The article illustrates some of the strategies we are developing in the secondary analysis of Timescapes data and seeks to draw some general lessons for qualitative data analysts. We focus on three different areas of work. Across all of these we examine the potential explanatory value of working with data in a comparative way, and engage with some challenges presented by contextual specificity in the way qualitative data are generated. In the first area we consider the issue of how we situate qualitative data with reference to diversity across the population, and use an example of working between a single qualitative Timescapes data set and survey data. Understanding how qualitative data are situated offers a framework for internal comparison which maps onto wider diversity. In the second area we consider the outcome of bringing together primary researchers whose comparison of project data, as secondary analysts, allow them to 'hear silences' and, therefore, re-interrogate their own data within a revised conceptual framework. In the third area we describe how, as secondary analysts, we have worked across Timescapes data sets. Here we consider the challenges of undertaking secondary analysis across diverse, project specific, research contexts, and the potential of comparative working across data sets for enhancing understanding.

The current paper takes as a focus some issues relating to the possibility for, and effective conduct of, qualitative secondary data analysis. We consider some challenges for the re-use of qualitative research data, relating to researcher distance from the production of primary data, and related constraints on knowledge of the proximate contexts of data production. With others we argue that distance and partial knowledge of proximate contexts may constrain secondary analysis but that its success is contingent on its objectives. So long as data analysis is fit for purpose then secondary analysis is no poor relation to primary analysis. We argue that a set of middle range issues has been relatively neglected in debates about secondary analysis, and that there is much that can be gained from more critical reflection on how salient contexts are conceptualised, and how they are accessed, and assumed, within methodologies and extant data sets. We also argue for more critical reflection on how effective knowledge claims are built. We develop these arguments through a consideration of ESRC Timescapes qualitative data sets with reference to an illustrative analysis of gender, time pressure and work/family commitments. We work across disparate data sets and consider strategies for translating evidence, and engendering meaningful analytic conversation, between them.

The expansion of higher education in the UK has been accompanied by ongoing class related inequalities in expectations about, and access to, university. In the context of detailed research into middle-class and working-class experiences and difference, there have been calls for more detailed analysis of internal class diversity, and for complicating the class dichotomy. This is particularly important for understanding the experiences of prospective first generation students. Drawing on data from an Economic and Social Research Council (ESRC) funded study, this article offers a qualitative longitudinal analysis of young people's expectations about going to university, as these evolve over the teenage years, from 14 to 18. We analyse the experiences and expectations of young women with different parental class and educational backgrounds. We explore the interplay of parental expectations, school, teacher and friendship group influences through the teenagers' biographies. The qualitative longitudinal analysis offers valuable insights into how different influential processes intersect and play out for those with different backgrounds and circumstances, shaping expectations in divergent ways. As such it contributes to a more processual account of the structuring of social inequality in higher education expectations.

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