American Institute of Mathematical Sciences

Advanced
November  2020, 3(4): 249-262. doi: 10.3934/mfc.2020011

Network centralities, demographic disparities, and voluntary participation

Qiang Fu 1,, , Yanlong Zhang 2, , Yushu Zhu 3, and  Ting Li 4,

1. 

Assistant Professor, Department of Sociology, The University of British Columbia, Vancouver, BC, V6T 1Z1, Canada
2. 

Associate Professor, Guanghua School of Management, Peking University, Beijing, 100871, China
3. 

Assistant Professor, Urban Studies Program and School of Public Policy, Simon Fraser University, Vancouver, BC, V6B 5K3, Canada
4. 

Associate Professor, Center for Population and Development Studies, Renmin University, Beijing, 100872, China

* Corresponding author: Qiang Fu

Received  October 2019 Revised  March 2020 Published  June 2020

Fund Project: The first author is supported by The Lincoln Institute of Land Policy

This article explores racial and gender disparities in civic-network centrality using various social network methods and regression models. We find that civic networks of women and whites exhibit greater network centrality than their counterparts do. Religious organizations are the hub of civic networks, while labor unions and ethnic/civil-rights organizations are more peripheral. Whites tend to have job-related and nondomestic organizations as the core of their civic network. Women rely on domestic organizations and show little advantage over men in overlapping memberships of voluntary associations. These findings provide a more holistic view of racial and gender disparities in social networks.

Keywords: Social network analysis, network centrality, demographic disparity, voluntary participation.
Mathematics Subject Classification: Primary: 91D30, 62P25; Secondary: 91C20.
Citation: Qiang Fu, Yanlong Zhang, Yushu Zhu, Ting Li. Network centralities, demographic disparities, and voluntary participation. Mathematical Foundations of Computing, 2020, 3 (4) : 249-262. doi: 10.3934/mfc.2020011
References:
[1]

G. Almgren, M. Magarati and L. Mogford, Examining the influences of gender, race, ethnicity, and social capital on the subjective health of adolescents, J. Adolesc., 32 (2009), 109-133.  doi: 10.1016/j.adolescence.2007.11.003.  Google Scholar

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A. F. Aveni, Organizational linkages and resource moblization: The significance of linkage strength and breadth, The Sociological Quarterly, 19 (1978), 185-202.  doi: 10.1111/j.1533-8525.1978.tb01164.x.  Google Scholar

[3]

D. Baldassarri and M. Diani, The integrative power of civic networks, American Journal of Sociology, 113 (2007), 735-780.  doi: 10.1086/521839.  Google Scholar

[4]

K. Beyerlein and J. R. Hipp, From pews to participation: The effect of congregation activity and context on bridging civic engagement, Social Problems, 53 (2006), 97-117.   Google Scholar

[5]

S. P. Borgatti, M. G. Everett and L. C. Freeman, Ucinet 6 for Windows: Software for Social Network Analysis, Analytic Technologies, Cambridge, MA, 2002. Google Scholar

[6]

H. E. Brady, S. Verba and K. L. Schlozman, Beyond ses: A resource model of political participation, American Political Science Review, 89 (1995), 271-294.  doi: 10.2307/2082425.  Google Scholar

[7]

R. L. Breiger, The duality of persons and groups, Social Forces, 53 (1974), 181-190.  doi: 10.2307/2576011.  Google Scholar

[8]

C. Buchmann, T. A. DiPrete and A. McDaniel, Gender inequalities in education, Annual Review Sociolology, 34 (2008), 319-337.  doi: 10.1146/annurev.soc.34.040507.134719.  Google Scholar

[9]

W. K. Carroll and R. S. Ratner, Master framing and cross-movement networking in contemporary social movements, The Sociological Quarterly, 37 (1996), 601-625.   Google Scholar

[10]

H. Coffe and B. Geys, Measuring the bridging nature of voluntary organizations: The importance of association size, Sociology, 42 (2008), 357-369.  doi: 10.1177/0038038507087359.  Google Scholar

[11] J. S. Coleman, Introduction to Mathematical Sociology, Free Press, New York, 1964.   Google Scholar
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B. Cornwell and J. A. Harrison, Union members and voluntary associations: Membership overlap as a case of organizational embeddedness, American Sociological Review, 69 (2004), 862-881.   Google Scholar

