Band 24, Heft 4 - Proceedings of the 18th Jan Tinbergen European Peace Science Conference

This article reviews the literature on gender, conflict, and peace. In traditional security studies there was not much room for gender or gender equality, while feminist theorists have claimed most of the research on war and peace. The empirical research on gender, conflict, and peace is a relatively new sub-field that brings together diverse traditions from sociology, feminist theory, international relations, and economic development. The common ground of all researchers included in this short review is the effort to systematically understand the role of gender in shaping outcomes of conflict and peace. Despite the increasing number of articles and new datasets, I identify four areas that scholars must address for the research agenda to further grow, deepen, and develop as part of the mainstream study of peace and conflict: women’s status and quality of peace, women’s participation, sexual violence, and gender mainstreaming to promote gender equality in development and peace.

The United Nations Peacemaking Initiatives (UNPI) data compile information on the full range of instruments the UN employs to advance peace and stability. After briefly introducing the data, we will describe how they help us to identify different types of UN peacemaking instruments based on what they aim to achieve (tasks), when they are applied (trends) and to what conflicts (selection).

This paper reports that the econometric findings of Azam & Thelen (2010) remain valid when the sample is extended by 10 years to cover 1990–2014 in Azam & Thelen (2018). They blame the presence of US troops in oil-exporting countries and their neighbors for increasing transnational terrorist attacks by nationals from these countries. They also confirm that foreign aid and educational capital are playing the opposite role by reducing the number of such attacks. The “Obama years” saw a lowered presence of US troops overseas and their smaller marginal impact on transnational terrorism.

Governments and NGOs establish aid projects in order to improve the quality of life for local residents around the world. While recent news stories about aid workers being kidnapped or killed by terrorist groups are alarming, they mask a broader question: Are aid projects effective in promoting humanitarian aims and pacifying the areas to which it is sent? Or, conversely, does their presence actually attract more violence? Although humanitarian assistance is ostensibly non-political, aid projects themselves may make popular targets for terrorist groups. In addition to increasing resources available to plunder, aid provides an appealing foreign target, allowing terrorist groups to reach wider audiences with their attacks and to reinforce the narrative that the government lacks capacity to protect and provide for civilians. In this paper we combine subnational, project-level aid data with newly-assembled subnational data on transnational terrorism to explore terrorist targeting of aid locations. After presenting our matched-sample analysis of terrorist targeting of aid, we outline avenues for future inquiry using high-resolution, subnational data to investigate the strategic vulnerabilities of foreign aid projects.

In this note, we outline a general framework for analyzing how inequality and military spending interact in a society governed by a rent-seeking autocrat. Relying on a general equilibrium model, we show that, generally, the autocrat utilizes the military for redistribution in favor of poorer citizens. However, the dictator’s own rent-seeking activity weakens the extent of redistribution and, in the extreme, can even reverse its direction, yielding more unequal secondary distributions instead. Accordingly, the initial level of inequality also affects the impact of military spending on inequality as the former has an impact on the extent of both, the regime’s rent-seeking activity as well as redistribution. Here, our model shows that primary and secondary distributions are rather equal for extreme initial equality/inequality. For medium levels of initial inequality, redistribution is rather large and can be in favor of the poor or of the rich, depending on the extent of rent-seeking and the primary distribution. Based on these results, we highlight the importance of a society’s institutional framework for analyzing the relation of inequality and military spending.

Sentiment, judgments and expressed positions are crucial concepts across international relations and the social sciences more generally. Yet, contemporary quantitative research has conventionally avoided the most direct and nuanced source of this information: political and social texts. In contrast, qualitative research has long relied on the patterns in texts to understand detailed trends in public opinion, social issues, the terms of international alliances, and the positions of politicians. Yet, qualitative human reading does not scale to the accelerating mass of digital information available currently. Researchers are in need of automated tools that can extract meaningful opinions and judgments from texts. Thus, there is an emerging opportunity to marry the model-based, inferential focus of quantitative methodology, as exemplified by ideal point models, with high resolution, qualitative interpretations of language and positions. We suggest that using alternatives to simple bag of words (BOW) representations and re-focusing on aspect-sentiment representations of text will aid researchers in systematically extracting people’s judgments and what is being judged at scale. The experimental results below show that our approach which automates the extraction of aspect and sentiment MWE pairs, outperforms BOW in classification tasks, while providing more interpretable parameters. By connecting expressed sentiment and the aspects being judged, PULSAR (Parsing Unstructured Language into Sentiment-Aspect Representations) also has deep implications for understanding the underlying dimensionality of issue positions and ideal points estimated with text. Our approach to parsing text into aspects-sentiment expressions recovers both expressive phrases (akin to categorical votes), as well as the aspects that are being judged (akin to bills). Thus, PULSAR or future systems like it, open up new avenues for the systematic analysis of high-dimensional opinions and judgments at scale within existing ideal point models.

This paper highlights how machine learning can help explain terrorism. We note that even though machine learning has a reputation for black box prediction, in fact, it can provide deeply nuanced explanations of terrorism. Moreover, machine learning is not sensitive to the sometimes heroic statistical assumptions necessary when parametric econometrics is applied to the study of terrorism. This increases the reliability of explanations while adding contextual nuance that captures the flavor of individualized case analysis. Nevertheless, this approach also gives us a sense of the replicability of results. We, therefore, suggest that it further expands the role of science in terrorism research.

Despite raising fears over the use of states’ cyber capabilities as a tool of foreign policy, little empirical evidence is provided about its actual diffusion. Using a newly developed dataset collecting information on cyber interactions between rival states from 2000 to 2014, I analyse the evolution of the network of cyber incidents over the considered period by the mean of a Social Network Analysis approach. Results show that the level of cohesion in the network is low and the number of countries which does not make use of cyber tactics is high. Furthermore, Russia is emerging as the major offender while the USA is the most attacked country. Finally, geography appears to be a driving factor in influencing links formation.

In this paper, we focus on mediation in intrastate conflicts, specifically on the impact of rebel group goals on the prospects for mediation. We ask whether the goals for which rebel groups fight (i.e. secession, irredentism, autonomy, greater political rights, government overthrow) have an impact on the likelihood that these conflicts will be mediated. We test our hypotheses on a new data set of rebel groups in Africa 1962–2010.