At the core of the analysis is data from the Scottish Household Survey (SHS). The SHS provides a large representative sample of the population in Scotland through repeat cross-sectional surveys which have been carried out for the last 20 years.
This study uses data from four waves of the SHS over seven years, consisting of cross-sectional samples conducted in 1999-2000, 2001-2002, 2009-2010, and 2011. The datasets were chosen to coincide with the early and late periods of the New Labour government, coming to power in 1997 and finishing in 2010. As the first two waves of the SHS were conducted between 1999 and 2002, it is expected that possible changes attributed to the change of government would not be reflected in perceptions of local services particularly under the devolved Scottish Government. Therefore the early data is considered appropriate to represent the situation prior to the influence of the public service reform and neighbourhood initiatives of New Labour. In turn, possible effects can be assumed to have occurred over the ten-year period, being reflected in the three years of data for 2009-2011. It would have been preferable to use the full range of survey years but resource constraints within Scottish Government,
the data owner, meant they were unable to supply a greater number of years with the geographic identifiers which permit the linkage of neighbourhood contextual variables on social mix and social capital.
Two study waves at each end of the time period in question are combined to obtain larger sample sizes and to include more questions on service outcomes in the first period, as reflected in Tables 4.1, 4.2, and 4.3. Tables 4.1-4.3 summarise the variables included in each survey wave. Ideally, the study would have hoped to obtain more years of data but the resource constraints from the data provider meant that this was not possible.
Local services are a core part of the survey, which is designed to cover a wide range of topics overall on the characteristics of households and the views of individuals on issues such as neighbourhood conditions, education, and local government with the aim of informing policy in a number of different areas (e.g., Martin & Hope, 2001).
The SHS is designed to provide an effective sample size from larger local authorities each year and all local authorities over two-year periods. The sampling of households consists of a complex survey design which uses both unclustered and clustered random sampling. Surveys conducted 1999-2002 used a slightly different sampling method compared to the surveys 2009-2011. In 1999-2002, for areas of high population density the survey stratified postcode sectors using a geo-demographic indicator (Scottish MOSAIC) in and took a random sample within each selected sector. For local authorities with lower population densities, the surveys up to 2002 clustered sampling through the smaller Enumeration Districts (EDs), with random sampling within each (Martin & Hope, 2001; Hope, 2002). In 2009-2011, the sample was stratified by local authority using the Government’s urban-rural classification. Unclustered sampling was used in authorities classified as ‘large urban areas’ or ‘other urban areas’ while in other authorities sampling was again clustered (Hope & Nava-Ledezma, 2010; 2011). The surveys achieved response rates between 66% and 69% at each wave (Hope & Nava-Ledezma, 2010).
The individual survey data is weighted to adjust the achieved sample to known age/sex distributions of the populations of local authorities (Martin & Hope, 2001; Hope, 2002; Hope & Nava-Ledezma, 2010; 2011). The analyses in Chapters 6-8 take into account the weighting of individual data and the complex survey design. In addition to weighting, Chapters 7 and 8 account for the nesting of individuals within geographical areas by conducting multilevel modelling.
The interview structure of the SHS consists of two parts in order to provide representative samples of households and of the adult population within them. The variables concerning household composition, income, and housing come from the survey interview with the householder or their partner. After this one adult from the household, which can be the same person as the householder, is chosen at random to complete the second part. This includes the modules on views about local services, as well as topics such as housing change and neighbourhood problems. Therefore the analysis in this study is based on individuals while it also uses some information on the characteristics of their household (Martin & Hope, 2001; Hope, 2002; Hope & Nava-Ledezma, 2010; 2011).
Local service outcomes
This study focuses on examining differences in the perceptions of local services, which are a core aspect of the SHS and thereby represented by extensive question modules in the data. The SHS provides three kinds of outcome measure comprised of subjective questions on: Frequency of Use of Services, Convenience of Services, and Satisfaction with Services. Convenience and Satisfaction can be considered to represent the perceptions of access to and quality of services, which are important aspects in light of the concerns with equalisation standards and needs-based provision of services discussed in the literature review (section 3.1 above). Frequency of Use allows the study to distinguish whether individuals differ in their patterns of use of services. The frequency of use of services further reflects need and is assumed to be connected to perceptions of access and quality, as for example easier access is likely to encourage the use of some services, making the item useful to compare with perceptual outcomes.
As this study aims to measure variations in the perceptions of local services with regard to social mix, it will examine patterns across groups of services provided at the neighbourhood level. The survey includes a range of items concerning leisure services and amenities, essential services such as post offices and food shops, and public services, such as street cleaning. While the questionnaires do not specify these as local, the services in question are generally distributed at a small area level, and it can be assumed that most respondents tend to access them within their local area.
Different services are covered in relation to each outcome and the specific services change over time, as shown in Tables 4.2 to 4.4. To reduce the complexity, similar services are combined to form eight summary indices (Table 4.1). These are the main outcome measures used in the regression analyses (Chapters 6-8). Due to the changes in survey content, only six of these indices can be constructed on a consistent basis for both time periods. Two indices cover Frequency of Use of Leisure services, such as sports facilities and libraries, using the four services available at both periods. Another index covers Frequency of Use of Necessities services, consisting of a group of eight private and public services required by most people, but only available for the later period. Indices of Convenience of Services are constructed for both periods using the seven services available consistently. Indices of Satisfaction with four Leisure services are constructed for both periods, using the same consistent subset as for Frequency. Finally, Satisfaction with Public services is measured for the later period only (Table 4.1). As discussed in Chapter 6, we use statistical tests to check that it is appropriate to combine each group of services into these indices i.e. that there are similar patterns of responses for each service in the group. Chapter 6 also explains how the items are grouped together and how they have been transformed for analysis.
