I wanted to investigate how deeply instilled concepts of ableism are and how they are perpetuated, as I believe that only by rooting them out can we begin to understand and thus change them. What I am interested in is the extent to which these views are inculcated into educational institutions, which then filter down to infect the minds and bodies of our young people; and the effect this has on disabled people’s sense of self-worth.
As Braun and Clarke assert in their 2018 lecture, thematic analysis can best be seen as an umbrella term for qualitative analyses that focus on identifying patterns across a data set. It is a flexible approach that can be used with a range of theoretical orientations, but here I will be following their stated preference: reflexive thematic analysis. What this means is that I will be reflecting on the processes I use to infer my analysis of the participants stories, ‘emphasising the active role of the researcher in the knowledge production process’ (Clarke et al., 2019:6) and using my subjectivity as a valid resource. As such, I aimed to critically engage with the meanings, significance and implications of any patterns identified and acknowledged my active role in doing this.
Braun and Clarke’s (2006; 2013; 2018; 2019) version of thematic analysis appealed to me as a flexible, responsive approach that can be applied across my frameworks of critical social psychoanalysis, studies in ableism and postconventialism. I wish to focus on the issues within neoliberal university education as experienced by my participants psychologically and emotionally, and to take account of the impact of ableism as operating with/in their worlds. I attempted to conduct my analysis not just at a semantic level, but to uncover the latent assumptions and ideologies that underlie the semantic content of the data (Braun & Clarke, 2006:13). Because of the way that I as a researcher am deeply embedded in the research that I conducted; the length of time between data collection and analysis; and my ontological position as a disabled student, I inevitably brought to the analysis certain predetermined theoretical
72 concepts. The way that this could have impacted on the analysis is that it could have morphed into a deductive rather than an inductive process with me trying to squash the data corpus into fixed conclusions. My analytical lens and my positionality inevitably had an effect on the analysis procedure.
Because of the laborious one-finger typing I can do, it was not feasible to transcribe the voice- based (in-person and Skype) interviews myself, but they were transcribed in an orthographical manner, recording most of the false starts, interruptions, hesitations, murmurs and pauses of the interview. At first I was horrified at this blatant mapping of my (flaw) and I felt an urge to delete all of my stutters and hesitations in my own reported speech. However these fluctuations in the fluency of speech can be hugely insightful and can be indicative of many aspects of the interview encounter. As all my voice-based interviews were audio-recorded, I have the benefit of being able to revisit them at my leisure, armed with the theoretical lens that has come from the completion of the data collection process.
Braun & Clarke (2006) suggest a 6-step framework for the actual ‘doing’ of thematic analysis, but caution researchers that this should not be seen as a linear, unidirectional process. Instead they encourage conscientious researchers to pause, rethink and retrace these stages in order to achieve a rich, intricate analytical account of the research.
The Braun & Clarke (2006) way (adapted from Braun & Clarke, 2012)
Phase 1: Familiarisation
During phase one, the researcher immerses herself in the data, reading and rereading each transcript or piece of data and making notes on the pertinent sections. Making notes and actively reading the transcripts, Braun and Clarke (2012:60), enables the researcher to ‘treat the data as data’ and to think through what might be implied by the words spoken or, indeed, unspoken. We can then start to get a sense of the participant’s world, and of themselves as operating within that world. Braun and Clarke recommend that the researcher reads through the entire data set at least twice in order to obtain a clearer picture of what they are working with before trying to generate codes. They are encouraged to make notes on individual transcripts as well as the whole data set but at this stage the notes will be more like initial observations rather than in-depth analytical interpretations.
Phase 2: Generating initial codes
This stage is where the researcher contextualises and begins to make sense of the interview transcripts in relation to their particular research question. The codes can be derived from a
73 semantic reading of the transcript and/or a more latent interpretation that attempts to capture the underlying meaning behind participant’s utterings. Codes at this stage can be descriptive, eliciting the actual content of the more pertinent data. As the researcher embraces the context of the transcript, allows herself to become enveloped in the threads of the encounter, she can become more highly tuned in interpreting the particular nuances implied by the participant in relation to your research questions. The researcher needs to read through all the data item for one identified code before moving on to the next code, modifying as necessary. Codes will likely deepen and diversify, potentially splitting into separate codes as the codification procedure develops and matures, and so will require constant re-reading and reabsorption to see the richness of the data throughout. Braun & Clarke (2006; 2012; 2013; 2018; 2019) do not specify a saturation point for the number of codes identified, rather they encourage the researcher to generate enough codes to adequately capture the breadth, diversity and the patterns within each data item and across the data set more broadly.
