Abstract
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.
Highlights
The ongoing revolution in the digital data landscape has given rise to a vast international network of research data repositories and infrastructures (Corti et al 2016; Hughes and Tarrant 2020a; Edwards et al 2020)
Debate on whether it was possible to re-use qualitative data emphasised the distinc‐ tion between primary and secondary analysts based on their connections to, or remove from, the contexts of data production (Mauthner et al 1998; Mauthner and Parry 2010)
Data are neither ‘fixed’ in any simple sense, nor can they ever be entirely separated or disconnected from the contexts of their production. We have found it useful to set out key activities involved in qualitative secondary analysis (QSA) in terms ofcontextu‐ alisation andconnection in order to clarify how reflexive engagement might be supported in QSA. (Re)contextualisation typically encourages us to engage in a reductive, analytical, process through which to explicate degrees of proximity and distance from a particular set of data
Summary
The ongoing revolution in the digital data landscape has given rise to a vast international network of research data repositories and infrastructures (Corti et al 2016; Hughes and Tarrant 2020a; Edwards et al 2020). Our second line of argument is that QSA is not a question of ‘analysis’ in the narrower sense of ‘reductive’ techniques or procedures; rather, that it involves modes of research engagement in the round In this way, we move from a view of data as a neutral and reified ‘product’, towards a consideration of how researchers apprehend different orders of data to recast these as evidence (Hughes et al 2020b). We propose that such engagement can be more ‘synthetic’, entail‐ ing not just the (re)contextualisation and the (re)connection of research through QSA, as researchers repurpose data in new ways and in new contexts (Moore 2007) Such recon‐ nection in part involves the synthesis of different orders of data by bringing them into con‐ versation with one another, as well as with evidence, findings, theory, and developments in the social world beyond the original study contexts (see Irwin and Winterton 2011a; Fielding and Fielding 2000).
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