Social cohesion is a key concept in development studies. Weak social cohesion is often related to slow economic growth and (violent) conflict. So far few attempts have been made to measure this complex concept in a systematic manner. This paper introduces an innovative method to measure national-level social cohesion based on survey data from 19 African countries. We distinguish three dimensions of social cohesion; i.e. the extent of perceived inequalities, the level of societal trust, and the strength of people's adherence to their national identity. Importantly, our social cohesion index is based on individuals' perceptions vis-à-vis these three different dimensions of social cohesion rather than certain macro-level 'objective' indicators such as GDP/capita or Gini-coefficients. We develop two social cohesion indices: a national average Social Cohesion Index (SCI) and a Social Cohesion Index Variance-Adjusted (SCIVA); the latter one takes into account the level of variation across different ethnic groups within countries. The SCI and SCIVA are computed for and compared across nineteen African countries for the period 2005-2012 on the basis of Afrobarometer survey rounds 3, 4 and 5. We also investigate quantitatively the relationship between countries' levels of social cohesion and the occurrence of a range of conflict events. As expected, we find that countries with low levels of social cohesion in a particular year according to our SCI are more likely to experience a range of different conflict events in the subsequent year.

Recent spikes in international food prices and the occurrence of 'food riots' in the period 2007-2008 has led many researchers to investigate the links between food prices and conflict or political instability more closely. However, this emerging literature suffers from a number of flaws and misunderstandings. The objective of this paper is to discuss these further and offer ways of addressing them. I focus on three main issues: firstly, the vague use of concepts such as 'political instability' or 'conflict', which leads to conceptual and empirical confusion. In addition, specific doubts are placed on the usefulness of the 'food riot' concept. Secondly, the often uncritical data gathering based on international media sources. And thirdly, the issue of presupposed and understudied causal mechanisms and a general neglect of the importance of context.

Since attaining independence, Nigeria has experienced recurrent tensions due to the severe horizontal inequalities that exist between different regions and ethnic groups. After the end of the Biafran civil war, consecutive regimes embarked on a reform process intended to address the sensitive issues of inequality and ethnic domination. Key reforms included the adoption of the federal character principle to ensure the equitable representation of different groups in all tiers of government, and the formation of the Federal Character Commission (FCC) to monitor and enforce its implementation. While the FCC has raised hopes on redressing historical imbalances in Nigeria's civil service, this paper finds that little progress has been made over time. The workings of the FCC remain plagued by legal and administrative constraints, chronic underfunding, and political dependence. These issues will need to be addressed if the FCC wants to gain the legitimacy and power needed to fulfil its mandate.

While conflict event data sets are increasingly used in contemporary conflict research, important concerns persist regarding the quality of the collected data. Such concerns are not necessarily new. Yet, because the methodological debate and evidence on potential errors remains scattered across different subdisciplines of social sciences, there is little consensus concerning proper reporting practices in codebooks, how best to deal with the different types of errors, and which types of errors should be prioritised. In this article, we introduce a new analytical framework—that is, the Total Event Error (TEE) framework—which aims to elucidate the methodological challenges and errors that may affect whether and how events are entered into conflict event data sets, drawing on different fields of study. Potential errors are diverse and may range from errors arising from the rationale of the media source (e.g., selection of certain types of events into the news) to errors occurring during the data collection process or the analysis phase. Based on the TEE framework, we propose a set of strategies to mitigate errors associated with the construction and use of conflict event data sets. We also identify a number of important avenues for future research concerning the methodology of creating conflict event data sets.

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