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M. Diani, Leaders or brokers, in Social Movements and Networks, Oxford University Press, Oxford, 2003,105–122. doi: 10.1093/0199251789.001.0001.  Google Scholar

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C. S. Fischer, On urban alienations and anomie: Powerlessness and social isolation, American Sociological Review, (1973), 311–326. Google Scholar

[15]

L. C. Freeman, Centrality in social networks conceptual clarification, Social Networks, 1 (1978), 215-239.   Google Scholar

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Q. Fu, X. Guo and K. C. Land, A Poisson-multinomial mixture approach to grouped and right-censored counts, Communications in Statistics-Theory and Methods, 47 (2018), 427-447.  doi: 10.1080/03610926.2017.1303736.  Google Scholar

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Q. Fu, X. Guo and K. C. Land, Optimizing count responses in surveys: A machine-learning approach, Sociological Methods & Research, (2020). doi: 10.1177/0049124117747302.  Google Scholar

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Q. Fu, How does the neighborhood inform activism? Civic engagement in urban transformation, Journal of Environmental Psychology, 63 (2019), 1-8.   Google Scholar

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Q. Fu and K. C. Land, Does urbanisation matter? A temporal analysis of the socio-demographic gradient in the rising adulthood overweight epidemic in China, 1989–2009, Population, Space and Place, 23 (2017), 1-17.  doi: 10.1002/psp.1970.  Google Scholar

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Q. Fu, K. C. Land and V. L. Lamb, Bullying victimization, socioeconomic status and behavioral characteristics of 12th graders in the United States, 1989 to 2009: Repetitive trends and persistent risk differentials, Child Indicators Research, 6 (2013), 1-21.  doi: 10.1007/s12187-012-9152-8.  Google Scholar

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Q. Fu, K. C. Land and V. L. Lamb, Violent physical bullying victimization at school: Has there been a recent increase in exposure or intensity? An age-period-cohort analysis in the United States, 1991 to 2012, Child Indicators Research, 9 (2016), 485-513.  doi: 10.1007/s12187-015-9317-3.  Google Scholar

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Q. Fu and N. Lin, The weaknesses of civic territorial organizations: Civic engagement and homeowners associations in urban China, International Journal of Urban and Regional Research, 38 (2014), 2309-2327.   Google Scholar

[23]

Q. Fu and Q. Ren, Educational inequality under China's rural-urban divide: The Hukou system and return to education, Environment and Planning A, 42 (2010), 592-610.  doi: 10.1068/a42101.  Google Scholar

[24]

Q. Fu, C. Wu, H. Liu, Z. Shi and J. Gu, Live like mosquitoes: Hukou, rural-urban disparity, and depression, Chinese Journal of Sociology, 4 (2018), 56-78.  doi: 10.1177/2057150X17748313.  Google Scholar

[25]

A. Fung, Associations and democracy: Between theories, hopes, and realities, Annual Review of Sociology, 29 (2003), 515-539.  doi: 10.1146/annurev.soc.29.010202.100134.  Google Scholar

[26]

W. A. Gamson, The Strategy of Social Protest, The Dorsey Press, Homewood, IL, 1975. Google Scholar

[27]

J. Ginn and S. Arber, Gender, class and income inequalities in later life, British Journal of Sociology, 42 (1991), 369-396.  doi: 10.2307/591186.  Google Scholar

[28]

R. M. Groves, F. Fowler Jr., M. Couper, J. Lepkowski, E. Sniger and R. Tourangeau, Survey Methodology, Wiley & Sons, New York, 2004.  Google Scholar

[29]

R. Gulati and M. Gargiulo, Where do interorganizational networks come from?, American Journal of Sociology, 104 (1999), 1439-1493.  doi: 10.1086/210179.  Google Scholar

[30]

R. Gulati and M. Sytch, Dependence asymmetry and joint dependence in interorganziational relationships, Administrative Science Quarterly, 52 (2007), 32-69.   Google Scholar

[31]

R. A. Hanneman and M. Riddle, Introduction to Social Network Methods, University of California, Riverside, CA, 2005. Google Scholar

