Two for One: Public Welfare and Regime Legitimacy Through State Funding for CSOs in Russia

Civil societies are usually seen as facilitators of democracy or as oppositional powers withstanding authoritarian rule. However, more and more often civil society organizations (CSOs) appear to contribute to the legitimacy of non-democratic incumbents. Taking the example of contemporary Russia, this paper argues that state funding for CSOs under authoritarian regime conditions serves for securing regime legitimacy in two respects—by supporting CSOs contribution to public welfare and by transmitting state-led legitimacy discourse to the civil society sector. The analysis of applications submitted between 2013 and 2016 to the Presidential Grant Competition (PGC), the biggest public funding programme for CSOs in Russia, shows that the state is (1) supporting CSO activities above all in social, health and education-related fields, and (2) privileging projects that relate to a state-led conservative public discourse not only but foremost within those welfare-related fields. These results highlight the importance of investigating state support to CSOs in order to access the changing role of civil society under authoritarian regime conditions.

     

“Service” Municipal Administration as Part of the Development of Youth Entrepreneurship in Russia

The study offers a development of the social technologies of “service” municipal administration. The consumers’ opinions should be taken into consideration when determining the nomenclature and standards of their provision, which include the quality parameters that the consumers consider important. In addition, “service” relations imply the assessment of consumer satisfaction with the services and the correction of services based on the results of the assessment. Since this interaction implies communication between the municipal administration body and service users, it is necessary to focus on communicative technologies that are capable of providing a full cycle of service development and improvement for young entrepreneurs. Communications should help determine the expectations associated with a service, raise awareness thereof, and involve young people in the decisions related to the provision of services.     

An ICT-Driven Hybrid Automation System for Elderly Care Support: A Rehabilitation Facility Study Case

Abstract

The demographic statistics in developed countries suggest growth in the elderly segment of the population. At the same time, other studies forecast a shortage of nurses, increasing the pressure on hospitals to provide treatment for longer periods of time. These trends suggest a need for new ways of taking care of the elderly population that support safe, comfortable, and independent living. Meanwhile, prominent advances in information and communications technology (ICT) have enabled new systems that address various needs of the elderly. This article presents a case study of a rehabilitation facility located in Tampere, Finland, that uses an automation system in which ambient assisted living (AAL) and building automation (BA) system functionalities are combined. It details a field study summarizing the needs of the users, describes functional scenarios supported by the system, and reports the results of the first usability tests suggesting acceptance of a new technology by residents and caregivers. The unique combination of ambient assisted living and building automation offers a safer and more comfortable environment for the elderly as well as helps caregivers on-site in managing their workloads.     

Erratum to: Modernizing State Support of Nonprofit Service Provision: The Case of Kyrgyzstan

VOLUNTAS: International Journal of Voluntary and Nonprofit Organizations -     

Estimation of river and stream temperature trends under haphazard sampling

Long-term temporal trends in water temperature in rivers and streams are typically estimated under the assumption of evenly-spaced space-time measurements. However, sampling times and dates associated with historical water temperature datasets and some sampling designs may be haphazard. As a result, trends in temperature may be confounded with trends in time or space of sampling which, in turn, may yield biased trend estimators and thus unreliable conclusions. We address this concern using multilevel (hierarchical) linear models, where time effects are allowed to vary randomly by day and date effects by year. We evaluate the proposed approach by Monte Carlo simulations with imbalance, sparse data and confounding by trend in time and date of sampling. Simulation results indicate unbiased trend estimators while results from a case study of temperature data from the Illinois River, USA conform to river thermal assumptions. We also propose a new nonparametric bootstrap inference on multilevel models that allows for a relatively flexible and distribution-free quantification of uncertainties. The proposed multilevel modeling approach may be elaborated to accommodate nonlinearities within days and years when sampling times or dates typically span temperature extremes.     

On the role of local blockchain network features in cryptocurrency price formation

Cryptocurrencies and the underpinning blockchain technology have gained unprecedented public attention recently. In contrast to fiat currencies, transactions of cryptocurrencies, such as Bitcoin and Litecoin, are permanently recorded on distributed ledgers to be seen by the public. As a result, public availability of all cryptocurrency transactions allows us to create a complex network of financial interactions that can be used to study not only the blockchain graph, but also the relationship between various blockchain network features and cryptocurrency risk investment. We introduce a novel concept of chainlets, or blockchain motifs, to utilize this information. Chainlets allow us to evaluate the role of local topological structure of the blockchain on the joint Bitcoin and Litecoin price formation and dynamics. We investigate the predictive Granger causality of chainlets and identify certain types of chainlets that exhibit the highest predictive influence on cryptocurrency price and investment risk. More generally, while statistical aspects of blockchain data analytics remain virtually unexplored, the paper aims to highlight various emerging theoretical, methodological and applied research challenges of blockchain data analysis that will be of interest to the broad statistical community. The Canadian Journal of Statistics 48: 561–581; 2020 © 2020 Statistical Society of Canada     

Strong consistency of the regularized least-squares estimates of infinite autoregressive models

Our main interest is on-line parameter estimation of infinite AR models with exponentially decaying coefficients. The practical importance of the problem follows from the fact that the class of such models includes (but not limited to) all causal invertible ARMA(p,q$p,q$) models. On-line parameter estimation means that the length of the observed data sample is not known a priori and may indefinitely increase. Hence, the parameter estimates should be refined upon arrival of every new observation. So use of the maximum likelihood (ML) method is not feasible due to the high computational burden, and recursive estimation procedures are preferable.     

Integrative Family Therapy for Child Behavioural Problems in a Parenting Support Agency

This paper describes family therapy for behavioural problems in a parenting support agency. It discusses the literature on the effectiveness of family therapy with child behaviour problems within a community support environment. The paper presents a detailed family case study, which is discussed from an integrative family therapy framework. Narrative therapy is used as an overarching framework for integrating systemic therapy and parenting skills to help a family with a mixed cultural Aboriginal and Australian background. This allows sessions that are meaningful for the family and encourages a connection to their own resources and to their community, besides creating a safe space for a dialogue that hears and values all voices.