Publication - Research and analysis

Exploring Dimensions of Social Capital in Scotland Findings from the Scottish Social Attitudes Survey and Scottish Household Survey

Published: 29 Oct 2012
ISBN:
9781782560951

The report explores whether different groups in society experience different levels of social capital. It draws on data from the Scottish Social Attitudes survey (SSA) 2009 and the Scottish Household Survey 2010.

Exploring Dimensions of Social Capital in Scotland Findings from the Scottish Social Attitudes Survey and Scottish Household Survey
Footnotes

Footnotes

1. The report uses SSA 2009 rather than later years because the 2009 survey included a wider range of measures of social capital.

2. For evidence of the benefits of social capital on health and wellbeing see: Mackinnon J, Reid, M. & Kearns, A. (2006). Communities and health improvement: A review of evidence and approaches http://www.healthscotland.com/uploads/documents/2876-Communities%20and%20Health%20Improvement.pdf

3. See for example ONS (2001) and OECD (2001).

4. Note that trust may be both an indicator of social capital and an outcome of it - those who are more connected to their community may become more trusting as a result.

5. As discussed in Li, Y., Pickles, A. & Savage, M. (2005).

6. Decisions about which questions to include in were based on discussions with the Scottish Government and on pragmatic considerations about data availability and the extent to which questions had already been analysed and reported elsewhere. For example, variations on various additional questions about perceptions of the local area in SSA 2009 had already been analysed in a report on attitudes to sustainable places and greenspace (Reid and Curtice, 2010).

7. Respondents were divided into four age categories - 18-29, 30-39, 40-64 and 65+. It is perhaps worth noting that different sub-groups may have been associated with somewhat different findings. For example, it is possible that there may be differences between relatively younger and older people within the oldest age category (65+).

8. SSA uses the National Statistics Socio-Economic Classification (NS-SEC). SSA respondents were classified according to their own occupation, rather than that of the 'head of household'. Each respondent was asked about their current or last job, so that all respondents, with the exception of those who had never worked, were classified. The seven NS-SEC categories are: Employers in large organisations, higher managerial and professional; Lower professional and managerial; Higher technical and supervisory; Intermediate occupations; Small employers and own account workers; Lower supervisory and technical occupations; Semi-routine occupations; Routine occupations. The remaining respondents were grouped as 'never had a job' or 'not classifiable'.

9. See http://www.scotland.gov.uk2c84fccd-f86c-46b4-b48b-576009c022a8 for details of the Scottish Government urban-rural classification.

10. The Scottish Index of Multiple Deprivation (SIMD) 2009 measures the level of deprivation across Scotland - from the least deprived to the most deprived areas, based on 38 indicators in seven domains of: income, employment, health, education skills and training, housing, geographic access and crime. For more details about SIMD, see http://www.scotland.gov.uk/Topics/Statistics/SIMD/.

11. Specifically, neighbouring (as measured by an 8 item version of Buckner's Neighbourhood Cohesion Instrument, which covers things like feeling of belonging to a neighbourhood, willingness to seek advice from someone in the neighbourhood, and willingness to work together to improve the neighbourhood), general trust (based on two questions, one about the extent to which most people can be trusted or not and another about willingness to take risks with strangers) and interest in politics (as measured on a 4 point scale from 'Very interested' to 'Not at all interested).

12. Galloway, S., Bell, D., Hamilton, C. and Scullion, A (2006) Quality of Life and Wellbeing: Measuring the Benefits of Culture and Sport: A Literature Review and Thinkpiece, Scottish Executive Social Research.

13. It is also worth noting that some of the independent variables included in the regressions differed slightly for SHS and SSA, reflecting differences in the way the data for that variable was collected or processed. However, variables in each dataset were recoded for analysis so that categories were as consistent as possible across analyses.

14. As a general rule, if something is marginally significant (p = >0.05 but >=0.10) in a multivariate regression model, but the bivariate relationship with the dependent variable is highly significant (p >=0.05), the bivariate relationship is reported in the text and tables, with the qualification that this relationship does not hold once other factors are taken into account. If a variable is only marginally significant in both multivariate and bivariate analyses, differences are not generally reported in the text and tables.

15. Differences by gender are only only marginally significant in the regression model (p = 0.093). However, differences in the proportion of men and women strongly agreeing that they regularly stop and speak to people in their area are significant at the bivariate level (p = 0.049). In contrast, having school-aged children in the household was marginally significant in the regression analysis but differences were not significant at the bivariate level (regardless of whether agree and strongly agree were banded together or not). Given that it was only marginally significant in the regression model and not significant at all at the bivariate level, whether or not there were school-aged children in the household is not included in Table 2, above.

16. Education was significant in the regression analysis. However, none of the individual categories were significantly different from the reference category (no qualifications). This probably reflects the fact that the pattern of response by education was not linear - rather, graduates simply stand out from other groups on this measure.

17. Note that combined figures (for example, 'agree' plus 'strongly agree') are combined in SPSS, to avoid rounding errors. As such, they may vary by a percentage point from the sum of the (rounded) individual figures.

18. P = 0.089. Note that gender is also marginally significant in both the regression analysis and marginally significant at the bivariate level.

19. For evidence of the link between trust and volunteering, see Brown and Ferris (2004).

20. This pattern is apparent at the bivariate level. However, multivariate analysis only shows that those aged 30 and over a more likely than those aged 18-29 to disagree that it is too difficult for them to do much about improving their area.

21. Whether people live in a rural or urban setting was also significantly associated with wanting to be more involved in council decision making in the multivariate analysis (those living in other urban areas, accessible small towns and accessible rural areas were all less likely than those in large urban areas to want to be more involved). However, there was no clear pattern at the bivariate level.

22. Area deprivation was also marginally significantly associated with agreeing 'I would like to be more involved in the decisions my council makes that affect my local area' in the regression analysis (Annex A, Model 9, p = 0.080). However, variations at the bivariate level did not follow a clear pattern, so deprivation is not included in Table 10, above.

23. Income was only marginally significantly related to having something active to register ones views in the regression analysis. However, it was not significant at the bivariate level, so is not reported here.

24. The 5 dimensions of social capital as defined by ONS are: social networks and support; social trust; civic participation; social participation and views of local area.


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Email: Linzie Liddell