[32]

M. Hunter, "If you're light you're alright" light skin color as social capital for women of color, Gender & Society, 16 (2002), 175-193.  doi: 10.1177/08912430222104895.  Google Scholar

[33]

J. C. Jenkins, Resource mobilization theory and the study of social movements, Annual Review of Sociology, 9 (1983), 527-553.   Google Scholar

[34]

F. L. Jones, Sources of gender inequality in income: What the Australian Census says, Social Forces, 62 (1983), 134-152.  doi: 10.2307/2578352.  Google Scholar

[35]

D. Knoke, Associations and interest groups, Annual Review of Sociology, 12 (1986), 1-21.   Google Scholar

[36]

K. C. Land, V. L. Lamb, S. Meadows, H. Zheng and Q. Fu, The CWI and its components: Empirical studies and findings, in The Well-Being of America's Children, Springer, New York, 2012, 29–75. doi: 10.1007/978-94-007-4092-1_3.  Google Scholar

[37]

K. L. Land, P. L. McCall and D. S. Nagin, A comparison of Poisson, negative binomial, and semiparametric mixed Poisson regression models with empirical applications to criminal careers data, Sociological Methods & Research, 24 (1996), 387-442.  doi: 10.1177/0049124101029003004.  Google Scholar

[38]

J. S. Long and J. Freese, Regression Models for Categorical Dependent Variables Using Stata, Stata Press, College Station, 2006. Google Scholar

[39]

G. Marwell, P. E. Oliver and R. Prahl, Social Networks and Collective Action: A Theory of the Critical Mass. III, American Journal of Sociology, 94 (1988), 502-534.   Google Scholar

[40]

D. S. Massey and N. A. Denton, The dimensions of residential segregation, Social Forces, 67 (1988), 281-315.  doi: 10.2307/2579183.  Google Scholar

[41]

J. D. McCarthy and M. N. Zald, Resource mobilization and social movements: A partial theory, American Journal of Sociology, 82 (1977), 1212-1241.   Google Scholar

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S. McDonald and J. C. Day, Race, gender, and the invisible hand of social capital, Sociology Compass, 4 (2010), 532-543.  doi: 10.1111/j.1751-9020.2010.00298.x.  Google Scholar

[43]

J. M. McPherson, Hypernetwork sampling: Duality and differentiation among voluntary organizations, Social Networks, 3 (1982), 225-249.  doi: 10.1016/S0304-422X(01)80005-X.  Google Scholar

[44]

J. M. McPherson and D. L. Smith-Lovin, Women and weak ties: Differences by sex in the size of voluntary associations, American Journal of Sociology, 87 (1982), 883-904.   Google Scholar

[45]

M. McPherson, L. Smith-Lovin and M. E. Brashears, Social isolation in America: Changes in core discussion networks over two decades, American Sociological Review, 71 (2006), 353-375.  doi: 10.1177/000312240607100301.  Google Scholar

[46]

J. Moody, Race, school integration, and friendship segregation in America, American Journal of Sociology, 107 (2001), 679-716.  doi: 10.1086/338954.  Google Scholar

[47]

J. Moody and D. R. White, Structural cohesion and embeddedness: A hierarchical concept of social groups, American Sociological Review, (2003), 103–127. doi: 10.2307/3088904.  Google Scholar

[48]

P. Paxton, Social capital and democracy: An interdependent relationship, American Sociological Review, 67 (2002), 254-277.  doi: 10.2307/3088895.  Google Scholar

[49]

P. A. Popielarz, Voluntary association: A multilevel analysis of gender segregation in voluntary organizations, Gender and Society, 13 (1999), 234-250.  doi: 10.1177/089124399013002005.  Google Scholar

[50]

P. A. Popielarz and and J. M. McPherson, On the edge or in between: Niche position, niche overlap and the duration of voluntary association memberships, American Journal of Sociology, 101 (1995), 628-720.   Google Scholar

[51]

W. R. Poster, The challenges and promises of class and racial diversity in the women's movement: A study of two women's organziations, Gender and Society, 9 (1995), 659-679.  doi: 10.1177/089124395009006002.  Google Scholar

[52]

