Thinking about Transcripts 2

While I continue to read, code, make connections, and bring forward new questions and ideas, I think more about these transcripts that I take to be the primary source of information. I ponder about how these text based words become the ‘stuff’ upon which my research resides, rather than the video recordings from which they derived. Is there a way to capture the moments in video form without revealing the identity of the participants? Is there a way to create a collage of instances, of ideas emerging, of struggles putting ideas into words, and efforts to make meaningful what needed to be understood? Can this be done without revealing who said it or how it was said, within a collage of sound and movement, that somehow anonymizes the voice of participants without losing the voiced message, without committing the ideas shared to a static page of text.

These thoughts are ‘singing’ through my mind today, as I continue to read about transcription as a form of liminality, neither in time and space. This is a ‘betweenness’ which I need to accept, a moment where I can “activate a different sort of listening and attention” (Cannon, 2018, p. 572). As I work through the second round of coding and build sense out of the transcriptions, re-viewing the videos of the interviews and re-listening to the voices of the participants, I need to sit comfortably in the disarray of ideas. As I ponder the interplay between video, textual transcript, graphic word clouds, and artifactual objects Cannon’s (2018) words echo loudly.

“How did this exploration, this play, function in my thinking/researching? How might it function for you as reader/listener? In considering how to make a better representation, or whether to make one at all, and seeking some other kinds of truth or ways of knowing, I fear I lost the participant completely. Perhaps this is the point, since she could never be represented fully. She is always already lost to me. And the representations have always already failed”

Cannon, 2018, p. 579

Skukauskaite (2012) suggests that there is no singular way to transcribe or make visible the decisions I make while conducting these transcriptions. My ontology and epistemology guide the decisions, providing foundation for the warrants and claims I may make about the recorded and observed interactions and actions with the human ‘subjects’ of this research. While I am creating the codes and phrases to bring sense to the interview data, it is singularly my belief and/or bias that determines the words attached to the ideas emerging from the interviews. As I struggle through this liminal space, each word or code I attach to an idea expressed by the participants is in itself a way of attaching a new representation of thoughts expressed, thus moving away from the individual as I seek new ways of knowing.

What Jamison et al. reminds me is that the NVivo software I am using to code the transcripts and artifacts also extends this ‘re-presenting’ into new forms of representation. From the codes I attach to the ideas shared by the participants, I can then re-present the ideas. From this action, my analysis may become more rigorous since I can easily pull quotes from various participants together under one word or concept (Jamison et al., 2018). I can move and re-c0de ideas as I review and re-listen. What I am finding on the second round of coding is my attention and focus on the unspoken and un-captured nuances of body language and emotions that the textual transcripts cannot capture.

Weller et al., bring something else into focus – the need to know if I’ve captured enough? Did I include enough participants to make meaningful connections to the core ideas I’m researching? Did I achieve some measure of saturation or salience in the fourteen interviews I conducted? These authors, in their investigation of the importance of probing during interviews to achieve adequate relevance to a domain of information, determine that “saturation in salience” (Weller et al., 2018, p. 15) is a more important measure for determining an adequate sample size. Saturation “defined as the point where less than one new item would be expected for each additional person interviewed” (Weller et al., 2018, p. 7) was deemed useless in determining a sample size stop point. By examine salience as an alternative measure, Weller et al., (2018) determine: “If an investigator wishes to obtain most of the ideas that are relevant in a domain, a small sample with extensive probing (listing) will prove much more productive than a large sample with casual or no probing” (p. 14, emphasis in original). This suggests I need to look at the type and frequency of my probes during the interviews to see how they support participant ideation.

What St. Pierre provokes in my thinking is the “textualization” of information that is unwritten or unwrite-able, the process whereby it becomes “fixed, atomized, and classified as data of a certain type” (St. Pierre, 1997, p. 179). What St. Pierre identifies for me in this exploration into data and analysis are “three non-traditional kinds of data – emotional data, dream data, and sensual data – and named another, response data” (St. Pierre, 1997, p. 179). My need for data at all, and how analysis emerges from a positivistic ontology, fails to honour the emergence of the lived experiences I hope to explore – this is not data to be counted, tabulated or categorized.

“…the values that enable the methodological instrumentalism and practices of formalization that discipline social science inquiry to make it scientific—e.g., systematicity, linearity, accuracy, and objectivity; obsessive concerns with individuating, sorting, and categorizing; the consensus of disciplinary communities, IRBs, and so forth—leach our energies and constrain experimentation …”

St. Pierre, 2013, p. 226

How do I avoid the scientific taint that is inherently attached to the terms ‘data’ and ‘analysis’ while staying true to the post-intentional phenomenology that points to emergence as a realized outcome of research?

References

Cannon, S. O. (2018). Teasing transcription: Iterations in the liminal space between voice and text. Qualitative Inquiry, 24(8), 571–582. https://doi.org/10.1177/1077800417742412

Jamison, T., Kemp, C. L., Speirs, K. E., Swenson, A., & Vesely, C. K. (2018). Dialogue about qualitative data analysis software. In Á. Humble & E. Radina (Eds.), How qualitative data analysis happens: Moving beyond “themes emerged” (1st ed., pp. 221–227). Routledge. https://doi.org/10.4324/9781315171647-16

Skukauskaite, A. (2012). Transparency in transcribing: Making visible theoretical bases impacting knowledge construction from open-ended interview records. Forum: Qualitative Social Research, 13(1), Article 14.

St. Pierre, E. A. (1997). Methodology in the fold and the irruption of transgressive data. International Journal of Qualitative Studies in Education, 10(2), 175–189. https://doi.org/10.1080/095183997237278

St. Pierre, E. A. (2013). The appearance of data. Cultural Studies ↔ Critical Methodologies, 13(4), 223–227. https://doi.org/10.1177/1532708613487862

Weller, S. C., Vickers, B., Bernard, H. R., Blackburn, A. M., Borgatti, S., Gravlee, C. C., & Johnson, J. C. (2018). Open-ended interview questions and saturation. PLOS ONE, 13(6). https://doi.org/10.1371/journal.pone.0198606