Bono Made Jesse Helms Cry: Jubilee 2000, Debt Relief, and Moral Action in International Politics

Do states and decision-makers ever act for moral reasons? And if they do, is it only when it is convenient or relatively costless for them to do so? A number of advocacy movementsFon developing country debt relief, climate change, landmines, and other issuesFemerged in the 1990s to ask decision-makers to make foreign policy decisions on that basis. The primary advocates were motivated not by their own material interests but broader notions of right and wrong. What contributes to the domestic acceptance of these moral commitments? Why do some advocacy efforts succeed where others fail? Through a case study of the Jubilee 2000 campaign for developing country debt relief, this article offers an account of persuasion based on strategic framing by advocates to get the attention of decision-makers. Such strategic but not narrowly self-interested activity allows weak actors to leverage existing value and/ or ideational traditions to build broader political coalitions. This article, through case studies of debt relief in the United States and Japan, also links the emerging literature on strategic framing to the domestic institutional context and the ways veto players or ‘‘policy gatekeepers’’ evaluate trade-offs between costs and valuesLBJ School of Public Affair

Hearts or Minds? Persuasive Messages on Climate Change

What kinds of appeals do the public find persuasive for global causes? Are arguments that appeal to so-called rational self-interest more persuasive than those that appeal to morality? Are mixed messages that combine appeals of self-interest with morality more successful than streamlined single themed messages? The causal mechanisms by which transnational advocacy movements are able to generate political support for their campaigns are poorly specified in the literature in international relations and public opinion. This paper explores the relative persuasiveness of advocacy appeals for the issue of climate change. Using an experimental design, this paper reports the results of survey market research of a diverse sample of 360 subjects, each of whom was assigned to one of four conditions, a control condition with no message appeal, an economic self-interest appeal, a secular moral appeal, and a mixed appeal combining self interest and morality. Subjects were then asked a series of questions about their willingness to support advocacy efforts, including such actions as writing a letter to the member of Congress, signing a petition, and joining an organization. We hypothesized that for issues like climate change for which the costs of action are higher and for which there is a more direct cost to individuals or the country, arguments based on economic self-interest are more likely to be persuasive than moral appeals. Where the direct risks or costs to individuals or the country are lower (like the global AIDS crisis), moral messages are more likely to have appeal. For especially religious subjects, however, we hypothesize that moral arguments may be as if not more persuasive even on issues like climate change where the direct costs to the individual or country are likely to be higher.LBJ School of Public Affair

Pandemic disruptions in energy and the environment

Public health measures implemented during the coronavirus pandemic have had significant global impacts on energy systems. Some changes may be ephemeral: as industries go back to work and supply chains relink once production resumes, energy use and emissions have and will continue to rebound. Some may be more durable, such as reductions in commuter and business travel and increases in teleworking. The crisis has exposed the persistent vulnerability of communities of color and those living in poverty, as well as highlighting weaknesses in just-in-time production systems and inequities of supply chains. The social and policy response to the societal impacts of the coronavirus crisis will affect energy systems and the environment in complex and dynamic ways over the long run. Strategic policy responses by nations, communities, organizations, and individuals could go a long way toward reshaping energy systems and impacts on communities and the environment. Here, we highlight themes for continued investigation and research into socioecological interactions between the Great Lockdown and pathways for recovery with a focus on energy systems and the environment

From Imperialism to the "golden Age" to the Great Lockdown: The Politics of Global Health Governance

This article reviews the state of the literature on the politics of global health governance and associated political dynamics of actors involved in this issue space. We identify seven eras in the field, beginning with the period of empire and colonialism and ending with the COVID-19 outbreak. The field of global health has long had a focus on infectious disease, often rooted within a state-centered approach to transnational global health problems with recurrent debates about whether and how restrictions on trade and travel should be imposed in the wake of disease outbreaks. This statist focus is in tension with more cosmopolitan visions of global health, which require broader health system strengthening. In the mid-2000s, a golden age emerged with the influx of new financing and political attention to addressing HIV/AIDS and malaria, as well as reducing the risk posed by infectious disease outbreaks to economies of the Global North. Despite increased awareness of noncommunicable diseases and the importance of health systems, events of recent years (including but not limited to the COVID-19 outbreak) reinforced the centrality of states to global health efforts and the primacy of infectious diseases

