Notes

Alterations in admissions, and hospital stay connection between IBD patients in a German tertiary recommendation middle over the 13-year time period.
In the United States the number of health systems that own practices or hospitals have increased in number and complexity leading to interest in assessing the relationship between health organization factors and health outcomes. However, the existence of multiple types of organizations combined with the nesting of some hospitals and practices within health systems and the nesting of some health systems within larger health systems generates numerous analytic objectives and complicates the construction of optimal survey designs. An objective function that explicitly weighs all objectives is theoretically appealing but becomes unwieldy and increasingly ad hoc as the number of objectives increases. To overcome this problem, we develop an alternative approach based on constraining the sampling design to satisfy desired statistical properties. For example, to support evaluations of the comparative importance of factors measured in different surveys on health system performance, a constraint that requires at least lyses that illustrate features of the sampling design are also presented.Mitigating misinformation on social media is an unresolved challenge, particularly because of the complexity of information dissemination. To this end, Multivariate Hawkes Processes (MHP) have become a fundamental tool because they model social network dynamics, which facilitates execution and evaluation of mitigation policies. In this paper, we propose a novel light-weight intervention-based misinformation mitigation framework using decentralized Learning Automata (LA) to control the MHP. Each automaton is associated with a single user and learns to what degree that user should be involved in the mitigation strategy by interacting with a corresponding MHP, and performing a joint random walk over the state space. We use three Twitter datasets to evaluate our approach, one of them being a new COVID-19 dataset provided in this paper. Avotaciclib clinical trial Our approach shows fast convergence and increased valid information exposure. These results persisted independently of network structure, including networks with central nodes, where the latter could be the root of misinformation. Further, the LA obtained these results in a decentralized manner, facilitating distributed deployment in real-life scenarios.Exogeneous disruptions in labor demand have become more frequent in recent times. The COVID-19 pandemic has resulted in millions of workers being repeatedly laid off and rehired according to local public health conditions. This may be bad news for market efficiency. Typical employment relations-which resemble non-enforceable (implicit) contracts-rely on reciprocity (Brown et al. in Econometrica 72747-780, 2004), and hence could be harmed when workers' efforts no longer guarantee reemployment in the next period. In this paper we extend the BFF paradigm to include a per-period probability (0%, 10%, 50%) of publicly observable "shutdown", where a specific firm cannot contract with any workers for several periods. A Perfect Bayesian Equilibrium exists in which these shutdowns destabilize relationships, but do not harm efficiency. Our experiment shows that, remarkably, market efficiency can be maintained even with very frequent stochastic shutdowns. However, the dynamic of relational contracts changes from one where a worker finds stable employment to one where she juggles multiple employers, laying the burden of maintaining productivity upon workers and worsening worker-side inequality.
The online version contains supplementary material available at (10.1007/s10683-020-09697-1).
The online version contains supplementary material available at (10.1007/s10683-020-09697-1).Are countries especially entitled, if not obliged, to prioritize the interests or well-being of their own citizens during a global crisis, such as a global pandemic? We call this partiality for compatriots in times of crisis "crisis nationalism". Vaccine nationalism is one vivid example of crisis nationalism during the COVID-19 pandemic; so is the case of the US government's purchasing a 3-month supply of the global stock of the antiviral Remdesivir for domestic use. Is crisis nationalism justifiable at all, and, if it is, what are its limits? We examine some plausible arguments for national partiality, and conclude that these arguments support crisis nationalism only within strict limits. The different arguments for partiality, as we will note, arrive at these limits for different reasons. But more generally, so we argue, any defensible crisis nationalism must not entail the violation of human rights or the worsening of people's deprivation. Moreover, we propose that good faith crisis nationalism ought to be sensitive to the potential moral costs of national partiality during a global crisis and must take extra care to control or offset these costs. Thus, crisis nationalism in the form of vaccine nationalism or the hoarding of global supplies of therapeutics during a global pandemic exceeds the bounds of acceptable partiality.During the northern hemisphere Winter 2020 academic term, university students had to adjust to remote learning in response to the COVID-19 pandemic. This abrupt change provided a unique opportunity to examine students' motivation, engagement and perceptions of success and cheating under two learning conditions, namely traditional and remote. We used a single survey to collect retrospective self-report data from a convenience sample of Canadian undergraduate students (n = 98) about their motivation, engagement and perceptions of success and cheating before COVID-19 and then in remote learning. Students' achievement goals, engagement and perceptions of success all significantly decreased, while their perceptions of cheating increased. Moreover, we used regression analyses to examine associations amongst achievement goals and engagement, perceptions of success and cheating concerns. Mastery-approach goals were positively associated with more engagement and higher perceptions of success. Achievement goals were unrelated to cheating. Students in large classes and who were originally concerned about cheating became more concerned about cheating in remote learning conditions. Our study provides information to researchers and instructors about how achievement goals relate to student outcomes across learning conditions. By extension, we provide timely recommendations for instructors as they continue to wrestle with how to deliver their courses during the COVID-19 pandemic.
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