Published online by Cambridge University Press: 11 July 2013
Noting limited attention by international development agencies to inequalities compared to global poverty, we ask how these two challenges have been framed in agencies’ policy publications during the past several decades. Following a recent application of algorithmic analysis to health policy narratives in the UK, we use text-mining software to compare the frequency of two alternative conceptualisations of poverty and inequality in three different document categories: the World Bank's World Development Reports, the United Nations Development Programme's (UNDP) Human Development Reports and a set of white papers by bilateral donor agencies. In a second step, we visualise each document's degree of contextual similarity in using the two conceptualisations of poverty and inequality with all documents in the same source category. We find that while references to poverty have, on average, been twice as prominent as references to inequality, conceptualisations of poverty and inequality as well as the textual contexts in which they appear differ both temporally and substantively between agencies included in our sample. We show how such agency-specific framing patterns can be leveraged politically to forge more effective social policy coalitions. We also outline follow-up research capable of capturing the politics of language underpinning our observations.