Data from: Religious visibility, disadvantage and bridging social capital: a comparative investigation of multicultural localities in Melbourne’s north

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This project explored neighbourhood experiences of residents in two ethno-religiously diverse suburbs in Melbourne’s north, Fawkner and Broadmeadows. The two localities were chosen because they both have large Muslim minorities (25 and 30 per cent respectively at the time of the 2011 Census, and 32 and 36 at the time of the 2016 census) and the project’s primary focus was on the impact of (primarily Muslim) ‘religious visibility’ on the local bridging social capital. Bridging social capital is an important aspect of social capital, especially in large, diverse and socially anonymous urban contexts. It refers to interactions and connections among people with different demographic, ethno-cultural and socio-economic characteristics. Bridging social capital is crucial for (but not limited to) local community cohesion, which translates into friendliness, neighbourliness and safety of (sub)urban communities. Literature on social cohesion and social capital in the context of ethnically diverse Western cities is extensive and its findings are varied, depending on the specific characteristics of the local context under investigation, as well as wider national and international contexts at any given time. Some studies found that urban ethnic diversity tends to decrease social capital and social cohesion, while other studies came up with different conclusions. One of the reasons for the inconclusive findings is not just real differences between localities but also methodological difficulty of precisely measuring social capital and social cohesion. Our study was informed by theoretical and methodological insights of Australian and overseas studies, as well as our own earlier research on diverse neighbourhoods and the impact of ‘visible difference’ in Australian urban contexts. The project also built on our recent (2012-13) empirical research in Melbourne’s diverse north. The project employed mixed methodology of data collection and analysis. We started with the background analysis of the Census and other available quantitative information about the two localities. The empirical data collection for the project developed in three stages: • key informant interviews (May-June 2016) • the survey of residents (September-November 2016) • follow-up interviews with residents (December 2016-March 2017). The key informant interviews (the total of 16) were conducted by principal investigators and targeted professionals and services providers working in Fawkner and Broadmeadows. These interviews helped identify key issues and sharpened our research focus. They also informed the development of the key research instrument, the survey questionnaire. The total of 301 residents participated in the survey. Once the questionnaire was drafted and piloted, seven community-based bilingual research assistants (BRAs) were engaged to administer the survey face-to-face to a sample of residents of the two suburbs. The sample was balanced by suburb, gender and religion (Muslim / non-Muslim). The sample was appropriately diverse in terms of participants’ ethnicity, length of residence in their suburb and socio-economic background. The sample is not representative for the population of the two suburbs, because Muslims were overrepresented in our sample. The follow-up in-depth interviews (the total of 36) were conducted with residents of the two suburbs who previously took part in the survey and expressed interest to be interviewed later on. The sample included people from a variety of ages, ethnic backgrounds, religions and walks of life. The large data set consisted of quantitative and qualitative data. Quantitative data were checked for quality, entered into the Statistical Package for Social Sciences (SPSS) and cleaned. We used descriptive and inferential statistical methods to analyse the data. The narrative interview data were professionally transcribed and thematically analysed. The quantitative and qualitative analyses are complementary and combining them is the best way to contribute to an in-depth understanding of the phenomena under investigation.