@article{JankinBaturo, author = {Jankin, Slava and Baturo, Alexander}, title = {Blair Disease? Business Careers of the Former Democratic Heads of State and Government}, series = {Public Choice}, volume = {166}, journal = {Public Choice}, number = {3-4}, issn = {0048-5829}, doi = {10.1007/s11127-016-0325-8}, pages = {335 -- 354}, abstract = {Examining the careers of democratic heads of state and government from 1960-2010, we find that one in every seven turns to the private sector after office. Distinguishing between the factors that attract leaders to business and those that render leaders attractive, we find that the global CEO compensation rates, cultural norms, having served in office in Anglo-Saxon countries as well as their personal background, matter. We also find that certain economic outcomes and policies in office such as economic growth and reduction in state spending are often associated with post-tenure business careers. We do not find evidence, however, that leaders are able to implement policies with future careers in mind, which would in turn raise concerns over accountability.}, language = {en} } @article{JankinBenoitConwayetal., author = {Jankin, Slava and Benoit, Kenneth and Conway, Drew and Laver, Michael}, title = {Crowd-Sourced Text Analysis: Reproducible and agile production of political data}, series = {American Political Science Review}, volume = {110}, journal = {American Political Science Review}, number = {2}, issn = {0003-0554}, doi = {10.1017/S0003055416000058}, pages = {278 -- 295}, abstract = {Empirical social science often relies on data that are not observed in the field, but are transformed into quantitative variables by expert researchers who analyze and interpret qualitative raw sources. While generally considered the most valid way to produce data, this expert-driven process is inherently difficult to replicate or to assess on grounds of reliability. Using crowd-sourcing to distribute text for reading and interpretation by massive numbers of non-experts, we generate results comparable to those using experts to read and interpret the same texts, but do so far more quickly and flexibly. Crucially, the data we collect can be reproduced and extended transparently, making crowd-sourced datasets intrinsically reproducible. This focuses researchers' attention on the fundamental scientific objective of specifying reliable and replicable methods for collecting the data needed, rather than on the content of any particular dataset. We also show that our approach works straightforwardly with different types of political text, written in different languages. While findings reported here concern text analysis, they have far-reaching implications for expert-generated data in the social sciences.}, language = {en} } @article{JankinBaturoDasandi, author = {Jankin, Slava and Baturo, Alexander and Dasandi, Niheer}, title = {Understanding State Preferences With Text As Data: Introducing the UN General Debate Corpus}, series = {Research \& Politics}, volume = {4}, journal = {Research \& Politics}, number = {2}, doi = {10.1177/2053168017712821}, abstract = {Every year at the United Nations (UN), member states deliver statements during the General Debate (GD) discussing major issues in world politics. These speeches provide invaluable information on governments' perspectives and preferences on a wide range of issues, but have largely been overlooked in the study of international politics. This paper introduces a new dataset consisting of over 7300 country statements from 1970-2014. We demonstrate how the UN GD corpus (UNGDC) can be used as a resource from which country positions on different policy dimensions can be derived using text analytic methods. The article provides applications of these estimates, demonstrating the contribution the UNGDC can make to the study of international politics.}, language = {en} } @techreport{HerzogJankin, type = {Working Paper}, author = {Herzog, Alexander and Jankin, Slava}, title = {Database of Parliamentary Speeches in Ireland, 1919-2013}, series = {IEEE Proceedings of the 2017 International Conference on the Frontiers and Advances in Data Science (FADS)}, journal = {IEEE Proceedings of the 2017 International Conference on the Frontiers and Advances in Data Science (FADS)}, doi = {10.1109/FADS.2017.8253189}, pages = {29 -- 34}, abstract = {We present a database of parliamentary debates that contains the complete record of parliamentary speeches from D{\´a}il {\´E}ireann, the lower house and principal chamber of the Irish parliament, from 1919 to 2013. In addition, the database contains background information on all TDs (Teachta D{\´a}la, members of parliament), such as their party affiliations, constituencies and office positions. The current version of the database includes close to 4.5 million speeches from 1,178 TDs. The speeches were downloaded from the official parliament website and further processed and parsed. Background information on TDs was collected from the member database of the parliament website. Data on cabinet positions (ministers and junior ministers) was collected from the official website of the government. A record linkage algorithm and human coders were used to match TDs and ministers.