Fri, April 19, 2013 | CLA 2.402
Over the last several decades quantitative research on armed conflicts has become increasingly influential for theory building and policy making. However, this strain of research raises numerous ontological and methodological issues that receive relatively little attention from social scientists.
First, much of the research is data-driven. The majority of studies of terrorism and insurgencies rely on a limited number of online databases, which were mostly compiled by journalists or from journalistic sources without rigorous protocols for data collection. Indeed, a comparison between different databases that are aimed at documenting the same phenomenon reveals large discrepancies.
Second, since the data was not collected for a particular study, scholars often are forced to ignore important variables, which could be highly relevant for the testing of their hypotheses, but are not present in the database. In many cases researchers rely on proxy variables in place of more appropriate or accurate variables, as well as on data that is coded at the aggregate (i.e. country), a practice that masks variations across time (i.e. days, months) and space (i.e. local, regional).
Third, due to data availability, the most frequent subject for research on terrorism and counterterrorism is the Arab-Israeli conflict, while Africa serves as the main hub for quantitative analyses of civil wars. Given the focus on statistical analyses, much of the research on conflicts is conducted by scholars with greater knowledge of sophisticated statistical techniques than of the cases under consideration.
The result has been a volume of statistically sophisticated research that lacks solid theoretical and substantive foundations. In many cases, the lack of these pillars along with the limited quality of the data leads to distorted findings, flawed conclusions, and dangerous policy recommendations. This project aims at addressing these problems through the creation of a multidisciplinary research group. We will work together on generating an innovative “high-definition” dataset of the Arab-Israeli conflict from 1936 to present.
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