The nature of qualitative research means doctoral students often collect large amounts of data, and it can be difficult to make sense of such a deep pool of views, opinions, interpretations, accounts and records. Moreover, it isn’t unusual to collect qualitative data using a mix of approaches, such as oral interviews, focus groups, informal conversations, observations and documentary reports. For these reasons, students often struggle with the sheer volume of data and find it difficult to write up their findings in a way they feel does justice to the wide range of arguments and perspectives involved, while developing and maintaining a coherent narrative that responds to their research question. In this chapter, the author shares some insights on how to make writing up qualitative findings less challenging. Specifically, he offers a four-step drafting process that involves the techniques of mind mapping, outlining, illustrating the narrative and integrating the evidence.
Victor Oyaro Gekara
Victor Gekara and Darryn Snell
New digital and automation technologies are causing major industrial transformations and far-reaching disruptions to people’s working lives. The nature and extent of these technologies are the subject of heated policy and academic debate, but they are yet to be fully understood. Debates have mostly focused on ‘future of work’ and the question of employment loss as technologies become more advanced and sophisticated in their capabilities and functionality. This ‘future’ focus has, in our view, obscured the important issue of the extent to which workers are losing jobs now. Instead, we suggest a shift in focus to how technologies are changing occupations and the texture of work and skills demands; which workers are most at risk and the nature of risk; whose responsibility it is to assist displaced workers in finding new work in the emerging order of work; and what policies, strategies and programmes should be developed for employment assistance in these circumstances.