}, language = {en} } @techreport{GurciulloJankin, type = {Working Paper}, author = {Gurciullo, Stefano and Jankin, Slava}, title = {Detecting Policy Preferences and Dynamics in the UN General Debate with Neural Word Embeddings}, series = {IEEE Proceedings of the 2017 International Conference on the Frontiers and Advances in Data Science (FADS)}, journal = {IEEE Proceedings of the 2017 International Conference on the Frontiers and Advances in Data Science (FADS)}, doi = {10.1109/FADS.2017.8253197}, pages = {74 -- 79}, abstract = {Foreign policy analysis has been struggling to find ways to measure policy preferences and paradigm shifts in international political systems. This paper presents a novel, potential solution to this challenge, through the application of a neural word embedding (Word2vec) model on a dataset featuring speeches by heads of state or government in the United Nations General Debate. The paper provides three key contributions based on the output of the Word2vec model. First, it presents a set of policy attention indices, synthesizing the semantic proximity of political speeches to specific policy themes. Second, it introduces country-specific semantic centrality indices, based on topological analyses of countries' semantic positions with respect to each other. Third, it tests the hypothesis that there exists a statistical relation between the semantic content of political speeches and UN voting behavior, falsifying it and suggesting that political speeches contain information of different nature then the one behind voting outcomes. The paper concludes with a discussion of the practical use of its results and consequences for foreign policy analysis, public accountability, and transparency.}, language = {en} } @article{JankinWattsAmannetal., author = {Jankin, Slava and Watts, Nick and Amann, Markus and Ayeb-Karlsson, Sonja and Belesova, Kristine and Bouley, Timothy and Boykoff, Maxwell and Byass, Peter and Cai, Wenjia and Campbell-Lendrum, Diarmid and Chambers, Jonathan and Cox, Peter M and Daly, Meaghan and Dasandi, Niheer and Davies, Michael and Depledge, Michael and Depoux, Anneliese and Dominguez-Salas, Paula and Drummond, Paul and Ekins, Paul and Flathault, Antoine and Frumkin, Howard and Georgeson, Lucien and Ghanei, Mostafa and Grace, Delia and Graham, Hilary and Grojsman, R{\´e}becca and Haines, Andy and Hamilton, Ian and Hartinger, Stella and Johnson, Anne and Kelman, Ilan and Kiesewetter, Gregor and Kniveton, Dominic and Liang, Lu and Lott, Melissa and Lowe, Robert and Mace, Georgina and Sewe, Maquins Odhiambo and Maslin, Mark and Milner, James and Latifi, Ali Mohammad and Moradi-Lakeh, Maziar and Morrissey, Karyn and Murray, Kris and Neville, Tara and Nilsson, Maria and Oreszczyn, Tadj and Owfi, Fereidoon and Pencheon, David and Pye, Steve and Rabbaniha, Mahnaz and Robinson, Elizabeth and Rockl{\"o}v, Joacim and Sch{\"u}tte, Stefanie and Shumake-Guillemot, Joy and Steinbach, Rebecca and Tabatabaei, Meisam and Wheeler, Nicola and Wilkinson, Paul and Gong, Peng and Montgomery, Hugh and Costello, Anthony}, title = {The Lancet countdown on health and climate change: from 25 years of inaction to a global transformation for public health}, series = {The Lancet}, volume = {391}, journal = {The Lancet}, number = {10120}, doi = {10.1016/S0140-6736(17)32464-9}, pages = {581 -- 630}, abstract = {The Lancet Countdown tracks progress on health and climate change and provides an independent assessment of the health effects of climate change, the implementation of the Paris Agreement, and the health implications of these actions. It follows on from the work of the 2015 Lancet Commission on Health and Climate Change, which concluded that anthropogenic climate change threatens to undermine the past 50 years of gains in public health, and conversely, that a comprehensive response to climate change could be "the greatest global health opportunity of the 21st century".