Towards Coding Social Science Datasets with Language Models

Researchers often rely on humans to code (label, annotate, etc.) large sets of texts. This kind of human coding forms an important part of social science research, yet the coding process is both resource intensive and highly variable from application to application. In some cases, efforts to automate this process have achieved human-level accuracies, but to achieve this, these attempts frequently rely on thousands of hand-labeled training examples, which makes them inapplicable to small-scale research studies and costly for large ones. Recent advances in a specific kind of artificial intelligence tool - language models (LMs) - provide a solution to this problem. Work in computer science makes it clear that LMs are able to classify text, without the cost (in financial terms and human effort) of alternative methods. To demonstrate the possibilities of LMs in this area of political science, we use GPT-3, one of the most advanced LMs, as a synthetic coder and compare it to human coders. We find that GPT-3 can match the performance of typical human coders and offers benefits over other machine learning methods of coding text. We find this across a variety of domains using very different coding procedures. This provides exciting evidence that language models can serve as a critical advance in the coding of open-ended texts in a variety of applications

AI Chat Assistants can Improve Conversations about Divisive Topics

A rapidly increasing amount of human conversation occurs online. But divisiveness and conflict can fester in text-based interactions on social media platforms, in messaging apps, and on other digital forums. Such toxicity increases polarization and, importantly, corrodes the capacity of diverse societies to develop efficient solutions to complex social problems that impact everyone. Scholars and civil society groups promote interventions that can make interpersonal conversations less divisive or more productive in offline settings, but scaling these efforts to the amount of discourse that occurs online is extremely challenging. We present results of a large-scale experiment that demonstrates how online conversations about divisive topics can be improved with artificial intelligence tools. Specifically, we employ a large language model to make real-time, evidence-based recommendations intended to improve participants' perception of feeling understood in conversations. We find that these interventions improve the reported quality of the conversation, reduce political divisiveness, and improve the tone, without systematically changing the content of the conversation or moving people's policy attitudes. These findings have important implications for future research on social media, political deliberation, and the growing community of scholars interested in the place of artificial intelligence within computational social science

Comprehensive comparative analysis of RNA sequencing methods for degraded or low input samples

RNA-Seq is an effective method to study the transcriptome, but can be difficult to apply to scarce or degraded RNA from fixed clinical samples, rare cell populations, or cadavers. Recent studies have proposed several methods for RNA-Seq of low quality and/or low quantity samples, but their relative merits have not been systematically analyzed. Here, we compare five such methods using metrics relevant to transcriptome annotation, transcript discovery, and gene expression. Using a single human RNA sample, we constructed and sequenced ten libraries with these methods and two control libraries. We find that the RNase H method performed best for low quality RNA, and confirmed this with actual degraded samples. RNase H can even effectively replace oligo (dT) based methods for standard RNA-Seq. SMART and NuGEN had distinct strengths for low quantity RNA. Our analysis allows biologists to select the most suitable methods and provides a benchmark for future method development

Enhanced methods for unbiased deep sequencing of Lassa and Ebola RNA viruses from clinical and biological samples

We have developed a robust RNA sequencing method for generating complete de novo assemblies with intra-host variant calls of Lassa and Ebola virus genomes in clinical and biological samples. Our method uses targeted RNase H-based digestion to remove contaminating poly(rA) carrier and ribosomal RNA. This depletion step improves both the quality of data and quantity of informative reads in unbiased total RNA sequencing libraries. We have also developed a hybrid-selection protocol to further enrich the viral content of sequencing libraries. These protocols have enabled rapid deep sequencing of both Lassa and Ebola virus and are broadly applicable to other viral genomics studies. Electronic supplementary material The online version of this article (doi:10.1186/s13059-014-0519-7) contains supplementary material, which is available to authorized users

Comparative analysis of RNA sequencing methods for degraded or low-input samples

available in PMC 2014 January 01RNA-seq is an effective method for studying the transcriptome, but it can be difficult to apply to scarce or degraded RNA from fixed clinical samples, rare cell populations or cadavers. Recent studies have proposed several methods for RNA-seq of low-quality and/or low-quantity samples, but the relative merits of these methods have not been systematically analyzed. Here we compare five such methods using metrics relevant to transcriptome annotation, transcript discovery and gene expression. Using a single human RNA sample, we constructed and sequenced ten libraries with these methods and compared them against two control libraries. We found that the RNase H method performed best for chemically fragmented, low-quality RNA, and we confirmed this through analysis of actual degraded samples. RNase H can even effectively replace oligo(dT)-based methods for standard RNA-seq. SMART and NuGEN had distinct strengths for measuring low-quantity RNA. Our analysis allows biologists to select the most suitable methods and provides a benchmark for future method development.National Institutes of Health (U.S.) (Pioneer Award DP1-OD003958-01)National Human Genome Research Institute (U.S.) (NHGRI) 1P01HG005062-01)National Human Genome Research Institute (U.S.) (NHGRI Center of Excellence in Genome Science Award 1P50HG006193-01)Howard Hughes Medical Institute (Investigator)Merkin Family Foundation for Stem Cell ResearchBroad Institute of MIT and Harvard (Klarman Cell Observatory)National Human Genome Research Institute (U.S.) (NHGRI grant HG03067)Fonds voor Wetenschappelijk Onderzoek--Vlaandere