CHAPTER FIVE: ANALYSIS OF LIFE HISTORY DATA
SECTION 1: PROCESSES AND ISSUES OF REPORTING
5.1 Introduction
5.1.3 Second Level Analysis
maintained and the research story served as a first level analysis. I requested participants to comment on the revised version of the stories with the intention to enhance their 'truth value' .Few changes were suggested and these further revised versions are presented in Section 2 of this chapter as research stories.
All the comments and discussion revealed to me that the writing process is neither an innocent nor a romantic one. It was an occasion for me to reflect on the power of the written word and how dangerous constructing research stories can be.
According to Reddy (2000) there are no standard approaches to the analysis of qualitative data. However, the process was informed by analytic and grounded theorising as discovery-oriented approaches to analysis of qualitative data (McMillian & Schumacher, 2001). In the context oflife histories, the process was an intuitive one in which I intended to develop a configurative understanding of the unfolding experience. Therefore methodologically, I have chosen the approach of negotiated analysis.
Freeman (1996) explores this negotiated analysis within a framework based on three elements in data analysis and interpretation process. He calls them stance, process and categories. By stance he refers to the attitude the researcher adopts towards the participants in the research process. By process he refers to the linear or iterative process of data handling through the research. He regards both as binary choices. Either the researcher adopts a participatory stance where the participants are regarded as eo-analyst in the data analysis process or declarative stance where no further input is required of the research participants.
Freeman says the both stance and process in the data analysis are shaped by categories the researcher uses. Grounded categories (Freeman, 1996:372) are developed from data itself without prior assumptions of what their significance may be. On the other extreme, a priori categories (Miles & Huberman, 1996:152) are determined and used as a framework to organize and classify the data so that the findings emerge as responses to these predetermined areas. The a priori and grounded concepts,he says, forms the two ends of a continuum, which have at least two other categories: negotiated categories and guided categories.
Guided categories and negotiated categories are shaped by the interaction with the data.
Negotiated categories are those developed through participatory and usually iterative, analysis of data. These may begin with grounded categories but are modified and confirmed by researcher and participants in the meaning making process. Guided categories, while springing from a priori categories, responds to what the researcher actually finds in the data and are thus modified.
It is within this understanding of negotiated analysis,that the approach I used to analyse and interpret data, falls within the 'hypothesis generating' side of the continuum (see Figure 5.2)
EMIC
Outsider as Insiders
Hypothesis generation
ETIC Outsiders as Outsiders
Hypothesis testing
Grounded Anlaysis Categories and analysis emerged from the data with minimala priori expectation
Negotiated analysis Categories and analysis developed by the researcher with inputs of participants
Guided analysis Categories developeda priori:
subsequent analysis guided and categories modified through
interaction with the data.
Apriori Analysis Categories determined in advance of the data collection:
analysis according to those categories
------ Figure 5.2: Model for Data Analysis and Interpretation (Samuel, 2002)
In relation to the study, the process was informed by analytic induction and grounded theorising as discovery-oriented approaches to analysis of qualitative data. In the context of life stories, the process was an intuitive one in which each story described what happened in the lives and, by configuring the different dynamics through a plot, provides an explanation of why the life unfolded as it did.
The grounded theory approach to analyzing qualitative data has roots in the work of Glaser & Strauss (1967). Using a grounded theorising approach I wanted to generate explanatory constructs from the data, explaining how and why the changing history curriculum policy influences history teachers' understanding of their pedagogical roles.
The strict application of the original method has not been applied (Plurnmer, 2001), especially in life history research. The single long case is not amenable to the traditional
notions of theoretical sampling, where the researcher moves from one sampling source to the next according to strict theoretical criteria. In addition, the main emphasis of discovery of theory through rigorous engagement with the empirical data has remained as an important guiding principle in qualitative research.
In this study the inductive nature of analysis assumes an openness and flexibility in the process wherein the patterns and issues emerge from the data. Of course, it is argued that it is almost impossible to arrive at the analysis process with a 'blank slate'. Itis important not to force preconceived ideas into the data analysis process but to nevertheless interact with theory for the purpose of enhancing it. This study included the application of inductive strategies for the purposes of engaging with the data.
The process of grounded analysis did not begin at this point but was embedded in the interview and story construction processes. My intention was not to be guided by a priori theoretical categories but to rely on the empirical data to generate possibilities. The process began with a close reading and re-reading of data. Researchers like Hammersley
& Atkinson (1983), Miles & Huberman (1994) and Polkinghorne (1995) recommend 'immersing oneself in the data and then searching out patterns, identifying possible surprising phenomena and being sensitive to inconsistencies, such as divergent views offered by different groups of individuals'.In this study, I studied different facets of the emerging data in many ways and for varying purposes.
