A Tale of Two Analyses: The Use of Archived Qualitative Data

Haynes, Jo; Jones, Demelza

doi:10.5153/sro.2523

Cited by 10 publications

(11 citation statements)

References 17 publications

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“…Students using the data archive's resources often write their masters theses based solely on archived qualitative data sets. Compared with collecting their own data for the theses, using archived data has the advantage of allowing students to spend significantly more time on thinking, analysis, and interpretation rather than on data collection (Haynes & Jones, 2012).…”

Section: Measuring Data Reuse Using Information From Data Downloadsmentioning

confidence: 99%

Revisiting Qualitative Data Reuse

2017

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Secondary analysis of qualitative data entails reusing data created from previous research projects for new purposes. Reuse provides an opportunity to study the raw materials of past research projects to gain methodological and substantive insights. In the past decade, use of the approach has grown rapidly in the United Kingdom to become sufficiently accepted that it must now be regarded as mainstream. Several factors explain this growth: the open data movement, research funders' and publishers' policies supporting data sharing, and researchers seeing benefits from sharing resources, including data. Another factor enabling qualitative data reuse has been improved services and infrastructure that facilitate access to thousands of data collections. The UK Data Service is an example of a well-established facility; more recent has been the proliferation of repositories being established within universities. This article will provide evidence of the growth of data reuse in the United Kingdom and in Finland by presenting both data and case studies of reuse that illustrate the breadth and diversity of this maturing research method. We use two distinct data sources that quantify the scale, types, and trends of reuse of qualitative data: (a) downloads of archived data collections held at data repositories and (b) publication citations. Although the focus of this article is on the United Kingdom, some discussion of the international environment is provided, together with data and examples of reuse at the Finnish Social Science Data Archive. The conclusion summarizes the major findings, including some conjectures regarding what makes qualitative data attractive for reuse and sharing.

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Section: Measuring Data Reuse Using Information From Data Downloadsmentioning

confidence: 99%

Revisiting Qualitative Data Reuse

2017

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“…This trend in data reuse has also been driven by innovation in early methodological advances that facilitated multiple interpretations of the same data . The varied and creative ways in which existing data are being re-constructed and re-contextualised to produce new insights and knowledge stands testament to the social scientific value of QSA (see, for example, Savage, 2005;Moore, 2007;Irwin and Winterton, 2011a, b;Duncan, 2012;Haynes and Jones, 2012;Bornat et al, 2012;Neale, 2017). A less developed strand of this debate, however, concerns the complexities and affordances of bringing multiple datasets from different research teams into 'meaningful analytical conversation' and translating evidence across them (Irwin et al 2012) 4 .…”

Section: Qsa: Our Approachmentioning

confidence: 99%

Qualitative Secondary Analysis: Building Longitudinal Samples to Understand Men’s Generational Identities in Low Income Contexts

Tarrant

Hughes

2018

Sociology

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There have been significant developments in methods of qualitative secondary analysis (QSA), prompted in part by growth in infrastructure for archiving and sharing qualitative data, facilitating reuse. Building from these developments, this article presents QSA that brings together subsamples of men in low income contexts from two qualitative longitudinal datasets produced under Timescapes, demonstrating the complex linkages between them, and addressing two key questions. First, in bringing these two datasets together, is it possible to build an intergenerational sample of men in low income contexts to further our understanding of their generational identities and intergenerational experiences? Second, what sorts of intergenerational, or intra-generational, analyses are possible? We conclude that it was not possible to build a straightforwardly vertical intergenerational sample, but our theoretical focus on generational identities has enabled insights into the dynamic relational processes productive of longitudinal experiences of marginalisation and vulnerability for men living in low income contexts.

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“…Our second worked example, here of collective QSA, draws on a two-day workshop of which Author A was a part, which involved bringing together the research teams from two separate studies, again under Timescapes: the Grandparenting study (as described above) and The OldestGeneration (TOG). 5 This workshop was held to explore and promote methods and strategies for reusing archived QL data such as through collaborative analysis (see especially Bornat et al 2008 ; also, Irwin et al 2012 ; Thomson et al 2012 ; Haynes and Jones 2012 ). Indeed, our model of collective QSA 6 builds directly out of this tranche of work.…”

Section: Collective Qualitative Secondary Analysismentioning

confidence: 99%

Working at a remove: continuous, collective, and configurative approaches to qualitative secondary analysis

Hughes

Tarrant

2021

Qual Quant

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In this paper, we define and operationalise three modes of research engagement using qualitative secondary analysis (QSA). We characterise these forms of engagement as continuous, collective and configurative. Continuous QSA involves modes of engagement that centre on asking new questions of existing datasets to (re)apprehend empirical evidence, and develop continuous (or contiguous) samples in ways that principally leverage epistemic distance. Collective QSA characteristically involves generating dialogue between members of different research teams to establish comparisons and linkages across studies, and formulate new analytic directions harnessing relational distance. Configurative QSA refers to how existing data are brought into conversation with broader sources of theory and evidence, typically in ways which exploit greater temporal distance. In relation to each mode of engagement we discuss how processes of both (re)contextualisation and (re)connection offer opportunities for new analytical engagement through different combinations and degrees of proximity to, and distance from, the formative contexts of data production.

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A Tale of Two Analyses: The Use of Archived Qualitative Data

Cited by 10 publications

References 17 publications

Revisiting Qualitative Data Reuse

Revisiting Qualitative Data Reuse

Qualitative Secondary Analysis: Building Longitudinal Samples to Understand Men’s Generational Identities in Low Income Contexts

Working at a remove: continuous, collective, and configurative approaches to qualitative secondary analysis

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