R. D. Putnam, Bowling alone: America's declining social capital, Journal of Democracy, 6 (1995), 65-78.   Google Scholar

[53]

T. J. Rowley and M. Moldoveanu, When will stakeholder groups act? An interest-and-identity-based model of stakeholder group mobilization, Academy of Management Review, 28 (2003), 204-219.  doi: 10.2307/30040709.  Google Scholar

[54]

D. H. Smith, Voluntary action and voluntary groups, Annual Review of Sociology, 1 (1975), 247-270.  doi: 10.1146/annurev.so.01.080175.001335.  Google Scholar

[55]

S. S. Smith, Mobilizing social resources: Race, ethnic, and gender differences in social capital and persisting wage inequalities, The Sociological Quarterly, 41 (2000), 509-537.   Google Scholar

[56]

T. A. B. Snijders, The degree variance: An index of graph heterogeneity, Social Networks, 3 (1981), 163-174.  doi: 10.1016/0378-8733(81)90014-9.  Google Scholar

[57]

D. A. Snow, L. A. Zurcher and S. Ekland-Olson, Social networks and social movements: A microstrucural approach to differential recruitment, American Sociological Review, 45 (1980), 787-801.  doi: 10.2307/2094895.  Google Scholar

[58]

S. Verba, K. L. Schlozman, H. Brady and N. H. Nie, Race, ethnicity and political resources: Participation in the United States, British Journal of Political Science, 23 (1993), 453-497.   Google Scholar

[59]

S. Wasserman, Social Network Analysis: Methods and Applications, Cambridge University Press, New York, 1994. doi: 10.1017/CBO9780511815478.  Google Scholar

[60]

W. J. Wilson, The Truly Disadvantaged: The Inner City, the Underclass, and Public Policy, University of Chicago Press, Chicago, 2012. Google Scholar

[61]

M. N. Zald and J. D. McCarthy, Social Movements in an Organizational Society, Transaction, New Brunswick, NJ, 1987. Google Scholar

[62]

Y. Zhu, W. Breitung and S. Li, The changing meaning of neighbourhood attachment in Chinese commodity housing estates: Evidence from Guangzhou, Urban Studies, 49 (2012), 2439-2457.  doi: 10.1177/0042098011427188.  Google Scholar

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Y. Zhu and Q. Fu, Deciphering the civic virtue of communal space: Neighborhood attachment, social capital, and neighborhood participation in urban China, Environment and Behavior, 49 (2017), 161-191.  doi: 10.1177/0013916515627308.  Google Scholar

show all references

References:
[1]

G. Almgren, M. Magarati and L. Mogford, Examining the influences of gender, race, ethnicity, and social capital on the subjective health of adolescents, J. Adolesc., 32 (2009), 109-133.  doi: 10.1016/j.adolescence.2007.11.003.  Google Scholar

[2]

A. F. Aveni, Organizational linkages and resource moblization: The significance of linkage strength and breadth, The Sociological Quarterly, 19 (1978), 185-202.  doi: 10.1111/j.1533-8525.1978.tb01164.x.  Google Scholar

[3]

D. Baldassarri and M. Diani, The integrative power of civic networks, American Journal of Sociology, 113 (2007), 735-780.  doi: 10.1086/521839.  Google Scholar

[4]

K. Beyerlein and J. R. Hipp, From pews to participation: The effect of congregation activity and context on bridging civic engagement, Social Problems, 53 (2006), 97-117.   Google Scholar

[5]

S. P. Borgatti, M. G. Everett and L. C. Freeman, Ucinet 6 for Windows: Software for Social Network Analysis, Analytic Technologies, Cambridge, MA, 2002. Google Scholar

[6]

H. E. Brady, S. Verba and K. L. Schlozman, Beyond ses: A resource model of political participation, American Political Science Review, 89 (1995), 271-294.  doi: 10.2307/2082425.  Google Scholar

[7]

R. L. Breiger, The duality of persons and groups, Social Forces, 53 (1974), 181-190.  doi: 10.2307/2576011.  Google Scholar

[8]

C. Buchmann, T. A. DiPrete and A. McDaniel, Gender inequalities in education, Annual Review Sociolology, 34 (2008), 319-337.  doi: 10.1146/annurev.soc.34.040507.134719.  Google Scholar

