The Department of Government
The Department of Government

International Relations Workshop- Tana Johnson (Duke Univ)

“At the Nexus of Environmental Policy and Trade Policy: Textual Analysis Using Machine Learning”

Wed, April 24, 2019 | BAT 5.108

12:30 PM - 2:00 PM

 Abstract: Inter-governmental organizations (IGOs) face numerous challenges.  Many deal with more than one policy area, include states that are equal in sovereignty but quite unequal in characteristics such as development level, and involve emerging economies that have grown richer rapidly.  For these and other reasons, it can be difficult to deductively predict what various states will do in international fora.  We show how more inductive, machine-learning techniques can help.  With 3,678 paragraphs of government statements made between 1995 and 2012 in negotiations at the nexus of environmental and trade policy within the World Trade Organization (WTO), we use text as data to answer three questions: 1) which topics are states discussing? 2) are some topics strongly associated with poorer states, and others with richer states?  3) as the “BASIC” states of Brazil, South Africa, India, and China have grown richer since the 1990s, have they increased or decreased their emphasis on particular topics?  This produces three findings that are likely to hold in other IGO contexts – but are unlikely to be revealed by purely deductive approaches.  First, institutional mandates can be incomplete, or even misleading, for anticipating what states actually discuss.  Second, some (but not all) discussions are correlated with characteristics of the speakers themselves.  Third, the BASIC states are not moving in lockstep.  We demonstrate the promise – and detail the process – of using computer-assisted approaches to investigate the numerous IR research contexts in which theoretical expectations are opaque or incomplete.

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