Abstract
Social movement, civil society, and world polity scholars use counts of nongovernmental organizations (NGOs) to evaluate important theoretical and empirical claims. To construct these measures, researchers often classify NGOs by their goals and/or domains. However, over time, the ways organizations describe and orient themselves change, blurring boundaries between organizations and complicating measurement. In this research note, we identify methodological challenges of organizational classification in the context of our work constructing a longitudinal dataset of transnational social movement organizations. We draw attention to an understudied cause of measurement error: overcounting of organizations. We suggest that as automated methods for classifying data become widespread, devising strategies for dealing with these challenges becomes even more pressing.
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