[9]

W. K. Carroll and R. S. Ratner, Master framing and cross-movement networking in contemporary social movements, The Sociological Quarterly, 37 (1996), 601-625.   Google Scholar

[10]

H. Coffe and B. Geys, Measuring the bridging nature of voluntary organizations: The importance of association size, Sociology, 42 (2008), 357-369.  doi: 10.1177/0038038507087359.  Google Scholar

[11] J. S. Coleman, Introduction to Mathematical Sociology, Free Press, New York, 1964.   Google Scholar
[12]

B. Cornwell and J. A. Harrison, Union members and voluntary associations: Membership overlap as a case of organizational embeddedness, American Sociological Review, 69 (2004), 862-881.   Google Scholar

[13]

M. Diani, Leaders or brokers, in Social Movements and Networks, Oxford University Press, Oxford, 2003,105–122. doi: 10.1093/0199251789.001.0001.  Google Scholar

[14]

C. S. Fischer, On urban alienations and anomie: Powerlessness and social isolation, American Sociological Review, (1973), 311–326. Google Scholar

[15]

L. C. Freeman, Centrality in social networks conceptual clarification, Social Networks, 1 (1978), 215-239.   Google Scholar

[16]

Q. Fu, X. Guo and K. C. Land, A Poisson-multinomial mixture approach to grouped and right-censored counts, Communications in Statistics-Theory and Methods, 47 (2018), 427-447.  doi: 10.1080/03610926.2017.1303736.  Google Scholar

[17]

Q. Fu, X. Guo and K. C. Land, Optimizing count responses in surveys: A machine-learning approach, Sociological Methods & Research, (2020). doi: 10.1177/0049124117747302.  Google Scholar

[18]

Q. Fu, How does the neighborhood inform activism? Civic engagement in urban transformation, Journal of Environmental Psychology, 63 (2019), 1-8.   Google Scholar

[19]

Q. Fu and K. C. Land, Does urbanisation matter? A temporal analysis of the socio-demographic gradient in the rising adulthood overweight epidemic in China, 1989–2009, Population, Space and Place, 23 (2017), 1-17.  doi: 10.1002/psp.1970.  Google Scholar

[20]

Q. Fu, K. C. Land and V. L. Lamb, Bullying victimization, socioeconomic status and behavioral characteristics of 12th graders in the United States, 1989 to 2009: Repetitive trends and persistent risk differentials, Child Indicators Research, 6 (2013), 1-21.  doi: 10.1007/s12187-012-9152-8.  Google Scholar

[21]

Q. Fu, K. C. Land and V. L. Lamb, Violent physical bullying victimization at school: Has there been a recent increase in exposure or intensity? An age-period-cohort analysis in the United States, 1991 to 2012, Child Indicators Research, 9 (2016), 485-513.  doi: 10.1007/s12187-015-9317-3.  Google Scholar

[22]

Q. Fu and N. Lin, The weaknesses of civic territorial organizations: Civic engagement and homeowners associations in urban China, International Journal of Urban and Regional Research, 38 (2014), 2309-2327.   Google Scholar

[23]

Q. Fu and Q. Ren, Educational inequality under China's rural-urban divide: The Hukou system and return to education, Environment and Planning A, 42 (2010), 592-610.  doi: 10.1068/a42101.  Google Scholar

[24]

Q. Fu, C. Wu, H. Liu, Z. Shi and J. Gu, Live like mosquitoes: Hukou, rural-urban disparity, and depression, Chinese Journal of Sociology, 4 (2018), 56-78.  doi: 10.1177/2057150X17748313.  Google Scholar

[25]

A. Fung, Associations and democracy: Between theories, hopes, and realities, Annual Review of Sociology, 29 (2003), 515-539.  doi: 10.1146/annurev.soc.29.010202.100134.  Google Scholar

[26]

W. A. Gamson, The Strategy of Social Protest, The Dorsey Press, Homewood, IL, 1975. Google Scholar

[27]

J. Ginn and S. Arber, Gender, class and income inequalities in later life, British Journal of Sociology, 42 (1991), 369-396.  doi: 10.2307/591186.  Google Scholar

[28]

