Data Analysis and Interpretation

The distinction between analysis and interpretation lies in the purpose and processes, whereas analysis establishes cause, interpretation elucidates meaning. At the end of the data collection phase, the researcher had to carry out two main exercises to analyse the available information both qualitatively and quantitatively. Walliman (2009:112) talks about the purpose of research being “to describe data and thereby discover relationships among events in order to describe or explain their occurrence”.

It must be indicated up front that the bulk of this study was qualitative because of the nature of the study but a certain amount of quantitative data and results were also used and produced to enhance the study.

73

After collecting all the information (raw data) the researcher went through a process of ensuring that this data was complete and devoid of inconsistencies and, if inconsistencies were present, ensured that they were at a minimum. The researcher checked all responses especially in the research instrument for gaps and inconsistencies and these were cleared up especially with key respondents where they were contacted telephonically or by e-mail. This process, known as data cleaning, has to precede data processing (Kumar, 2005:220). In cases of the communities, some questions especially on service delivery were asked from different angles in both research questions two and three in the research instrument which assisted in ensuring that there was consistency in the answers given in this part.

 Qualitative Data

Normally the analysis of qualitative data follows four steps: identifying the themes, assigning codes to these themes, classifying the responses under new themes and finally integrating the themes and responses (Kumar, 2005:240-241). According to de Vos (2006:338), this can be done by abbreviating the key words, colouring, using dots, or even numbering. Meaning was then given to this area by integrating the themes with the responses to reflect on the results to the key questions in this study.

There are many ways of identifying themes and these can be through word repetition, i.e., words which keep recurring in a conversation. They could also be key words, referred to by many researchers in the social sciences as “Key Words in Context”

(KWIC). Here one looks at the way a word is used to understand a context (www.anlytictech.com).

The main themes in this study were developed using the former method mentioned earlier, namely word repetitions from analysing the meaning of the answers and categorising. This process was mainly used to analyse the texts especially in the qualitative areas of the research instrument as well as during the focus group sessions.

In this case the main themes were on delivery, especially of the basic services to the community namely, water, electricity, housing, toilets and waste disposal, especially in respect to the communities, the beneficiaries on the ground.

74

Although some key respondents also mentioned similar themes as the beneficiaries, the emphasis in this group focused on rather more important aspects from their view such as governance, corruption, capacity building, challenges at the politico-administrative levels, capacity to deliver on the local government mandate and institutional development. The coding was done by attaching a number to the relevant theme. The responses were then classified under the themes and discussed. As described in Chapter 4, the researcher opted to integrate the answer to each research question by using these themes and also in some cases by using some verbatim responses from some of the participants in the study.

 Quantitative Data

The quantitative analysis in this study involved mainly looking at the frequencies, cross-tabulations and distributions. In frequency, it was mainly ascertaining how often a certain attribute occurs. For example, the statement in research question 1 “we have Aid projects in our Municipality” was used to ascertain how many people in each category in this research were aware of the presence of aid projects in their municipality. During the processing of the limited qualitative data, cross-tabulation was employed to identify, describe and analyse some important variables in this study. In agreement with Kumar (2005:240), cross-tabulation was used in this study with caution to avoid a barrage of results which could emanate from such data presentations, and which could easily complicate the interpretation and presentation of the results.

The field data from the returned questionnaires was entered into a statistical, analytical software programme as a tool to search and generate relationship criteria as set by the researcher in order to detect trends and behaviour patterns in relation to responses to the research questions (quantitative analysis). The statistical package used was SPSS (Statistical Package for the Social Sciences), thereafter frequencies and cross-tabulations were carried out between groups and various responses to questions. In agreement with Robson (2002:393-98) this data was captured into the computer since all the questions had been coded. It was then easy to enter the pre-coded answers into a database which was further analysed for the relevant relationships pertaining to the research questions.

75

During the later period of this research, Buffalo City Municipality evolved into a fully fledged metro immediately after the announcement of the results of the second truly democratic municipal elections of post-apartheid South Africa held on 18^th May 2011.

Therefore the study which began as an interrogation of the implementation of the Paris Declaration in one metro and one municipality in 2009 ended up being a study involving two metros.