scholarly journals The Boundaries of Research in an Authoritarian State

2019 ◽  
Vol 18 ◽  
pp. 160940691987646 ◽  
Author(s):  
Saltanat Janenova

This article provides a reflective analysis of a local scholar on methodological challenges of conducting research in Kazakhstan — a post-Soviet, authoritarian, Central Asian country. It specifically addresses the problems of getting access to government officials and the quality of data, describes the strategies applied by the researcher to mitigate these obstacles, and discusses the impact of the political environment on decisions relating to the research design, ethical integrity, safety of participants and researchers, and publication dilemma. This article will be of interest both for researchers who are doing or planning to conduct research in Kazakhstan and Central Asia and those who are researching in nondemocratic contexts as methodological challenges of an authoritarian regime stretch beyond the geographical boundaries.

2019 ◽  
Vol 2 (2) ◽  
Author(s):  
Yeni Sri Lestari

This article analyzes the history and role of the Ombudsman in improving the quality of public service delivery by government officials of a country. The establishment of the Ombudsman is an important step that is done to balance the performance of the apparatus of government in providing public services and justice to the people. This study is important as a reference many countries are working to improve the quality of public services personnel administration. Therefore, the discussion in this article is what is meant by the Ombudsman? How Ombudsman formed? The second is how the performance of the Ombudsman? And how is the impact of the Ombudsman? This study found that the background of the establishment of Ombudsman first appeared in Sweden is based on the Swedish government's efforts to create a balance of public services by government officials and the general public to the demands of globalization and democracy today. At the end of the study it was found that by taking a study on the Ombudsman parliamentary in New Zealand and the United Kingdom found that the practice of the concept of Ombudsman institutions have a positive impact to the management of the public service, it then becomes the impetus for other countries to participate in establishing the Ombudsman.Keywords: Ombudsman, New Zealand, United Kingdom


2019 ◽  
Author(s):  
Pavankumar Mulgund ◽  
Raj Sharman ◽  
Priya Anand ◽  
Shashank Shekhar ◽  
Priya Karadi

BACKGROUND In recent years, online physician-rating websites have become prominent and exert considerable influence on patients’ decisions. However, the quality of these decisions depends on the quality of data that these systems collect. Thus, there is a need to examine the various data quality issues with physician-rating websites. OBJECTIVE This study’s objective was to identify and categorize the data quality issues afflicting physician-rating websites by reviewing the literature on online patient-reported physician ratings and reviews. METHODS We performed a systematic literature search in ACM Digital Library, EBSCO, Springer, PubMed, and Google Scholar. The search was limited to quantitative, qualitative, and mixed-method papers published in the English language from 2001 to 2020. RESULTS A total of 423 articles were screened. From these, 49 papers describing 18 unique data quality issues afflicting physician-rating websites were included. Using a data quality framework, we classified these issues into the following four categories: intrinsic, contextual, representational, and accessible. Among the papers, 53% (26/49) reported intrinsic data quality errors, 61% (30/49) highlighted contextual data quality issues, 8% (4/49) discussed representational data quality issues, and 27% (13/49) emphasized accessibility data quality. More than half the papers discussed multiple categories of data quality issues. CONCLUSIONS The results from this review demonstrate the presence of a range of data quality issues. While intrinsic and contextual factors have been well-researched, accessibility and representational issues warrant more attention from researchers, as well as practitioners. In particular, representational factors, such as the impact of inline advertisements and the positioning of positive reviews on the first few pages, are usually deliberate and result from the business model of physician-rating websites. The impact of these factors on data quality has not been addressed adequately and requires further investigation.


2021 ◽  
Vol 2021 (2) ◽  
pp. 229-241
Author(s):  
Vera L. LUKICHEVA ◽  
◽  
Andrey A. PRIVALOV ◽  
Daniil D. TITOV ◽  
◽  
...  

Objective: To analyze the impact of computer attacks on the performance quality of data transmission channels and channeling systems. It is also necessary to take into account the capabilities of an intruder to introduce malware into channeling systems when committing a computer attack. Methods: To determine the required design ratios, several options for setting various distribution functions characterizing the parameters used as input data and types of inbound streams have been considered, taking into account the parameters of the intruder’s computer attack model set by the values of the probability of successful attack. Mathematical modeling is carried out using the method of topological transformation of stochastic networks. The exponential, momentum and gamma distributions are considered as distribution functions of random variables. The solutions are presented for inbound streams corresponding to the Poisson, Weibull, and Pareto models. Results: The proposed approach makes it possible to assess the performance quality of data transmission channels in the context of computer attacks. These assessments make it possible to analyze the state and develop guidelines for improving the performance quality of communication channels against the destructive information impact of the intruder. Various variants of the functions of random variables distribution and various types of the inbound stream were used for modeling, making it possible to compare them, as well as to assess the possibility of using them in channels that provide users with different services. Practical importance: The modeling results can be used to build communication management decision support systems, as well as to detect attempts of unauthorized access to the telecommunications resource of transportation management systems. The proposed approach can be applied in the development of threat models to describe the capabilities of the intruder (the ‘Intruder Model’).


2021 ◽  
Author(s):  
Sven Hilbert ◽  
Stefan Coors ◽  
Elisabeth Barbara Kraus ◽  
Bernd Bischl ◽  
Mario Frei ◽  
...  

