their abilities to affect the political system’s performance” (p. 413). 2. The classic model in the tradition of Toennies (1887/1957) and Wirth (1938) says that size and density are the primary factors influencing social behavior; thus, urbanism is seen as weakening community kinship and friendship bonds, affectional ties for the community, and social participation in local affairs. Wirth had argued that social heterogeneity increases with community size, but, Wilson (1986) notes, he offered no rationale outside the occupational sphere. Wilson (1986) tested the notion that size also leads to heterogeneity in values and attitudes, using a national data set. Wilson found size associated with heterogeneity for political and sexual attitudes but not for attitudinal satisfaction. Abrahamson and Carter (1986) analyzed national data sets from 1947 to 1982 to study the effects of city size and region on indicators of tolerance, finding that the effect of city size declined while the effect of region remained. 3. Lindstrom (1997) argues that social bonds and solidarity have been transformed from affective ties into more diffuse relationships. “One of the classic questions in urban sociology is how social relations and solidarity are maintained in an urbanized, industrialized, bureaucratic society. The central theoretical and research focuses have been the issues of (1) the persistence of territorially based affective ties and primary relations in an urban world and (2) the micro/macro links connecting community residents and the larger society” (p. 19). Lindstrom adds that the “underlying assumption of the early Chicago School and of those theorists concerned with preindustrial solidarities in urban neighborhoods was that common locality (with its unique mix of territorially defined boundaries, organizational activity and population characteristics) is necessary for warm, intimate social bonds and social order” (p. 20; see also Wirth, 1938). Once successful people move from their immigrant neighborhoods, the link between affective ties and territory would dissolve. In the 1970s, researchers using a network analysis approach found evidence that individuals who had moved beyond their immigrant neighborhoods still maintained strong intimate ties with family and friends (Fischer, 1982; Granovetter, 1973; Kadushin, 1966; Laumann, 1973; Wellman, 1979). 4. Results of several polls are available from Public Opinion Online, the Roper Center. 5. Dahlgren (2000) chronicled the worldwide decline of public trust in formal political systems, and Putnam (1995) argued that civic engagement is associated with general trust in people, but both notions of trust have eroded in recent years (Brehm & Rahn, 1996). In the literature, trust has been examined in terms of political cynicism, confidence in government institutions, and support for democracy. Political cynicism has been negatively linked to voting behavior (Capeheart, 2000; Peterson & Wrighton, 1998; Southwell, 1995; Southwell & Everest, 1998). Fife-Schaw and Breakwell (1990) found that lack of interest in politics and cynicism about politics and politicians were the most powerful predictors of unwillingness to vote in a study of 17- and 18-year-olds in the United Kingdom. An American study of eligible voters found that cynicism had both positive and negative associations with voting efficacy (Austin & Pinkleton, 1995). Americans’ confidence in government also is low by historical standards (Lipset & Schneider, 1983; Lock, Shapiro, & Jacobs, 1999; Miller & Borrelli, 1991). 6. The literature on political efficacy and alienation is lengthy, with the concept occupying positions as dependent (e.g., Stewart & Weinstein, 1997), mediating (e.g., Sharp, 1980), and independent (e.g., Willnat, 1995) variables in various studies. Willnat found people’s political outspokenness boosted by higher political efficacy, political interest, and exposure to television news and news magazines. 7. Geyer and Heinz (1992) show the direction alienation and efficacy research has taken from its Marxist roots. In the past couple of decades, it has been applied to socialist states and consumer society in general rather than remaining as a critique of capitalist society. 8. Items in the index asked respondents to indicate how often they attended local government and public affairs, thought of ideas for improving the community, got together with others to talk about the community’s needs, and worked to bring about change in the community.