Table 4.1 Key outcome indicators and service items included in the SHS 1999-2002, 2009 2011.
In addition to analyses using the combined indices, Chapter 7 produces separate models for the individual service items. Tables 4.2, 4.3 and 4.4 show the survey questions and service items available at each wave for each of the three types of outcome. While there is some inconsistency in the services included in each outcome category (i.e., Frequency, Convenience, and Satisfaction are comprised of a slightly different groups of services), this is not considered problematic as the study does not focus on comparing specific services across different outcomes. The analysis focuses on modelling the perceptual outcomes through indicators for groups of services. When analysing change over time, however, the study always uses consistent groups of services at both time points.
Outcome indicators Services included N items 1999- 2002 2009- 2011 Frequency of Use of Leisure Services
Libraries, parks, museums, sports
4
Frequency of Use of Necessities
Post offices, banks, cash machines, doctors, dentists, grocery/food shops, chemists, outpatients, petrol stations, public transport
8
Convenience of Essential Services
Post offices, banks, outpatients, small food shops, doctors, chemists, public transport
7
Satisfaction with Leisure Services
Libraries, parks, museums, sports 4
Satisfaction with Public Services
Health, police, fire, refuse collection, schools, social care, public transport, street cleaning
102 Table 4.2 Service questionnaire items for Frequency of Use by wave.SHS 1999-2002, 2009-2011.
Question Frequency of Use 1999-
2000
2001- 2002
2009-
2010 2011
When did you last use or visit each of the following?
Public library
Public parks and open spaces Museums and art galleries
Swimming pools
Sports/leisure centres How often you have you used each of the
following council services in the past 12 months?
Public library
Public parks and open spaces
Museums and art galleries
Theatres or concert halls
Community centres and facilities
Sports/leisure centres How often you have you used each of the
following council services in the past 12 months?
Post office
Banking services
Cash machine or ATM
Doctor's surgery
Dentist
Small amount of grocery or food shopping
Chemist/pharmacist
Hospital outpatients department
Petrol station
103 Table 4.3 Service questionnaire items for Convenience by wave. SHS 1999-2002, 2009-2011.
Question Convenience 1999- 2000 2001- 2002 2009- 2010 2011
Bearing in mind where they are and your own circumstances, please tell me how convenient or inconvenient you would find it to use these services during their normal opening hours, assuming you needed to?
Post office
Bank
Doctor's surgery
Small amount of grocery or food shopping Chemist/pharmacist
Hospital outpatients department
Public transport
Dentist
Cash machine or ATM Petrol station
104 Table 4.4 Service questionnaire items for Satisfaction by wave.SHS 1999-2002, 2009-2011.
Question Satisfaction 1999- 2000 2001- 2002 2009- 2010 2011
I would like you to tell me how satisfied or dissatisfied you are with the quality of each of the following?
Public library
Public parks and open spaces
Museums and art galleries
Swimming pools
Sports/leisure centres
Overall, how satisfied or dissatisfied are you with each of these council services?
Libraries
Parks and open spaces
Museums and galleries Theatres or concert halls Sports/leisure centres
Community centres and facilities
Overall, how satisfied or dissatisfied are you with each of these services?
Local health services
Police service
Fire service
Local schools
Social care or social work services
Public transport
Neighbourhood social capital
The SHS data is further utilised to gather information about respondents’ perceptions of neighbourhood social capital to address the third objective of this study: whether neighbourhood social capital contributes to variations in the perceptions of local services (Research Question 3). This stems from the theoretical assumptions around neighbourhood social capital, which is thought to help local residents to organise collectively in order to influence service provision (Sampson et al., 1997; DeFilippis, 2001). The research question is addressed in Chapter 8 which builds on the initial analysis of local services by adding variables on social capital from two sources, in turn.
The first measures of social capital come from the same samples of the SHS as the local service outcomes. (The second measures come from a different survey as explained in 4.2.3 below.) A few different questionnaire items on the topic of social capital can be found in the SHS (Table 4.5). For the purposes of comparing results over time, there are three questions which ask about informal support from social contacts with neighbours in the form of help or advice. These are combined into a single indicator as explained in detail in Chapter 8.
Additionally, we wish to measure willingness to improve the local area and influence decisions made about the area, which are part of the concept of ‘collective efficacy’. A consistent variable in the survey waves in question for this purpose enquires whether respondents have contacted the council regarding various services, which are combined into one indicator (Table 4.5).
Table 4.5 Social capital variables in the SHS by wave, SHS 1999-2002, 2009-2011.
Question 1999-2002 2009-2011
Could rely on friends/relatives in neighbourhood if needed help?
Could rely on friends/relatives in neighbourhood to watch if home empty?
Could turn to friends/relatives in neighbourhood for advice/support?
Contacted council about: refuse/bin collection; council tax; environmental planning; building control; street lighting; street cleaning/dog fouling; road repairs/potholes; pavements; winter maintenance; Trading Standards Using the council website for: finding information; downloading a form; making a complaint; asking a question; participating in a discussion forum;
access services like reporting a fault or renewing library books; making payment like council tax or parking fine; some other purpose.
Neighbourhood context
Lastly, the SHS data comes with one variable which describe the neighbourhood context already attached to the individual records. This is the measure of neighbourhood deprivation from the Scottish Index of Multiple Deprivation. That index is constructed for data zones, the same units used for the Census analysis. The SIMD ranks areas at the data zone level, and this ranking can be aggregated into deciles and quintiles. In the models, quintiles are used in order to avoid including too many parameters into the models. The 1999-2002 SHS data come with the SIMD quintiles from the 2004 update, and the 2009-2011 data are linked to quintiles from the 2009 SIMD. For intermediate zone models, we use the weighted average data zone scores for individuals in that area.