Reliability and Validity

Having reviewed the theoretical assumptions and guiding principles of the core methodologies of this thesis, now I will discuss how CA/MCA research attempts to demonstrate its reliability and validity. CA/MCA studies, which potentially can be criticised by other disciplines due to its perceived issues in relation to the radically narrow analytic focus, as well as its management of inherent

subjectivity. Hence, it is important to touch upon the ways in which CA/MCA practioners enhance reliability and validity of their own research. This will be the main discussion point of this chapter, then a summary of the chapter 3 will be followed as the final sub-section.

3.4.1 Reliability

Reliability refers to ‘the accuracy and inclusiveness of research data’ (Peräkylä, 2016: 414). Increasing reliability of a CA study depends on how to capture and record high quality video/audio data. In this sense, the video recording should guarantee whether it allows the researcher to ‘unpack the detailed production of on-going activities’ through providing interactional resources that participants orient to (Heath, et al., 2010:7). This specifically means that the video data should enable the researcher to view ‘setting features in the unfolding organisation of participants’ comportment’ such as gaze, facial expression, gestures, bodily conduct and surrounding artefacts (ibid). This study follows this guideline as the video recordings have a clear view displaying the aforementioned features and resources embedded in the interview interactions. Research interviews are relatively easier to record than other interactional settings in which participants

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are mobile as interview interactions in general are conducted with the

interviewer/interviewee sitting down, closer to one another and immobile for the duration. Additionally, I used extra audio recorder (i.e. iPhone) as a second device in order to ensure the quality of sound. The extra audio recordings are contributed to produce accurate transcripts of this thesis thanks to its better quality of sound. Indeed, it was a helpful tool to increase the accuracy of my transcripts as I was able to use it as a back-up resource when there is slightly unclear utterances in my video data due to its background noise.

Sharing video data with fellow researchers in the same discipline is one of the standard assessments to increase reliability of analysis (This will be explicated at full length in chapter 4, data analysis section). Presenting video data not only enhances transparency to show what happens during the field work (within this study’s context, it is about what/how interviewer and interviewees did during the interviews) but also ensures replicability of findings, particularly when other researchers found similar observation points from the same transcript. This is one of the methodological strengths of CA as the presentation of the original data is not required in other disciplines in social sciences in general (Seedhouse, 2004). To sum up, CA’s standard practices including presenting the primary data with transcripts incorporating fine-grained details of interaction, create a locus for extra scrutiny enhancing reliability of analytic findings.

3.4.2 Validity

Ensuring validity in qualitative studies is achieved by several factors all based upon a reflexive acknowledgment, which is related to the spectrum between objectivity and subjectivity (Holliday, 2013: 5). Specifically, validity check for a qualitative study entails justification for 1) a choice of research setting and participants; 2) the subjectivity and influence of the researcher, which is a main developer for the design, structure and argument of a given study; 3) the

relationship between the analysis of the data and presentation/construction of its following discussion points; 4) analytic claims attuning to the scope and design of

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the study; 5) a clear elaboration upon how the data speaks (ibid). In sum, in order to ensure validity of a study, the researcher needs to test the credibility of the analytic arguments that has been suggested through data analysis (ibid). CA studies require a slightly different version of validity check as it has

developed its own methodological machinery from an emic perspective. Indeed, CA studies attempt to examine social interactions as phenomena in its own right. In this vein, I employed Peräkylä’s (2016) suggestions, in order to ensure the validation of my findings and discussions. Peräkylä puts forward six points for the validity check for CA research as follows: 1) the transparency of analytic claims; 2) validation through ‘next turn’; 3) deviant case analysis; 4) questions about the institutional character of interaction; 5) the generalisability of conversation analytic findings; 6) the use of statistical techniques (ibid: 415). Amongst the six points, validation through ‘next turn’ and questions about the institutional

character of interaction was the major validity check points, as these two are most relevant to the main context of this thesis.

Validation through next turn, simply indicates that ‘the analysis of the next

speaker’s interpretation of the preceding actions demonstrates the validation of the researcher’s interpretations’ (Peräkylä, 2016: 413). This is the so-called, ‘next turn proof procedure’ originally proposed by Sacks et al. (1974), which signifies the next turn displays its speaker’s understanding of prior turns. Hence, the understanding uttered by the speaker itself allows observers to have a proof criterion as well as a search procedure for their analysis of what a turn is occupied with. Indeed, it is one of the most important resources not only for CA analysis itself, but also for the validity check for analytic claims. Therefore, the next turn proof procedure is ingrained in analytic observation and claims in the forthcoming analysis chapters.

Questions about the institutional character of interaction is about how to transfer institutional contexts into data. In other words, how to import ‘institutional roles, tasks and arrangements’ in terms of analysing data as they may be or may not be present in an actual data (Peräkylä, 2016: 419). This is not a simple injection of general institutional aims into the data analysis. Rather, it is crucial to demonstrate

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how the institutional context is made relevant and procedurally consequential by interactants’ action in the talk-in-interaction. This is particularly important for this study as the institutional identity as interviewer and interviewee, which is

purportedly known as questioner and answerer, have been dynamically shifted in the data, and the interviewer’s self-disclosure is a part of the phenomenon.

3.5 Summary

This chapter has explored the methodological apparatus applied to the analysis of this study. Section 3.2 outlined CA as a methodology by discussing the theories behind the CA transcription process, along with the core principles of transcribing talk-in-interaction. Then, the section documented the notion of key interactional features from a CA perspective (i.e. turn-taking, sequence organisation and repair), which are the fundamental analytic lens to examine the corpus of this thesis, especially the instances of the interviewer’ self-disclosure. Section 3.3 eloborated upon MCA, another core methodology of this study by explicating its theoretical assumptions derived from ethnometholocial mentality concerned with categories and morality. Additionally, general principles of doing MCA analysis were illustrated along with the key concepts, which will be core basis of analysing identity work as a part of the interviewer’s self-disclosure. Section 3.4, briefly touched upon how to ensure realibitliy and validity of CA analyses. Built upon the discussion, the next chapter will introduce research settings of this study by describing participant information, ethical considerations and data analysis procedure.

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