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There is an identified need in higher education research for methods which have the capacity to generate conceptual insights grounded in concrete local practice but with wider applicability in understanding and facilitating research-based change. This chapter outlines an intermediate approach to qualitative data analysis which can support theoretical knowledge advancement from practice-based research, which I call the difference-within-similarity approach. It involves a particular way of conducting dialogues with our data: of interanimating similarities and differences within our qualitative datasets. The approach outlined involves first identifying a similarity, then systematically examining differences within that similarity to generate theoretical explanations. Drawing on sociocultural theorising, particularly dialogic theory and cultural–historical activity theory, the approach is based on the idea that new meanings arise from a comparison of multiple perspectives on the ‘same’ phenomenon. The tensions between such perspectives are seen as a key driver for change in educational practice. Therefore, articulating and examining such tensions in our data gives an opportunity to simulate the possibility of change in our analysis and, hence, develop insights which can inform change beyond local settings. Important here is that the differences examined are bound together by an analytically productive similarity. Through multiple research examples, the chapter identifies and illustrates a range of ways of articulating productive analytical similarities for comparison in our data: through theory/literature, through forward and backwards processing of data itself and through a process termed ‘weaving’.

Historically, counter-terrorism's attitude towards women has been complicated, partly because both counter-terrorism and terrorism were for many years considered almost exclusively a male business. This approach has also been reflected in the media's sensationalised representation of women involved in political violence. This chapter explores how women's participation in non-state political violence is still largely explained through traditional conservative notions of sexual difference that characterise women as irrational and highly influenceable, eliminating the possibility of any informed discussion. Focusing on the British case, the chapter shows how the actions of female militants are still bound to gendered narratives and limited to specific frames that generally portray violent women as highly sexualised and pathologised. Depictions of female terrorists and ‘radicalised’ women are based on stereotypes that reinforce the image of women as weak, easily influenced, naïve, driven by romantic emotions, deceitful and in constant need of protection and supervision. From an intersectional perspective, the chapter also explores the orientalist imaginaries of Muslim women who are seen as victims and as individuals lacking empowerment and agency. The discussion highlights ultimately that explanations of women's violence must go beyond myths that explain women's involvement in political violence via a wide range of personal and emotional factors, to examine political motivations and consideration of the complexity of their decisions, and the wider context.

Since the development of the COVID-19 vaccinations, questions surrounding race have been prominent in the literature on vaccine uptake. Early in the vaccine rollout, public health officials were concerned with the relatively lower rates of uptake among certain racial/ethnic minority groups. We suggest that this may also be patterned by racial/ethnic residential segregation, which previous work has demonstrated to be an important factor for both health and access to health care.

In this study, we examine county-level vaccination rates, racial/ethnic composition, and residential segregation across the U.S. We compile data from several sources, including the American Community Survey (ACS) and Centers for Disease Control (CDC) measured at the county level.

We find that just looking at the associations between racial/ethnic composition and vaccination rates, both percent Black and percent White are significant and negative, meaning that higher percentages of these groups in a county are associated with lower vaccination rates, whereas the opposite is the case for percent Latino. When we factor in segregation, as measured by the index of dissimilarity, the patterns change somewhat. Dissimilarity itself was not significant in the models across all groups, but when interacted with race/ethnic composition, it moderates the association. For both percent Black and percent White, the interaction with the Black-White dissimilarity index is significant and negative, meaning that it deepens the negative association between composition and the vaccination rate.

The analysis is only limited to county-level measures of racial/ethnic composition and vaccination rates, so we are unable to see at the individual-level who is getting vaccinated.

We find that segregation moderates the association between racial/ethnic composition and vaccination rates, suggesting that local race relations in a county helps contextualize the compositional effects of race/ethnicity.