Classical statistical methods are limited in the analysis of highdimensional datasets. Machine learning (ML) provides a powerful framework for prediction by using complex relationships, often encountered in modern data with a large number of variables, cases and potentially non-linear effects. ML has turned into one of the most influential analytical approaches of this millennium and has recently become popular in the behavioral and social sciences. The impact of ML methods on research and practical applications in the educational sciences is still limited, but continuously grows as larger and more complex datasets become available through massive open online courses (MOOCs) and large scale investigations.The educational sciences are at a crucial pivot point, because of the anticipated impact ML methods hold for the field. Here, we review the opportunities and challenges of ML for the educational sciences, show how a look at related disciplines can help learning from their experiences, and argue for a philosophical shift in model evaluation. We demonstrate how the overall quality of data analysis in educational research can benefit from these methods and show how ML can play a decisive role in the validation of empirical models. In this review, we (1) provide an overview of the types of data suitable for ML, (2) give practical advice for the application of ML methods, and (3) show how ML-based tools and applications can be used to enhance the quality of education. Additionally we provide practical R code with exemplary analyses, available at https: //osf.io/ntre9/?view only=d29ae7cf59d34e8293f4c6bbde3e4ab2.


Sensors ◽  
2019 ◽  
Vol 19 (19) ◽  
pp. 4172 ◽  
Author(s):  
Karel Dejmal ◽  
Petr Kolar ◽  
Josef Novotny ◽  
Alena Roubalova

An increasing number of individuals and institutions own or operate meteorological stations, but the resulting data are not yet commonly used in the Czech Republic. One of the main difficulties is the heterogeneity of measuring systems that puts in question the quality of outcoming data. Only after a thorough quality control of recorded data is it possible to proceed with for example a specific survey of variability of a chosen meteorological parameter in an urban or suburban region. The most commonly researched element in the given environment is air temperature. In the first phase, this paper focuses on the quality of data provided by amateur and institutional stations. The following analyses consequently work with already amended time series. Due to the nature of analyzed data and their potential use in the future it is opportune to assess the appropriateness of chronological and possibly spatial interpolation of missing values. The evaluation of seasonal variability of air temperature in the scale of Brno city and surrounding area in 2015–2017 demonstrates, that the enrichment of network of standard (professional) stations with new stations may significantly refine or even revise the current state of knowledge, for example in the case of urban heat island phenomena. A cluster analysis was applied in order to assess the impact of localization circumstances (station environment, exposition, etc.) as well as typological classification of the set of meteorological stations.


Author(s):  
Galina Gorelova ◽  
Andrey Saak

Conducting research on the quality of life of young people and the impact on it of such a significant factor as the youth labor market, as well as related research on the problems of state support for young people, require the use of simulation methods due to the incompleteness of information and poorly structured problems of such complex systems as the quality of life of young people and the labor market. The article gives a brief overview of the categories “labor market”, “quality of life”, “youth”, which is necessary to determine the content of cognitive modeling of the complex system “youth, labor market, quality of life”. The technology of cognitive modeling is briefly presented. The results of the application of cognitive simulation modeling to the study of the quality of life of young people in relation to the labor market are presented. An example of modeling is presented in the form of a corresponding cognitive map and a number of scenarios for the possible development of situations on it, which may arise under the assumed influence of various social and economic factors, as well as under the influence of regulatory and control systems.


2020 ◽  
Author(s):  
Jose Juan Almagro Armenteros ◽  
Alexander Rosenberg Johansen ◽  
Ole Winther ◽  
Henrik Nielsen

AbstractMotivationLanguage modelling (LM) on biological sequences is an emergent topic in the field of bioinformatics. Current research has shown that language modelling of proteins can create context-dependent representations that can be applied to improve performance on different protein prediction tasks. However, little effort has been directed towards analyzing the properties of the datasets used to train language models. Additionally, only the performance of cherry-picked downstream tasks are used to assess the capacity of LMs.ResultsWe analyze the entire UniProt database and investigate the different properties that can bias or hinder the performance of LMs such as homology, domain of origin, quality of the data, and completeness of the sequence. We evaluate n-gram and Recurrent Neural Network (RNN) LMs to assess the impact of these properties on performance. To our knowledge, this is the first protein dataset with an emphasis on language modelling. Our inclusion of properties specific to proteins gives a detailed analysis of how well natural language processing methods work on biological sequences. We find that organism domain and quality of data have an impact on the performance, while the completeness of the proteins has little influence. The RNN based LM can learn to model Bacteria, Eukarya, and Archaea; but struggles with Viruses. By using the LM we can also generate novel proteins that are shown to be similar to real proteins.Availability and implementationhttps://github.com/alrojo/UniLanguage


1993 ◽  
Vol 7 (3) ◽  
pp. 232-243 ◽  
Author(s):  
Robert C. Eklund

Sport psychology research conducted in field settings has expanded considerably in the last decade and a half. However, there has been little formal discussion of a number of important issues concerning the notion of conducting research in ecologically valid settings. Gaining entry to collect data with sport participants is one such issue. This important initial stage of the field research process regards not only the feasibility of collecting data but also the very quality of data that one might be able to collect in the setting. This manuscript presents important guiding considerations for efforts to gain entry to field settings, including personal attributes of the researcher, connections, accounts, knowledge, and courtesy. Social science and sport psychology practitioner literature regarding gaining entry are examined, and relevant examples are integrated into the discussion.


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