‘Recession, it's all the same to us son’: the longitudinal experience (1999–2010) of deprivation

Who is vulnerable to energy poverty in China?

Energy poverty has been identified as a problem in China, but research to date does not discuss who experiences it, unlike in other countries. Here, we compared sociodemographic characteristics known to be linked to energy vulnerability in other nations between energy poor (EP) households and non-EP households, using the 2018 survey data from China Family Panel Studies (CFPS). We found that a range of sociodemographic characteristics associated with transport, education and employment, health, household structure, and social security, are disproportionately distributed among five provinces (Gansu, Liaoning, Henan, Shanghai, Guangdong) in our study. EP households are more likely to have low housing quality, low education, old people, poor mental/physical health, be mainly female, be rural-Hukou, be without pension, and lack clean cooking fuels. In addition, the logistic regression results further evidenced the increased likelihood of experiencing energy poverty given vulnerability related socio-demographic predictors in the full sample, in rural-urban areas, and in each single province. These results suggest that vulnerable groups should be considered specifically when formulating targeted policies for energy poverty alleviation to avoid exacerbating existing energy injustice or creating new ones.

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

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.