Phase 3: searching for themes
This is where the analysis starts to take shape as the researcher begins to discern patterns amongst the data set. They will look for broad patterns around which a group of codes clusters, identifying a unifying theme for a group of codes. The way the researcher sculpts these codes is individual to the researcher themselves; the themes are not just waiting to be discovered but are instead a product of the ontology of the researcher, the literature and the data itself. This is abhorrent to researchers coming from a more positivistic stance as it will be incredibly difficult to replicate, even with the same researcher as their experience of conducting this study will inevitably have some degree of influence on any further studies carried out. Themes ‘reflect and describe a coherent and meaningful pattern in the data’ (Braun & Clarke, 2012:63) in relation to a research question. Certain themes may overlap, and the researcher needs to think at this stage about how the themes will fit together to construct a larger picture, or story of the data. It is useful to view themes as part of a jigsaw puzzle, with each theme as discrete conceptual factors but better construed as part of a larger whole.
Phase 4: reviewing the themes
The developing themes need to be reviewed in relation to the coded data and entire data set (Braun & Clarke, 2012). Questions the researcher needs to ask herself around the quality of the theme include: does this theme tell me something important about my data in relation to my research questions? What are the boundaries of the theme (what does it include/exclude)? Is there enough meaningful data to support this theme? Is the theme coherent enough? Once these
74 questions are considered, Braun & Clarke advise, the researcher will then need to undertake the second stage in the review process: do these themes work in relation to the entire data set? The aim is to produce a set of themes that capture the ‘most important and relevant aspects of the data’ (Braun & Clarke, 2012:64) whilst giving an overall flavour of the research study.
Phase 5: defining and naming themes
When executing this aspect of the analysis procedure, the researcher needs to be able to state what is distinct and precise about each theme, with the boundaries clearly defined. Good thematic analysis will have themes which are related but do not overlap, and have a singular focus which can be summed up in a few sentences. Together the themes should build up a rich, vibrant picture of the research with a clear focus on the particular research questions addressed. However in qualitative research often the themes themselves can be developed into sub-themes to describe overarching patterns in the data that are linked but are performed in various different ways in the participant’s stories.
Each theme can be illustrated with a few choice extracts from the data that adequately represent the uniqueness of that theme. When selecting extracts to quote, Braun & Clarke (2012:67) warn, the extracts do not simply ‘speak for themselves’. Rather, the researcher needs to explain what is interesting about an extract, what analytical argument it helps to describe, and why they have chosen this particular quotation. The researcher also needs to remember to cite extracts from across the data corpus, not just focus on one or two participants who seem to capture a point eloquently and succinctly. This has special relevance to Project 1 as I focus on the valuation of speech and communication, and I need to fight the urge to select only those participants who neatly summarise the analytical claims I am trying to make. All of my participant’s experiences are equally valid, and I want to represent this factor in my analysis and throughout. This may make the reader’s job slightly more difficult as perhaps the participant’s stories are not ‘pithy’ extracts that concisely sum up my explanatory arguments. This in fact shows the ableist nature of thematic analysis as it has been conceived by Braun and Clarke (2006), and indeed by others advocating this approach. The reader of most research studies wants to discover the new dimensions brought about by the addition of the research to the field, and expects the research to be presented in a succinct and eloquent manner. In this way, reported speech is only valued if it is clear, to-the-point, fluid and articulate. I anticipate tension between wanting to create a good account of my research, and being reflective of the ableism contained in social science investigations themselves. This sentiment will be developed further in Chapter Four.
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Phase 6: producing the report
Here the researcher needs to pay close attention to the ordering of the themes. If one theme provides an overarching argument for the rest of the analysis, it makes sense to begin with that theme. The others should build on and take shape from this topic, creating a vivid picture of the research story in relation to the particular research questions, and the study should be embedded in a scholarly field. The researcher needs to make her theoretical orientations abundantly clear throughout thematic analysis, as it is often wrongly conceived of as atheoretical (Braun & Clarke, 2018). The assumptions made by the researcher are ontologically informed, and the final report should give appropriate recognition of this fact. In summary, what is needed in reflexive thematic analysis is a clear, detailed account of what the researcher has done and why they have done it – to focus not only on the content of the study but the process by which it was carried out. This should provide sufficient information for the reader to analyse the quality and credibility of the research.
Through this method of analysis I hoped to co-construct stories that explicitly expose the insidious ableism lurking within our educational systems. It began to weave together experiential, personal narratives and the structures and contours of society, accentuating how each shapes the other. By applying a postconventional framework to the analysis, the aim was to generate alternative pedagogical practices with the needs and desires of disabled people at their heart.