A Global Database on Migrant Boat Losses at Sea, 1990 to 2015

The A Global Database on Migrant Boat Losses at Sea contains information on migrant boat losses worldwide between 1990 and 2015. To construct this database, we employed a mixed methodology designed to locate, record and analyse boat losses to fill gaps we identified in the border externalisation literature. This involved collecting data from media aggregators and additional sources using content analysis for descriptive and time series statistical analysis. Our novel contributions via the database included to generalise time and geography in our analysis of boat losses, use of statistical methods therein and the provision of new empirical evidence related to the claim in migration studies that tougher border enforcement in the name of deterrence is generally ineffective in reducing migrant flows.

The “Boat Cemetery” on the island of Lampedusa, Italy, 2013. Photo credit: Massimo Ricciardo.

Summary

While migration by boat is an ancient human phenomenon, recent increases in deaths of migrants crossing the sea reached historical highs among those trying to land on sovereign territory of nation-states of the “Global North”. Increases in deaths also were accompanied by significant increases in global media coverage and resources dedicated to enforcement operations in the annual budgets of border enforcement activities. Despite this, little existing scholarship tracked this relationship between increased enforcement and migrant losses at sea. This project, therefore, worked to empirically demonstrate correlations between observed boat losses and enforcement using statistical methods.

Our findings were published in the journal International Migration in 2018 under the title, “Between Enforcement and Precarity: Externalization and Migrant Deaths at Sea”. In this article, and based on this database, we argued that although discourse about boat interception and externalisation has shifted to humanitarian rescue narratives, offshore enforcement by any other name continues to be highly correlated with migrant deaths. Our analysis continues to be timely due to empirical spikes in human displacement worldwide.

Data Structure

We built the collected data into a structured database sourced from targeted queries on two large media databases, LexisNexis and Factiva, as well as search engines to locate reports on migrant boat losses. We analysed and stored these articles in portable document format (PDF) for recording in our database. We were interested in a number of variables, including data of the loss incident, ship name, location, region, estimated passengers, estimated losses, ship origin, passenger origins, desired destination and related enforcement activities. The resulting data were linked through a comma-separated value (CSV) table to the PDF files for analysis in Stata 14.

In terms of linkages in the database, we named each article file after the case it represents; “1.pdf”, therefore, represents the first case/observation. Multiple but distinct articles for the same case featured the same number appended by a lower-case Roman numeral (e.g., “1a.pdf” and “1b.pdf”). The database, “losses_at_sea_database_10102017.csv”, contains a variable, Files, which associated the given case with its corresponding articles.

By the end of the project, we had collected 250 media reports on 218 discrete boat loss incidents and stored them per best practises in data management. We also catalogued 30 photographs related to these incidents that appeared in reports. Final case and report counts were obtained after quality assurance of all data.

Data Source

As noted, our primary data sources were the media aggregator engines LexisNexis and Factiva; however, we also used search engines. While initial searches focused solely on terms like “migrant boat incident”, we quickly began to identify more robust keywords and phrases in order to create more accurate searches. In attempts to exhaust reports from these sources, we employed multiple search terms and compared our outputs to contemporary data sets. As we analysed the documents, we decided to code additional variables not previously considered. For example, while many reports had estimates of passenger survivals or deaths, it became apparent that they also recorded the number of passengers missing from a loss. Some variables we had sought to record, like ship name, were nearly universally absent from available reports, but were included as missing observations where appropriate. We also found that most incidents featured more than one report, some of which recorded different but important details for the project. As stated, we therefore stored and used multiple reports of the same boat loss or operation for the data sets to enhance the completeness and reliability of the data.

Additional Resources

Original article: Williams, K., & Mountz, A. (2018). Between Enforcement and Precarity: Externalization and Migrant Deaths at Sea. International Migration, 56(5), 74-89.

International Organization for Migration (IOM)’s Missing Migrants Project. This project records since 2014 people who die in the process of migration towards an international destination, regardless of their legal status.

United Nations High Commissioner for Refugees (UNHCR’s) Europe Sea Arrivals. This project records sea arrivals into Europe since 2016, including estimates on dead and missing migrants.

Burroughs, E., & Williams, K (eds.). (2018). Contemporary Migration by Boat: Data, Geopolitics, and Discourses. Rowman & Littlefield International. This book discusses contemporary data sources, politics and narratives surrounding migration by boat, including losses.