}, language = {en} } @article{JankinPenchevaEsteve, author = {Jankin, Slava and Pencheva, Irina and Esteve, Marc}, title = {Big Data \& AI - A Transformational Shift for Government: So, What Next for Research?}, series = {Public Policy and Administration}, journal = {Public Policy and Administration}, doi = {10.1177/0952076718780537}, pages = {1 -- 21}, abstract = {Big Data and Artificial Intelligence will have a profound transformational impact on governments around the world. Thus, it is important for scholars to provide a useful analysis on the topic to public managers and policymakers. This study offers an in-depth review of the Policy and Administration literature on the role of Big Data and advanced analytics in the public sector. It provides an overview of the key themes in the research field, namely the application and benefits of Big Data throughout the policy process, and challenges to its adoption and the resulting implications for the public sector. It is argued that research on the subject is still nascent and more should be done to ensure that the theory adds real value to practitioners. A critical assessment of the strengths and limitations of the existing literature is developed, and a future research agenda to address these gaps and enrich our understanding on the topic is proposed.}, language = {en} } @article{JankinEsteveCampion, author = {Jankin, Slava and Esteve, Marc and Campion, Averill}, title = {Artificial intelligence for the public sector: opportunities and challenges of cross-sector collaboration}, series = {Philosophical Transactions of the Royal Society A}, volume = {376}, journal = {Philosophical Transactions of the Royal Society A}, number = {2128}, doi = {10.1098/rsta.2017.0357}, abstract = {Public sector organizations are increasingly interested in using data science and artificial intelligence capabilities to deliver policy and generate efficiencies in high uncertainty environments. The long-term success of data science and artificial intelligence (AI) in the public sector relies on effectively embedding it into delivery solutions for policy implementation. However, governments cannot do this integration of AI into public service delivery on their own. The UK Government Industrial Strategy is clear that delivering on the AI grand challenge requires collaboration between universities and public and private sectors. This cross-sectoral collaborative approach is the norm in applied AI centres of excellence around the world. Despite their popularity, cross-sector collaborations entail serious management challenges that hinder their success. In this article we discuss the opportunities and challenges from AI for public sector. Finally, we propose a series of strategies to successfully manage these cross-sectoral collaborations.}, language = {en} } @article{JankinWattsAmannetal., author = {Jankin, Slava and Watts, Nick and Amann, Markus and et al.,}, title = {The 2018 report of the Lancet Countdown on health and climate change: shaping the health of nations for centuries to come}, series = {The Lancet}, volume = {392}, journal = {The Lancet}, number = {10163}, issn = {0140-6736}, doi = {10.1016/S0140-6736(18)32594-7}, pages = {2479 -- 2514}, abstract = {The Lancet Countdown: tracking progress on health and climate change was established to provide an independent, global monitoring system dedicated to tracking the health dimensions of the impacts of, and the response to, climate change. The Lancet Countdown tracks indicators across five domains: climate change impacts, exposures, and vulnerability; adaptation, planning, and resilience for health; mitigation actions and health co-benefits; finance and economics; and public and political engagement. This report is the product of a collaboration of 27 leading academic institutions, the UN, and intergovernmental agencies from every continent. The report draws on world-class expertise from climate scientists, ecologists, mathematicians, geographers, engineers, energy, food, livestock, and transport experts, economists, social and political scientists, public health professionals, and doctors. The Lancet Countdown's work builds on decades of research in this field, and was first proposed in the 2015 Lancet Commission on health and climate change,1 which documented the human impacts of climate change and provided ten global recommendations to respond to this public health emergency and secure the public health benefits available.