R. M. Groves, F. Fowler Jr., M. Couper, J. Lepkowski, E. Sniger and R. Tourangeau, Survey Methodology, Wiley & Sons, New York, 2004.  Google Scholar

[29]

R. Gulati and M. Gargiulo, Where do interorganizational networks come from?, American Journal of Sociology, 104 (1999), 1439-1493.  doi: 10.1086/210179.  Google Scholar

[30]

R. Gulati and M. Sytch, Dependence asymmetry and joint dependence in interorganziational relationships, Administrative Science Quarterly, 52 (2007), 32-69.   Google Scholar

[31]

R. A. Hanneman and M. Riddle, Introduction to Social Network Methods, University of California, Riverside, CA, 2005. Google Scholar

[32]

M. Hunter, "If you're light you're alright" light skin color as social capital for women of color, Gender & Society, 16 (2002), 175-193.  doi: 10.1177/08912430222104895.  Google Scholar

[33]

J. C. Jenkins, Resource mobilization theory and the study of social movements, Annual Review of Sociology, 9 (1983), 527-553.   Google Scholar

[34]

F. L. Jones, Sources of gender inequality in income: What the Australian Census says, Social Forces, 62 (1983), 134-152.  doi: 10.2307/2578352.  Google Scholar

[35]

D. Knoke, Associations and interest groups, Annual Review of Sociology, 12 (1986), 1-21.   Google Scholar

[36]

K. C. Land, V. L. Lamb, S. Meadows, H. Zheng and Q. Fu, The CWI and its components: Empirical studies and findings, in The Well-Being of America's Children, Springer, New York, 2012, 29–75. doi: 10.1007/978-94-007-4092-1_3.  Google Scholar

[37]

K. L. Land, P. L. McCall and D. S. Nagin, A comparison of Poisson, negative binomial, and semiparametric mixed Poisson regression models with empirical applications to criminal careers data, Sociological Methods & Research, 24 (1996), 387-442.  doi: 10.1177/0049124101029003004.  Google Scholar

[38]

J. S. Long and J. Freese, Regression Models for Categorical Dependent Variables Using Stata, Stata Press, College Station, 2006. Google Scholar

[39]

G. Marwell, P. E. Oliver and R. Prahl, Social Networks and Collective Action: A Theory of the Critical Mass. III, American Journal of Sociology, 94 (1988), 502-534.   Google Scholar

[40]

D. S. Massey and N. A. Denton, The dimensions of residential segregation, Social Forces, 67 (1988), 281-315.  doi: 10.2307/2579183.  Google Scholar

[41]

J. D. McCarthy and M. N. Zald, Resource mobilization and social movements: A partial theory, American Journal of Sociology, 82 (1977), 1212-1241.   Google Scholar

[42]

S. McDonald and J. C. Day, Race, gender, and the invisible hand of social capital, Sociology Compass, 4 (2010), 532-543.  doi: 10.1111/j.1751-9020.2010.00298.x.  Google Scholar

[43]

J. M. McPherson, Hypernetwork sampling: Duality and differentiation among voluntary organizations, Social Networks, 3 (1982), 225-249.  doi: 10.1016/S0304-422X(01)80005-X.  Google Scholar

[44]

J. M. McPherson and D. L. Smith-Lovin, Women and weak ties: Differences by sex in the size of voluntary associations, American Journal of Sociology, 87 (1982), 883-904.   Google Scholar

[45]

M. McPherson, L. Smith-Lovin and M. E. Brashears, Social isolation in America: Changes in core discussion networks over two decades, American Sociological Review, 71 (2006), 353-375.  doi: 10.1177/000312240607100301.  Google Scholar

[46]

J. Moody, Race, school integration, and friendship segregation in America, American Journal of Sociology, 107 (2001), 679-716.  doi: 10.1086/338954.  Google Scholar

[47]

J. Moody and D. R. White, Structural cohesion and embeddedness: A hierarchical concept of social groups, American Sociological Review, (2003), 103–127. doi: 10.2307/3088904.  Google Scholar

[48]

P. Paxton, Social capital and democracy: An interdependent relationship, American Sociological Review, 67 (2002), 254-277.  doi: 10.2307/3088895.  Google Scholar

[49]

