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Native Americans are unique among domestic actors in that their relations with the U.S. government involve treaty making, with almost 600 such documents signed between the Revolutionary War and the turn of the twentieth century. We investigate the effect of constitutional changes to the treating process in 1871, by which Congress stripped the president of his ability to negotiate directly with tribes. We construct a comprehensive new data set by digitizing all of the treaties for systematic textual analysis. Employing scaling techniques validated with word-use information, we show that a single dimension characterizes the treaties as more or less "harsh" in land and resource cession terms. We find that specific institutional changes to treaty-making mechanisms had little effect on agreement outcomes. Rather, it is the relative bargaining power of the United States economically and militarily that contributes to worsening terms for Indians over the nineteenth century. Adapted from the source document.

Limited dependent variable (LDV) data are common in political science, and political methodologists have given much good advice on dealing with them. We review some methods for LDV "change point problems" and demonstrate the use of Bayesian approaches for count, binary, and duration-type data. Our applications are drawn from American politics, Comparative politics, and International Political Economy. We discuss the tradeoffs both philosophically and computationally. We conclude with possibilities for multiple change point work.

Measuring the polarization of legislators and parties is a key step in understanding how politics develops over time. But in parliamentary systems—where ideological positions estimated from roll calls may not be informative—producing valid estimates is extremely challenging. We suggest a new measurement strategy that makes innovative use of the "accuracy" of machine classifiers, i.e., the number of correct predictions made as a proportion of all predictions. In our case, the "labels" are the party identifications of the members of parliament, predicted from their speeches along with some information on debate subjects. Intuitively, when the learner is able to discriminate members in the two main Westminster parties well, we claim we are in a period of "high" polarization. By contrast, when the classifier has low accuracy—and makes a relatively large number of mistakes in terms of allocating members to parties based on the data—we argue parliament is in an era of "low" polarization. This approach is fast and substantively valid, and we demonstrate its merits with simulations, and by comparing the estimates from 78 years of House of Commons speeches with qualitative and quantitative historical accounts of the same. As a headline finding, we note that contemporary British politics is approximately as polarized as it was in the mid-1960s—that is, in the middle of the "postwar consensus". More broadly, we show that the technical performance of supervised learning algorithms can be directly informative about substantive matters in social science.

International audience ; Measuring the polarization of legislators and parties is a key step in understanding how politics develops over time. But in parliamentary systems-where ideological positions estimated from roll calls may not be informative-producing valid estimates is extremely challenging. We suggest a new measurement strategy, that makes innovative use of the 'accuracy' of machine classifiers, i.e. the number of correct predictions made as a proportion of all predictions. In our case, the 'labels' are the party identifications of the members of parliament, predicted from their speeches, along with some information on debate subjects. Intuitively, when the learner is able to discriminate members in the two main Westminster parties well, we claim we are in a period of 'high' polarization. By contrast, when the classifier has low accuracy-and makes a relatively large number of mistakes in terms of allocating members to parties based on the data-we argue parliament is in an era of 'low' polarization. This approach is fast and substantively valid, and we demonstrate its merits with simulations, and by comparing the estimates from 78 years of House of Commons speeches with qualitative and quantitative historical accounts of the same. As a headline finding, we note that contemporary British politics is approximately as polarized as it was in the mid-1960s-that is, in the middle of the 'post-war consensus'. More broadly, we show that the technical performance of supervised learning algorithms can be directly informative about substantive matters in social science. ; Mesurer la polarisation des législateurs et des partis est une étape clé pour comprendre comment la politique évolue au fil du temps. Mais dans des systèmes parlementaires - où les positions idéologiques estimées à partir d'appels nominaux sont possiblement moins révélatrices - produire des estimations valides est extrêmement difficile. Nous proposons une nouvelle stratégie de mesure qui utilise de manière innovante la précision des ...

In November 2010, the WikiLeaks organization began the release of over 250,000 diplomatic cables sent by U.S. embassies to the U.S. State Department, uploaded to its website by (then) Private Manning, an intelligence analyst with the U.S. Army. This leak was widely condemned, including by then Secretary of State Hillary Clinton. We assess the severity of the leak by considering the size of the disclosure relative to all diplomatic cables that were in existence at the time—a quantity that is not known outside official sources. We rely on the fact that the cables that were leaked are internally indexed in such a way that they may be treated as a sample from a discrete uniform distribution with unknown maximum; this is a version of the well-known "German Tank Problem." We consider three estimators that rely on discrete uniformity—maximum likelihood, Bayesian, and frequentist unbiased minimum variance—and demonstrate that the results are very similar in all cases. To supplement these estimators, we employ a regression-based procedure that incorporates the timing of cables' release in addition to their observed serial numbers. We estimate that, overall, approximately 5% of all cables from this timeframe were leaked, but that this number varies considerably at the embassy-year level. Our work provides a useful characterization of the sample of documents available to international relations scholars interested in testing theories of "private information," while helping inform the public debate surrounding Manning's trial and 35-year prison sentence.