Charles Crabtree

Human Rights Texts: Converting Human Rights Primary Source Documents into Data

We introduce and make publicly available a large corpus of digitized primary source human rights documents which are published annually by monitoring agencies that include Amnesty International, Human Rights Watch, the Lawyers Committee for Human Rights, and the United States Department of State. In addition to the digitized text, we also make available and describe document-term matrices, which are datasets that systematically organize the word counts from each unique document by each unique term within the corpus of human rights documents. To contextualize the importance of this corpus, we describe the development of coding procedures in the human rights community and several existing categorical indicators that have been created by human coding of the human rights documents contained in the corpus. We then discuss how the new human rights corpus and the existing human rights datasets can be used with a variety of statistical analyses and machine learning algorithms to help scholars understand how human rights practices and reporting have evolved over time. We close with a discussion of our plans for dataset maintenance, updating, and availability.

Uncovering Patterns Among Latent Variables: Human Rights and De Facto Judicial Independence

In this paper, we reexamine the relationship between judicial independence and state respect for human rights by taking advantage of new latent measures of both constructs. In our analysis, we demonstrate a simple method for incorporating the uncertainty of these latent variables. Our results provide strong support for theoretical and empirical claims that independent courts constrain human rights abuses. Although we show that independent courts influence state behavior, the strength of the estimated relationship depends upon whether and to what degree empirical models account for uncertainty in the measurement of the latent variables.

Party System Volatility in Post-Communist Europe

In their 2014 article in the British Journal of Political Science, Eleanor Neff Powell and Joshua A. Tucker examine the determinants of party system volatility in post-communist Europe. Their central conclusion is that replacement volatility – volatility caused by new party entry and old party exit – is driven by long-term economic performance. We show that this conclusion is based entirely on a miscalculation of the long-term economic performance of a single country, Bosnia-Herzegovina. Our reanalysis suggests that we know little about what causes party system volatility in post-communist Europe. Given the negative consequences traditionally associated with party system volatility, this area of research cries out for new theoretical development.

An Introduction to Conducting Email Audit Studies

This chapter offers the first general introduction to conducting email audit studies. It provides an overview of the steps involved from experimental design to empirical analysis. It then offers detailed recommendations about email address collection, email delivery, and email analysis, which are usually the three most challenging points of an audit study. The focus here is on providing a set of primarily technical recommendations to researchers who might want to conduct an email audit study. The chapter concludes by suggesting several ways that email audit studies can be adapted to investigate a broader range of social phenomena.

It's All About Race: How State Legislators Respond to Immigrant Constituents

How do elected representatives respond to the needs of immigrant constituents? We report the results of a field experiment on U.S. state legislators in which the nativity, likelihood of voting, and race/ethnicity of a hypothetical constituent are independently manipulated. The experimental design allows us to contribute new insights by isolating the various elements that may impede the connection between immigrants and elected representatives. Moreover, we explore racial/ethnic identities beyond black and white, by including Latino and Asian aliases. Contrary to expectations, nativity and voting status do not affect responsiveness. Instead, legislator behavior appears to be driven by racial/ethnic bias. Whites benefit from the highest degree of responsiveness, with blacks, Hispanics, and Asians all receiving lower response rates, respectively. This bias follows a partisan logic. Hispanic constituents receive lower responsiveness primarily from Republican legislators, while Asians experience discrimination from representatives of both parties. We argue that this difference may result from Hispanic identity sending a stronger signal about partisan affiliation, or from a prejudicial view of Asians as outsiders. In this interpretation, rather than the model minority, Asians become the excluded minority.

Truth Replaced by Silence: A Field Experiment on Private Censorship in Russia

Through highly visible acts of repression, authoritarian regimes can send informative signals to private actors about what types of speech are off-limits and might draw the punitive attention of the state. These acts not only encourage private actors to censor themselves but also to censor other private actors, a behavior we refer to as regime-induced private censorship. Our paper is the first to provide systematic empirical evidence on the extent and targets of such censorship behavior. We use a field experiment conducted throughout the Russian Federation in September 2014 to investigate the private censorship behavior of private media firms. The results suggest that private actors censor the messages of other private actors when those messages include anti-regime language, calls for collective action, or both. These results are partially consistent with previous empirical findings in that they show that private actors censor content with a collective action appeal even when the message itself is non-political. Our results, however, build upon previous work by showing that anti-regime messages that do not contain a call for collective action are still censored under some authoritarian regimes. Our results highlight the importance of forms of censorship other than state censorship when discussing repression, dissent, and public opinion formation in authoritarian regimes.

Using Google Trends to Measure Issue Salience for Hard-to-Survey Populations

Some populations are difficult to survey. This poses a problem for researchers who want to understand what issues matter to these populations and how the salience of those concerns varies over time. In this visualization article, the authors illustrate how Google Trends can be used to examine issue salience for hard-to-survey mass populations. Applying this method to immigrant concerns over deportation, the authors show that anxieties over removal increased in response to (potential) policy changes, such as Arizona’s Support Our Law Enforcement and Safe Neighborhoods Act (Senate Bill 1070) and the immigration policies that were considered in the wake of Donald Trump’s election.

It’s all about race : how State legislators respond to immigrant constituents.

How do elected representatives respond to the needs of immigrant constituents? We report the results of a field experiment on U.S. state legislators in which the nativity, likelihood of voting, and race/ethnicity of a hypothetical constituent are independently manipulated. The experimental design allows us to contribute new insights by isolating the various elements that may impede the connection between immigrants and elected representatives. Moreover, we explore racial/ethnic identities beyond black and white by including Latino and Asian aliases. Contrary to expectations, nativity and voting status do not affect response rates. Instead, legislator behavior appears to be driven by racial/ethnic bias. Whites benefit from the highest response rate, while blacks, Hispanics, and Asians all receive lower rates, respectively. This bias follows a partisan logic. The low response rate for Hispanic constituents comes primarily from Republican legislators, whereas Asians experience bias from representatives of both parties. We argue that this difference may result from Hispanic identity sending a stronger signal about partisan affiliation, or from a prejudicial view of Asians as outsiders. In this last interpretation, rather than the model minority, Asians become the excluded minority.

Plotrr: Functions for making visual exploratory data analysis with nested data easier.

plotrr helps address this issue by providing several functions that make visual EDA easier to conduct. The focus of many of the package’s functions is to create plots that can help researchers explore relationships within nested data. Among other things, these functions can help scholars assess the extent to which expected relationships between variables occur in specific cases. bivarplots creates a bivariate plot for every group/unit in the data, dotplots creates a dot plot for every group/unit, and violinplots creates a violin plot for every group/unit.