Word vectorization is an emerging text-as-data method that shows great promise for automating the analysis of semantics—here, the cultural meanings of words—in large volumes of text. Yet successes with this method have largely been confined to massive corpora where the meanings of words are presumed to be fixed. In political science applications, however, many corpora are comparatively small and many interesting questions hinge on the recognition that meaning changes over time. Together, these two facts raise vexing methodological challenges. Can word vectors trace the changing cultural meanings of words in typical small corpora use cases? I test four time-sensitive implementations of word vectors (word2vec) against a gold standard developed from a modest data set of 161 years of newspaper coverage. I find that one implementation method clearly outperforms the others in matching human assessments of how public dialogues around equality in America have changed over time. In addition, I suggest best practices for using word2vec to study small corpora for time series questions, including bootstrap resampling of documents and pretraining of vectors. I close by showing that word2vec allows granular analysis of the changing meaning of words, an advance over other common text-as-data methods for semantic research questions.

Rapid growth over the past two decades in digitized textual information represents untapped potential for methodological innovations in the adaptation governance literature that draw on machine learning approaches already being applied in other areas of computational social sciences. This Focus Article explores the potential for text mining techniques, specifically topic modeling, to leverage this data for large-scale analysis of the content of adaptation policy documents. We provide an overview of the assumptions and procedures that underlie the use of topic modeling, and discuss key areas in the adaptation governance literature where topic modeling could provide valuable insights. We demonstrate the diversity of potential applications for topic modeling with two examples that examine: (a) how adaptation is being talked about by political leaders in United Nations Framework Convention on Climate Change; and (b) how adaptation is being discussed by decision-makers and public administrators in Canadian municipalities using documents collected from 25 city council archives. This article is categorized under: Vulnerability and Adaptation to Climate Change > Institutions for Adaptation K E Y W O R D S climate change adaptation, governance, policy, quantitative text analysis, topic models 1 | INTRODUCTION Text-based research methods have been a cornerstone of qualitative social science methods since the 1950s (Lasswell, 1952). These approaches see documents as meaningful artifacts that can be analyzed for their thematic and semantic content (Krippendorff, 2013), and they form a core component of the climate change adaptation governance literature. In lieu of directly observable and measurable indicators such as greenhouse gas emissions, adaptation governance research relies on written records, surveys, and interviews as its primary information sources about how different actors are responding to climate change impacts. Content analysis methods are commonly applied to sources such as government reports, strategic planning documents, peer reviewed and gray literature, and media stories (Araos et al.

While recent scholarship has argued for the utility of W. E. B. Du Bois's thought for democratic theory, his career-long emphasis on the problem of social equality-and the solution of self-conscious manhood-has gone largely unnoticed. In this article, I argue that while Du Bois's emphasis on social equality powerfully situates racial oppression as a social and epistemic problem, his solution of self-conscious manhood paradoxically reproduces the very conditions of social inequality he seeks to combat. Open to people of all races, genders, and classes, the path of self-conscious manhood consists in radical truth-telling, a free anarchy of the spirit, a will to strive and act, and the purity of isolation. However, through a close reading of Du Bois's biographies, editorials, and fiction, I show that self-conscious manhood centers an exclusionary and atomized ethic of self-creation rather than producing a democratic political and social order.

Dignity is increasingly central to the justificatory logic of US Supreme Court decisions. Yet the perils inherent in this jurisprudence of dignity, which we argue frames the right to dignity as a right to recognition, have been overlooked. Understanding dignity as synonymous with recognition clarifies its effects: dignity dethrones the autonomous, rights-bearing individual, instead figuring individuals as intersubjectively vulnerable and dependent upon institutional recognition. Dignity also casts state action as innocent, elides structural harms, and exacerbates injuries of marginalization. Applying our theoretical frame to Obergefell v. Hodges, we argue that the effects of the emerging jurisprudence of dignity are troubling.