There is an ongoing debate about whether human rights standards have changed over the last 30 years. The evidence for or against this shift relies upon indicators created by human coders reading the texts of human rights reports. To help resolve this debate, we suggest translating the question of changing standards into a supervised learning problem. From this perspective, the application of consistent standards over time implies a time-constant mapping from the textual features in reports to the human coded scores. Alternatively, if the meaning of abuses have evolved over time, then the same textual features will be labeled with different numerical scores at distinct times. Of course, while the mapping from natural language to numerical human rights score is a highly complicated function, we show that these two distinct data generation processes imply divergent overall patterns of accuracy when we train a wide variety of algorithms on older versus newer sets of observations to learn how to automatically label texts with scores. Our results are consistent with the expectation that standards of human rights have changed over time.
This manuscript helps to resolve the ongoing debate concerning the effect of information communication technology on human rights monitoring. We reconceptualize human rights as a taxonomy of nested rights that are judged in textual reports and argue that the increasing density of available information should manifest in deeper taxonomies of human rights. With a new automated system, using supervised learning algorithms, we are able to extract the implicit taxonomies of rights that were judged in texts by the US State Department, Amnesty International, and Human Rights Watch over time. Our analysis provides new, clear evidence of change in the structure of these taxonomies as well as in the attention to specific rights and the sharpness of distinctions between rights. Our findings bridge the natural language processing and human rights communities and allow a deeper understanding of how changes in technology have affected the recording of human rights over time.
How do we measure religious violence? This study is focused on utilizing new methodological approaches and data sources to measure religiously motivated violence. Previous attempts to measure religious violence concentrated on coding U.S. State Department International Religious Freedom reports or utilizing existing datasets on armed conflict/civil wars. These previous attempts provided state-level data of the levels of religiously motivated violence, but due to data limitations cannot provide more fine-grained measures of specific acts of violence tied to religious motivation. In particular, accounting for varying levels of intensity especially in regards to non-lethal acts of religiously motivated violence is missing. This study builds upon previous attempts focusing on the creation of more fine-grained measures and accounting for its variation at the sub-national level utilizing natural language processing. The data generated are used to examine incidences of reported religious violence in India from 2000 to 2015.
How does the discussion of human rights issues change over time? Without advocates adopting a human rights issue in the first place, international ‘shaming’ cannot occur. In this article, we examine how human rights discussions converge and diverge around new frames and new issues over time. Human rights norms do not evolve alone; their prevalence, framing, and focus are all dependent on how they relate to other norms in the advocacy community. Drawing on over 30,000 documents from dozens of human rights organizations from 1990 to 2011, we provide a temporal overview and visualization of the ebb and flow of human rights issues. Using our new dataset and state-of-the-art methods from computer science, our approach allows us to quantitatively examine (a) how new issues emerge in the advocacy network, (b) the relationship of these new issues to extant human rights advocacy and information, and (c) how the framing and specificity of these issues change over time. By focusing on the process by which a new issue gets incorporated into the work of advocates, we provide an empirical assessment of the first step in the causal process connecting shaming to improvement in human rights practices.
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