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Collective Efficacy, Neighborhood and Geographical Units of Analysis: Findings from a Case Study of Swedish Residential Neighborhoods

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The concept of collective efficacy, defined as the combination of mutual trust and willingness to act for the common good, has received widespread attention in the field of criminology. Collective efficacy is linked to, among other outcomes, violent crime, disorder, and fear of crime. The concept has been applied to geographical units ranging from below one hundred up to several thousand residents on average. In this paper key informant- and focus group interview transcripts from four Swedish neighborhoods are examined to explore whether different sizes of geographical units of analysis are equally important for collective efficacy. The four studied neighborhoods are divided into micro-neighborhoods (N=12) and micro-places (N=59) for analysis. The results show that neighborhoods appear to be too large to capture the social mechanism of collective efficacy which rather takes place at smaller units of geography. The findings are compared to survey responses on collective efficacy (N=597) which yield an indication in the same direction through comparison of ICC-values and AIC model fit employing unconditional two-level models in HLM 6.

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  1. Note however that Sampson & Raudenbusch (1999; see also Sampson 2012) elsewhere use census tracts to study disorder due to acknowledgement of a need for “smallest level of aggregation possible in measuring observed disorder, owing to considerable variability block-to-block within larger ecological units” (ibid: 619).

  2. Note that Weisburd et al. (2012) measure collective efficacy through voting participation, which could be argued to tap into other dimensions of social capital than collective efficacy.

  3. In the city of Malmö city areas averaged about 2000 residents in the year 2008, or close to 3000 residents if only city areas with at least 500 residents are counted (Malmö stad 2009).

  4. Bellevuegården in addition to the multi-family housing area has an area with 102 small houses and two large retirement homes with a total of 419 apartments that were excluded due to the focus on multi-family housing. Kroksbäck in addition has a large small house area with 625 small houses that was excluded. Note that the data in Table 2 covers the whole neighborhoods, including single family housing and retirement homes which are excluded in the study. There is no census data available for just the studied parts of Kroksbäck and Bellevuegården. In this paper when referring to neighborhoods Belleuegården and Kroksbäck it will unless otherwise stated mean the multi-family, non-retirement home areas of the neighborhoods.

  5. Note however that the street blocks in St Jean (2007) had a considerably smaller average population, 57, than the micro-neighborhoods in this study. In Hipp (2010) a micro-neighborhood normally consists of 11 households.

  6. In one case a yard is made up of the space outside the entrances to one building only.

  7. Additional buildings may exist on some yards that did not fit the criteria of multi-family non-retirement home housing.

  8. Two from tenant-ownership associations, three from tenant associations, one from self-management, one from a youth center

  9. One from a pensioners organization and one from a women’s organization

  10. The 11 remaining consist of two representatives of tenant associations organized at roughly half a micro-neighborhood in size, two representatives of self management at a yard, one representative of a youth center, three representatives of pensioneers organizations with neighborhood or city part wide activities, one from a womens organization with city part wide activities and the two representatives of the municipality. The focus on instrumental organizations was in part deliberate in relation to research pointing toward such organizations being of higher importance (Swaroop & Morenoff 2006), but in part it was due to a lack of willingness among contacted representatives of expressive organizations, in the form of ethnic-cultural organizations, to participate in the research.

  11. In some cases respondents use the word “area” (“område”) which can be interpreted as neighborhood, property manager area or micro-neighborhood. When it is clear from the context in the interview which type of geographical unit is meant it has been coded, but in most cases these references have been left out. Examples of when it is clear what type of geographical unit is meant is when cohesion is discussed in relation to a tenant association, in which case the area of operations for the tenant association is the geographical unit.

  12. Surveys that were collected by mail in many cases (n = 48) lacked a specific address with respondents rather opting to state their micro-neighborhood or neighborhood. Effective response rate where address was obtained is 51.1 %, for analysis on the micro-neighborhood level where an additional 41 responses were obtained the effective response rate was 54.3 % and on the neighborhood level an additional two respondents result in effective responserate of 54.5 %.

