Post developed by Anne Pitcher, Rod Alence, Melanie Roberts, and Katherine Pearson

Secure elections are essential to democracy. ObSERV, a new study by researchers at the Electoral Institute for Sustainable Democracy in Africa (EISA) and the University of Michigan, with support from the University of Witwatersrand (Wits), presents a data collection methodology that improves the placement of election observers in order to improve the quality of their observations regarding the electoral process.

Election Observation Missions (EOM) seek to provide impartial observation of the electoral process in order to ensure the peaceful conduct of elections and to protect the rights of citizens to participate and to vote. On the African continent, however, the deployment of observers has been driven more by practical convenience than by a representative and systematic approach to deployment. Deploying observers just taking convenience into consideration potentially results in the collection of information from observers that is biased or misleading. Subsequently, this information can influence the content and tone of election reports that EOMs issue regarding the extent to which elections are “free” and “fair”.

Observer data that is collected more systematically and is geographically referenced provides a more accurate and representative description of an election. Such data can also be linked more fruitfully to other sources of contextual information – from local demographics and infrastructure to partisan polarization and the prevalence of political violence. ObSERV’s approach to deploying observers not only supports the goal of assessing how free and fair the current election is, it also enables researchers to analyze and better understand the causes of deeper threats to democracy, such as election-related violence and electoral fraud.

How does ObSERV work? 

ObSERV uses computer algorithms to group polling stations into local clusters and then to draw a random sample of clusters to be visited by observer teams. Stations are clustered to minimize driving distance for each team, which must cover at least 12 stations on election day, using routing tools similar to those used by modern carpooling apps. Clusters are then categorized between regions and urban and rural locations, and the required number of clusters is selected randomly within each category.

Clusters are subjected to a security assessment, to ensure that observers can safely access them. Where the security assessment (commissioned by the observer mission itself) identifies safety concerns with a cluster, it is removed and a substitute is drawn using the ObSERV method. Once in the field, observers use EISA’s Popola monitoring system to report on a range of election-related activities, from rallies to voting. The information captured helps the mission evaluate the overall conduct of the election, and a substantial part of it is curated for inclusion in the ObSERV data set.

The value of ObSERV

By collecting observer data systematically and attaching geographical coordinates, ObSERV facilitates linking to other data sets relevant for analyzing and better understanding localized patterns of election-related violence. Applications are not limited to issues of electoral security and violence. The data collected also include station-level details such as long voter queues, missing materials, voters being turned away, and voters showing up at the wrong station.

ObSERV’s approach can be adapted for anywhere observation takes place, as it accommodates the practical challenges of deploying an observer mission. By applying systematic methods, observers end up observing polling stations that have previously been overlooked, improving the quality of election observation. Over time, use of the ObSERV method will contribute to a cumulative body of research data, promoting better understanding and analysis of African elections and ultimately help protect the integrity of the democratic process.