P. A. Popielarz, Voluntary association: A multilevel analysis of gender segregation in voluntary organizations, Gender and Society, 13 (1999), 234-250.  doi: 10.1177/089124399013002005.  Google Scholar

[50]

P. A. Popielarz and and J. M. McPherson, On the edge or in between: Niche position, niche overlap and the duration of voluntary association memberships, American Journal of Sociology, 101 (1995), 628-720.   Google Scholar

[51]

W. R. Poster, The challenges and promises of class and racial diversity in the women's movement: A study of two women's organziations, Gender and Society, 9 (1995), 659-679.  doi: 10.1177/089124395009006002.  Google Scholar

[52]

R. D. Putnam, Bowling alone: America's declining social capital, Journal of Democracy, 6 (1995), 65-78.   Google Scholar

[53]

T. J. Rowley and M. Moldoveanu, When will stakeholder groups act? An interest-and-identity-based model of stakeholder group mobilization, Academy of Management Review, 28 (2003), 204-219.  doi: 10.2307/30040709.  Google Scholar

[54]

D. H. Smith, Voluntary action and voluntary groups, Annual Review of Sociology, 1 (1975), 247-270.  doi: 10.1146/annurev.so.01.080175.001335.  Google Scholar

[55]

S. S. Smith, Mobilizing social resources: Race, ethnic, and gender differences in social capital and persisting wage inequalities, The Sociological Quarterly, 41 (2000), 509-537.   Google Scholar

[56]

T. A. B. Snijders, The degree variance: An index of graph heterogeneity, Social Networks, 3 (1981), 163-174.  doi: 10.1016/0378-8733(81)90014-9.  Google Scholar

[57]

D. A. Snow, L. A. Zurcher and S. Ekland-Olson, Social networks and social movements: A microstrucural approach to differential recruitment, American Sociological Review, 45 (1980), 787-801.  doi: 10.2307/2094895.  Google Scholar

[58]

S. Verba, K. L. Schlozman, H. Brady and N. H. Nie, Race, ethnicity and political resources: Participation in the United States, British Journal of Political Science, 23 (1993), 453-497.   Google Scholar

[59]

S. Wasserman, Social Network Analysis: Methods and Applications, Cambridge University Press, New York, 1994. doi: 10.1017/CBO9780511815478.  Google Scholar

[60]

W. J. Wilson, The Truly Disadvantaged: The Inner City, the Underclass, and Public Policy, University of Chicago Press, Chicago, 2012. Google Scholar

[61]

M. N. Zald and J. D. McCarthy, Social Movements in an Organizational Society, Transaction, New Brunswick, NJ, 1987. Google Scholar

[62]

Y. Zhu, W. Breitung and S. Li, The changing meaning of neighbourhood attachment in Chinese commodity housing estates: Evidence from Guangzhou, Urban Studies, 49 (2012), 2439-2457.  doi: 10.1177/0042098011427188.  Google Scholar

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Figure 1.  Bonacich power centrality scores for civic networks by gender

Note: The centrality scores are normalized by the highest centrality in each network

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Figure 2.  Bonacich power centrality scores for civic networks by race

Note: The centrality scores are normalized by the highest centrality in each network

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Figure 3.  The civic network connected by overlapping memberships

Note: The node (or actor) size is proportionate to its degree centrality of each node. The tie width is proportionate to the tie strength, or the number of overlapping members between two given nodes