  13. For a brief discussion see Sampson (2012: 163)

  14. A total of 600 values for collective efficacy was registered, but incomplete spatial data resulted in a total of 561 surveys including valid values for both collective efficacy and micro-place, 596 for the micro-neighborhood and 597 for the neighborhood. The neighborhood level values are reported in Appendix Table 7.

  15. Although Hox (2002) discusses techniques for dealing with ICC-values in relation to a very small dataset with just five level 2 units, Maas & Hox (2005) show that level 2 variance components need more level 2 units to become stable.

  16. “IP4: Then we thought of something, IP1 and I which we think is fun to strengthen the neighborhood and maybe some cohesion and a bit of integration. It’s this about a singing choir, but we haven’t gotten there yet, but it is supposed to be like that.” (Focus group 110209)

  17. “M: What’s the best about living in Kroksbäck? IP: It is close.. There are a lot.. I dont feel like a stranger there, I feel like I live in Iraq. Many people that say hello to me, that know me, that know my family.” (Key informant 110209)

  18. Examples: “IP3: Yes, I have been thinking a bit over that question. I think, we try, there are a few of us. The tenant association does quite a lot, one of many. We try, but we are just too few. There is a lack of will and interest.” (Focus group 110126)

    “M: Do you think there is a sense of cohesion or belonging in the area? IP: Yes, we have that. We do. Unfortunately it is, I have to admit, a bit of a difficulty in reaching the young, those who are active in your age and work. It is difficult.” (Key informant 110928)

  19. Although no sensus data or similar is available for micro-neighborhoods estimations based on map data in a 200*200 m grid of income levels was used to get an approximation of SES in the micro-neigborhoods. The highest percentage of low income households was recorded in the public housing areas with most grids in the 40–60 % low income bracket (data not shown).

  20. Inclusion of a fixed lvl 2 effect of public housing reduces the ICC for the micro-neighborhood as level 2 to 1.8 %, most of the micro-neighborhood variance is thus explained by housing type which includes large variations in SES.

  21. Fixed-effect variance in non-hierarchical models with dummy-variables for each geographical unit of analysis yield r square of .162 for micro-places, .090 for micro-neighborhoods and .026 for neighborhoods separately.

  22. Survey respondents from the three yards on the northern half of the micro-neighborhood (n = 26) are registered for an average collective efficacy that is more than a micro-neighborhood standard deviation lower than the three yards in the southern half of the micro-neighborhood (n = 18 respondents).

  23. What Weisburd and colleagues (2009b: 20) call averaging: “[…] in measuring higher order geographic units miss local area effects”


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This paper is part of the project “Fire, vandalism, neighborhood, and social capital”, funded by Länsförsäkringars forskningsfond and led by professor Per-Olof Hallin of the Urban studies department at Malmö university. The author would like to thank professor Lieven Pauwels of Ghent University for invaluable comments and advice.

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Correspondence to Manne Gerell.

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Parts of these results have previously been submitted in a report (in Swedish) to Länsförsäkringars forskningsfond and printed in the Malmö University Publications In Urban Studies series (MAPIUS) no. 11 (Gerell 2013). Some results have been published in the NSFK (Scandinavian Research Council for Criminology) seminar report 2012 (Gerell 2012).



Appendix 1

Table 7 Trust and informal social control (two items each), collective efficacy mean of trust and informal social control. Low numbers imply high levels of trust, control or collective efficacy. Table includes all responses with valid values for both collective efficacy and neighborhood

Appendix 2

Table 8 Descriptive survey data and comparison with census data (2011) for three of the variables. Note that census data includes single family housing areas for two of the neighborhoods in addition to a retirement home in one of the neighborhoods. Chi square significance test of difference between observed and expected values reported with *** = p <0.001, other values p > 0.05

Appendix 3

Table 9 Interview question examples pertaining to main themes of the paper

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Gerell, M. Collective Efficacy, Neighborhood and Geographical Units of Analysis: Findings from a Case Study of Swedish Residential Neighborhoods. Eur J Crim Policy Res 21, 385–406 (2015).

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