}, language = {en} } @article{CarmodyDasandiJankin, author = {Carmody, P{\´a}draig and Dasandi, Niheer and Jankin, Slava}, title = {Power Plays and Balancing Acts: The Paradoxical Effects of Chinese Trade on African Foreign Policy Positions}, series = {Political Studies}, journal = {Political Studies}, doi = {10.1177/0032321719840962}, abstract = {There has been substantial focus on China's influence in Africa in recent years. Some argue that China's growing economic ties with African states have increased its political influence across the continent. This article examines whether trade with China leads African states to adopt more similar foreign policy preferences to China in the United Nations. We examine foreign policy similarity using voting patterns in the United Nations General Assembly and country statements in the United Nations General Debate. The analysis demonstrates that more trade with China has paradoxical effects on foreign policy positions of African states—it leads them to align more closely with US foreign policy positions in the United Nations, except on human rights votes. Our findings suggest that African states are engaged in balancing behavior with external powers whereby African elites seek to play off rival powers against one another in order to strengthen their own autonomy and maximize trade.}, language = {en} } @article{MunzertJankinal, author = {Munzert, Simon and Jankin, Slava and al., et}, title = {The 2019 report of The Lancet Countdown on health and climate change: ensuring that the health of a child born today is not defined by a changing climate}, series = {The Lancet}, volume = {394}, journal = {The Lancet}, number = {10211}, doi = {10.1016/S0140-6736(19)32596-6}, pages = {1836 -- 1878}, abstract = {The Lancet Countdown is an international, multidisciplinary collaboration, dedicated to monitoring the evolving health profile of climate change, and providing an independent assessment of the delivery of commitments made by governments worldwide under the Paris Agreement.}, language = {en} } @article{PomeroyDasandiJankin, author = {Pomeroy, Caleb and Dasandi, Niheer and Jankin, Slava}, title = {Multiplex communities and the emergence of international conflict}, series = {PLoS One}, volume = {14}, journal = {PLoS One}, number = {10}, doi = {10.1371/journal.pone.0223040}, abstract = {Advances in community detection reveal new insights into multiplex and multilayer networks. Less work, however, investigates the relationship between these communities and outcomes in social systems. We leverage these advances to shed light on the relationship between the cooperative mesostructure of the international system and the onset of interstate conflict. We detect communities based upon weaker signals of affinity expressed in United Nations votes and speeches, as well as stronger signals observed across multiple layers of bilateral cooperation. Communities of diplomatic affinity display an expected negative relationship with conflict onset. Ties in communities based upon observed cooperation, however, display no effect under a standard model specification and a positive relationship with conflict under an alternative specification. These results align with some extant hypotheses but also point to a paucity in our understanding of the relationship between community structure and behavioral outcomes in networks.}, language = {en} } @techreport{DasandiJankin, type = {Working Paper}, author = {Dasandi, Niheer and Jankin, Slava}, title = {AI for SDG-16 on Peace, Justice, and Strong Institutions: Tracking Progress and Assessing Impact}, pages = {3}, abstract = {The transition from the Millennium Development Goals (MDGs) to the Sustainable Development Goals (SDGs) brought with it significant changes in the process of creating the goals and with the actual content of the SDGs. One of the most important developments was the inclusion of SDG 16, which recognises the central role of effective, accountable and inclusive political institutions in promoting sustainable development. Yet, a significant shortcoming is the difficulty in measuring progress on this SDG 16. In addition to general issues linked with data availability across the various indicators, a key challenge is aggregating trends across these wide-ranging indicators to track overall progress on SDG 16. A second issue that follows, is that despite claims regarding the centrality of SDG 16 for achieving the other SDGs, little is known about the causal pathways from the different indicators in SDG 16 to the other SDGs and associated indicators. In other words, questions remain over how changes in SDG 16 indicators impact a country's progress towards indicators linked to health, gender equality, water and sanitation, and climate change.}, language = {de} }