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9. Drew and Weaver (1998) found media use affecting interest in the 1996 presidential campaign, while Domke et al. (1997) found a powerful relationship between media coverage and public opinion in the same campaign. Also see Shaw (1999) and Lopez-Escobar, Llamas, and McCombs (1998). 10. Stamm, Johnson, and Martin (1997) found radio listening made as large a contribution to respondents’ knowledge of the Republicans’ Contract with America as did television viewing and newspaper reading. 11. See Jeffres, Neuendorf and Atkin (1999); Noelle-Neumann (1984); Salmon and Neuwirth (1990); Stevenson and Gonzenbach (1990); and Wyatt (1994). 12. Reversing the order of influence, Hollander (1997) and Barker (1998) found that listening to particular talk radio programs increased the individual political efficacy of conservative listeners, spurring them to action. Further evidence that media should be independent variables is found in a panel study by Semetko and Valkenburg (1998), where respondents’ initial internal political efficacy did not affect subsequent attentiveness to news, but initial attentiveness to news did enhance subsequent feelings of efficacy. Pinkleton, Austin, and Fortman (1998) found that media use was negatively related to cynicism toward the political system and positively related to political efficacy. Thus, patterns of communication are important factors in predicting political beliefs. 13. See Austin and Nelson (1993), McLeod and Perse (1994), Paulsen (1991), Paulsen and Bartkowski (1997), St. George and Robinson-Weber (1983), Sharp (1980), and Shrivastava (1989). 14. Analyzing a 1,050-person survey from 1977 to 1978 in northern California, Silverman (1986) measured neighboring as the number of neighbors who were not kin but who could be called upon to take care of the home. The association between urbanism (population) and neighboring dropped out when local variables (housing, ethnicity) were included in the model. In contrast to the classic model of Toennies and Wirth, Kasarda and Janowitz (1974) posited the systemic model, which focused on length of residence as the key exogenous factor affecting attitudes and behavior toward the community. Kasarda and Janowitz (1974) found that length of residence was positively related to local friendships, community sentiment, and participation in local affairs, independent of urbanization, density, SES, and life cycle. The longer people live in a neighborhood or community, the stronger their affective attachments with the area, regardless of other factors. 15. Consistent with the prediction of the systemic model of community (Kasarda & Janowitz, 1974), length of residence had direct effects on individual-level local friendships, attachment to community, and participation in local social activities. Furthermore, community residential stability had significant contextual effects on individual-level local friendships and participation in such local social activities as visitation, entertainment, and sporting events (Sampson, 1988, p. 778). Sampson’s (1988) data suggest that the important social forces that undermine an individual’s integration into the local community are not urbanization or such compositional factors as social class but such systemic factors such as residential mobility and sparse friendship ties, and other perceptual factors. 16. The number of respondents surveyed varies slightly for neighborhood location (central city neighborhoods, 194; first-ring suburbs, 94; outer-ring suburbs, 101) and for neighborhood status (low status, 133; middle status, 125; high status, 131). 17. Two additional items initially included were eliminated to increase scale reliability. Both items focused on a specific day rather than asking for reports of communication across a longer context. One asked residents if they had relatives living in the neighborhood and how many they had talked with that day. A second asked respondents how many people in the neighborhood (other than relatives) they had talked to that day, including neighbors or people at local stores, in public places, or on public transit. 18. Two of the items also are similar to the efficacy measure used by Pinkleton et al. (1998). The second item, “The average person can get nowhere by talking to public officials,” is similar to the single-item measure of political efficacy used by Sharp (1980) in her three-city study, “You can’t get any satisfaction from talking to public officials in this community.”


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19. The age ranged from 18 to 90, with a mean of 48; a fifth were 30 or younger, 18% were 31 to 40, 19% were 41 to 50, 11% were 51 to 60, 14% were 61 to 70, and 15% were 71 or older. Some 30% had a high school education or less, 36% had some college, 22% were college graduates, and 12% had advanced degrees. Some 38% reported household incomes in 1999 of $30,000 or less; 25%, $30,001 to $50,000; 14%, $50,000 to $75,000; and 10%, more than $75,000. 20. The contrast between first-ring versus central city/outer-ring suburbs is statistically significant (p < .02); however, the post hoc Scheffe test is more appropriate, and there the differences between first-ring and either central city or outer-ring suburbs’ interest levels only approach significance (p < .09). 21. Book reading and video viewing are highest in the first-ring and middle-status communities and lowest in the central city and low-status neighborhoods. No differences are found for listening to the radio, reading magazines, or going out to see films. 22. Results of individual regressions are available from the authors.

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