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Abstract
Sunni Muslims in Kachchh, Gujarat commemorate the Islamic month of Muharram with a variety of practices, including street processions, drumming, musical stage performances, dancing, and dhamāl (piercing the body with skewers and daggers). This article focuses on osāṇī (<ḥusainī), a song genre that is only performed during Muharram and serves as the musical foundation of the osāṇī circle dance. Osāṇī dance is noteworthy for its incorporation of a stylized form of hāth kā mātam, the chest-beating typically associated with Shiʿa Muslims' lamentation for the Karbala martyrs, which is generally avoided and criticized by Sunnis in other areas of South Asia. Drawing attention to the affectively mixed quality of osāṇī performances, I underscore the role of maza (enjoyment, fun) in the religious life of Muslim Kachchh, thus offering a counterbalance to the focus on valorized affects that has characterized recent influential studies of self-formation and embodied religious devotion in Muslim societies. Finally, the article traces the impact of Islamic reformism, which has prompted many Sunnis associated with the Ahl-e Sunnat wa Jamaʿat ("Barelvī") movement to refrain from participating in osāṇī and other forms of Muharram commemoration over the past few decades.

Emergence of a new infectious disease out of China has caused a global reaction to combat the spread. On December 31, 2019, China reported a cluster of cases of pneumonia in people associated with the Huanan Seafood Wholesale Market in Wuhan, Hubei Province. On January 7, 2020, Chinese health authorities confirmed that this cluster was associated with a novel coronavirus, 2019-nCoV. Governments around the world responded to the threat by instituting lockdowns, closing businesses, using experimental medications, and even closing boarders. Citizens responded in kind by increasing social distancing and the usage of personal protective devices such as face masks and gloves. With past concerns such as SARS 2002-2003, Swine Flu 2009, Zika Virus 2015, and Ebola 2018 outbreaks, what is different? Although cases were originally reported to be associated with exposure to the seafood market in Wuhan, current epidemiologic data indicate that person-to-person transmission of 2019-nCoV is occurring. Despite efforts to curb the spread of the disease it has become a global pandemic with 2,982.688 cases across the globe as of April 28, 2020. An evaluation of each step must be performed to determine what has been successful and to avoid repeating any past failures. Comparative studies have been completed on the different measures each country instituted. Wading through endless news reports and information portals can only compound to the confusion. Evaluating exposure rates, how accurate information is spread, and what helped to flatten the curve in areas around the world are key in preventing another global pandemic from spreading so rapidly.

The discipline of public health informatics, part of the broader eHealth field, brings methods, knowledge, and theories from computer science and information science to support population health and well-being. This branch of informatics is most often found in governmental public health agencies that focus on population-level activities, including surveillance of disease as well as disease prevention. There are several specialised public health information systems used to prevent or mitigate disease, including syndromic surveillance, electronic laboratory reporting, and population health dashboards. This article defines and describes public health informatics and its role in eHealth. The article further discusses the role of public health information systems and challenges they face for the future. Strengthening public health will require greater investment in interoperability as well as analytics and the workforce. Disease outbreaks like COVID-19, Ebola, and H1N1 demonstrate the need for robust public health informatics applications and methods. Yet there is much work to be done to evolve existing tools and methods to strengthen the public health infrastructure for the next pandemic.

A hypothesized benefit of decentralization is that it will promote policy experimentation, yet there have been few studies examining this link. In this article, I identify three pathways through which decentralization could plausibly lead to greater experimentation and empirically assess their presence through an analysis of California's Local Control Funding Formula (LCFF), a policy that enhanced the fiscal autonomy of local school districts. I find mixed results; even though there was some evidence to suggest greater policy activity, most new actions taken by school districts were incremental changes. Further, there was little ideological differentiation in adopted policies despite variation in districts' partisan composition. Small districts were slightly more likely to experiment than larger ones, supporting the hypothesis that smaller jurisdictions are more nimble and flexible and thus more likely to enact policy change. I conclude by exploring how the incentives and preferences of local officials mediate the causal connection between decentralization and policy experimentation.

Decentralization is a structural change designed to influence policy outcomes by changing the policy‐making process. Critical to assessing the merits of decentralization is an articulation of the causal mechanisms through which it alters the motivations and behavior of officials which, in turn, influence policy decisions. This article offers a new theoretical framework that explicates these causal mechanisms. It yields two sets of hypotheses. The first posits causal relationships between decentralization and the mix of resources and constraints that a government faces when addressing a policy problem. The second set of hypotheses explores how these resources and constraints influences decisions makers' preferences, incentives, and capacity. This framework captures the potential ways through which decentralization could alter policy outcomes, pointing to a new research agenda that will allow scholars to empirically sort through the mixed and inconclusive findings on decentralization's impact.Related ArticlesDebrah,Emmanuel.2016. "."Politics & Policy44():135–164.http://onlinelibrary.wiley.com/doi/10.1111/polp.12146/abstractMeza,Oliver.2015. "."Politics & Policy43():723–753.http://onlinelibrary.wiley.com/doi/10.1111/polp.12131/abstractWaheduzzaman,Wahed, andSharifAs‐Saber.2015. "."Politics & Policy43():474–501.http://onlinelibrary.wiley.com/doi/10.1111/polp.12121/abstractRelated MediaDecentralization and Development: Making Local Governance Deliver.https://www.youtube.com/watch?v = P0NsYY2nK_A&index = 9&list = PLWa1aGn9LnaIpr767I7rHC1evmsnC6tw7Federalism and Decentralization MOOC, Leiden University.https://www.youtube.com/watch?v = cWrSladgwxsWorld Bank's Decentralization page.http://www1.worldbank.org/publicsector/decentralization/what.htm

AbstractI compare the distribution of risk attitudes of farm owners in the United States to nonfarm business owners and the general population using a measure of risk tolerance collected from national surveys. I find that farmers are significantly more tolerant of risk than the general population, though they are significantly less tolerant of risk than nonfarm business owners. Once demographic differences are controlled, farm and nonfarm business owners are more similar in their risk attitudes and both groups remain significantly more risk tolerant than the general population. First‐generation farmers display greater risk tolerance than farmers who inherit operations from family members, as do farmers who have just begun operating a farm; neither pattern emerges among nonfarm business owners. The most risk tolerant farmers are young and male with larger operations, higher incomes, less formal education and close proximity to metropolitan centers. Among farmers, those with less diversified operations and those with specialty enterprises are more risk tolerant than other types of farmers. Crop farmers are less risk tolerant than fruit and vegetable farmers or farmers with specialty enterprises, while farmers who receive government payments or buy enterprise insurance are not significantly different in risk tolerance from farmers who eschew such opportunities. These findings stimulate questions about how farm programs and the distinct challenges of entry in the production agriculture sector shape the underlying distribution of key farmer characteristics such as risk tolerance.