In the second level analysis, I first listened to the audio-tapes for the purposes of transcription and to gain a general understanding of the stories. I then re-read the transcriptions again, checking for accuracy. The third time I listened to the tapes and reviewed transcriptions was to generate an interpretative understanding and coding data.
The fourth time was to attend carefully to word choices, tones and emotions, what was repeated and what was not said. After the story revision I reviewed the data again and continued to do so throughout the analysis process. Having read and listened to the interview data many times, I found that I became very familiar with the stories. The continued immersion in the data allowed me to generate new and different ideas. I also
combined the emerging empirical understanding and theoretical position with intention to theorise creatively. I was also guided by the issues that participants thought were important in their research stories in forming my analysis.
During the initial stages of analysis my own frame of reference was limited. Having expanded my scope of understanding to various narratives and social texts I was able to read the data differently. For example, the experiences at school emerged as significant, but it became necessary to problematize this issue by understanding the school as a social institution and examining the power dynamics embedded in the experience. I remained guided by issues of variability, multiplicities and discontinuities, rather than only on seeking stable, coherent patterns across the data. At points, I realized that I slid towards seeking only regularities and that this did not serve the data well. I, therefore, remained vigilant about remaining grounded in empirical data. Life history data are rich and complex and I sometimes found that I was 'laying out or separating the threads' (Dhunpath, 2000) rather than to weave a tapestry of sorts.
I read across the individual research stories and interview data for the purpose of generating an analysis and looking for prevailing themes that I could use to classify the data. The fluid conception of identity formation and social relations presents particular problems for formation of fixed categories, which have the potential to reify and essentialise social categories. I coded the data and searched across the research stories data to find similar or conflicting themes or issues. The emerging themes were clustered and categorized. I used the assistance of a colleague, who is an experienced 'history' researcher, and who is familiar with my research, to do a form of analytical check. I gave him a list of the selected themes that I decided upon and the research stories and asked him to read through the stories and 'label' different responses in the margins (according to the chosen themes).
There was much agreement on the classification of categories between my colleague and myself. Ambiguous and doubtful themes were negotiated. There were some important
insights that emerged from the different ways in which two people look at the same set of data.
There was also a need to consider relationships across categories and over time in the second level of analysis. I then began the cross-case analysis (Patton, 1990). As Patton explains in this case, I approached cross-case analysis using a process of constant comparison between the six cases over time in relation to emerging constructs from the study. Reddy (2000) describes this as a mixed strategy which combines the case and issues / variables making it a preferred strategy in the context of life history research. I structured the analysis chronologically, looking for themes across the cases and examining how various themes / constructs unfolded over time. The discussion of each theme is generated through constant comparison between individual cases or by the clustering of cases that share certain patterns or configurations. An example of this type of analysis of what Miles& Huberman (1994) refer to as interactive synthesis of writing individual cases; then cross-case narratives with themes; then a general explanation and then going back to the individual cases to see how the explanation works there. My intention was to theorize in a way, which contributed to understanding experience as dynamic,human, social and political,that is a 'lively' theorizing (Cortazzi, 1993).
The analysis process stretched over a period of five months during which time I moved between emerging issues and the data and made notes when a theme began to emerge, around issues of identity formation there was also a need to re-read data in the context of the emerging issues and categories. As the process unfolded iteratively, there was a constant and intuitive play with constructs and categories across stories.
The intention of the cross-case analysis in the second level of analysis is to consider the issue of transferability of the emerging issues across cases and to deepen the understanding and explanation of particular constructs or issues by examining similarities and differences. I began by analyzing each case thoroughly, in relation to emerging themes. The details of the individual case analysis are not presented in the cross-case analysis. In life history research the cross-case analysis introduces a dilemma about
whether the individual story will lose its unique value as one seeks genenc understandings across cases. In this study I have attempted to accommodate the value of both these orientations by retaining the specificities of the individual case through the research story (first level analysis), and offering a cross-case analysis as a second level analysis. The analysis moved from particular to general issues across cases. My intention here was to present a set of emerging constructs which dialogize with the purpose of the study. The abstractions are not specific of the individual case but reflect the outcomes in the context ofthe critical questions raised in this study.
In this section I have explained how the process of data analysis unfolded. The data analysis process was iterative and influenced by the researchers' theoretical stance. Two levels of analysis, grounded in empirical data, contributed to theorizing in the context of critical questions. Two levels of analysis are provided:
• How the storied narratives were told (first level analysis): details concerning the choice of representation of different narrative forms are explored
• What was told through the storied narratives (second level analysis): details of emerging issues across cases and explanation of particular constructs or issues by examining similarities and differences are presented in response to critical questions raised in this study
In the section that follows, I present the first level analysis - the research stories.