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Figure 4.  Multi-dimensional scaling solution of civic networks by gender
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Figure 5.  Multi-dimensional scaling solution of civic networks by race
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Table 1.  Membership percentages of nine types of organizations and degree centralization
Organization type Membership percentages
All Male Female Whites Blacks Latinos
Religious groups 38% 34% 42% 42% 40% 25%
Charities 25% 23% 27% 27% 28% 15%
School and PTA 24% 17% 31% 25% 32% 21%
Professional organizations 23% 24% 22% 26% 19% 11%
Political parties 23% 23% 22% 26% 17% 11%
Leisure and sports groups 22% 25% 19% 24% 16% 13%
Neighborhood organizations 13% 13% 13% 13% 19% 8%
Labor unions 12% 15% 9% 12% 17% 6%
Ethnic/civil rights 3% 4% 3% 2% 9% 3%
Freeman degree centrality 23.56 27.27 26.1 25.01 25.28
Network heterogeneity 1.59 2.18 2.24 0.92 1.77
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Organization type Membership percentages
All Male Female Whites Blacks Latinos
Religious groups 38% 34% 42% 42% 40% 25%
Charities 25% 23% 27% 27% 28% 15%
School and PTA 24% 17% 31% 25% 32% 21%
Professional organizations 23% 24% 22% 26% 19% 11%
Political parties 23% 23% 22% 26% 17% 11%
Leisure and sports groups 22% 25% 19% 24% 16% 13%
Neighborhood organizations 13% 13% 13% 13% 19% 8%
Labor unions 12% 15% 9% 12% 17% 6%
Ethnic/civil rights 3% 4% 3% 2% 9% 3%
Freeman degree centrality 23.56 27.27 26.1 25.01 25.28
Network heterogeneity 1.59 2.18 2.24 0.92 1.77
Table 2.  Results from multinomial logistic regression, Poisson regression and negative-binomial regression on voluntary-organization memberships (N = 2, 456)
Poisson regression Negative-binomial regression Multinomial regression
Zero-inflation Zero-inflation Domes. & Non. Domes. & work Non. & work
Coeff. Coeff. Coeff. Coeff. Coeff. Coeff. Coeff.
Whites (ref: Latinos) 0.176** 0.076 0.179** 0.078 0.454** 0.902** 0.151
Blacks (ref: Latinos) 0.329*** 0.205* 0.337*** 0.208* 0.26 1.355*** -0.097
Female (ref: male) 0.069* 0.04 0.069* 0.039 -0.067 0.242 -0.266
Married 0.149*** 0.081* 0.152*** 0.083* 0.277** 0.301 0.117
Age 0.006*** 0.006** 0.006*** 0.006** 0.008 0.015* 0.007
Education c 0.223*** 0.152*** 0.224*** 0.153*** 0.479*** 0.647*** 0.747***
Religious affiliation 0.274*** 0.214*** 0.269*** 0.217*** 0.396** 0.366 -0.603*
Perceived social class 0.141*** 0.164*** 0.142*** 0.166*** 0.431*** 0.335*** 0.244
Annual income 0.007** 0.003 0.007** 0.003 0.017* 0.024* 0.045*
Constant -2.094*** -1.314*** -2.110*** -1.345*** -6.286*** -9.322*** -9.034***
Chi square 492.26*** 245.73*** 467.43*** 237.72*** 357.07***
Pseudo R2 0.072 0.052 0.089
Alpha 0.144 0.017
Vuong test 5.84*** 4.70***
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Poisson regression Negative-binomial regression Multinomial regression
Zero-inflation Zero-inflation Domes. & Non. Domes. & work Non. & work
Coeff. Coeff. Coeff. Coeff. Coeff. Coeff. Coeff.
Whites (ref: Latinos) 0.176** 0.076 0.179** 0.078 0.454** 0.902** 0.151
Blacks (ref: Latinos) 0.329*** 0.205* 0.337*** 0.208* 0.26 1.355*** -0.097
Female (ref: male) 0.069* 0.04 0.069* 0.039 -0.067 0.242 -0.266
Married 0.149*** 0.081* 0.152*** 0.083* 0.277** 0.301 0.117
Age 0.006*** 0.006** 0.006*** 0.006** 0.008 0.015* 0.007
Education c 0.223*** 0.152*** 0.224*** 0.153*** 0.479*** 0.647*** 0.747***
Religious affiliation 0.274*** 0.214*** 0.269*** 0.217*** 0.396** 0.366 -0.603*
Perceived social class 0.141*** 0.164*** 0.142*** 0.166*** 0.431*** 0.335*** 0.244
Annual income 0.007** 0.003 0.007** 0.003 0.017* 0.024* 0.045*
Constant -2.094*** -1.314*** -2.110*** -1.345*** -6.286*** -9.322*** -9.034***
Chi square 492.26*** 245.73*** 467.43*** 237.72*** 357.07***
Pseudo R2 0.072 0.052 0.089
Alpha 0.144 0.017
Vuong test 5.84*** 4.70***
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