Introduction

2019 ◽  
pp. 3-37
Author(s):  
Jennifer Bussell
Keyword(s):  
Data Sources ◽  
Distributive Politics ◽  
Partisan Bias ◽  
Constituency Service ◽  
High Level

The introduction to the book presents an overview of the puzzle constituency service presents to our understanding of distributive politics in patronage democracies. It then offers an overview of the book’s argument for why citizens demand assistance from their high-level representatives—individuals with substantially large constituencies such that they cannot know most of their voters personally—and why these politicians respond to such requests in a largely nonpartisan and noncontingent manner. The chapter places this constituency service conceptually within nonprogrammatic politics, alongside more well-studied forms of allocation: clientelism and partisan bias. It then offers an outline of the book’s contents and contributions, including a summary of the data sources used throughout the text.

Clients and Constituents

2019 ◽  
Author(s):  
Jennifer Bussell
Keyword(s):  
Developing Countries ◽  
Local Level ◽  
Distributive Politics ◽  
Democratic Accountability ◽  
Access To Services ◽  
Empirical Examination ◽  
Partisan Bias ◽  
Constituency Service ◽  
High Level

This book provides a theoretical and empirical examination of constituency service in developing countries. The predominant view of distributive politics in “patronage democracies” emphasizes the partisan targeting of pork and clientelism. In contrast, this book demonstrates that high-level legislators in India and other contexts often provide direct, nonpartisan assistance to individual constituents. Under what conditions do they provide constituency service, rather than engage in partisan bias? The book shows that the uneven character of access to services at the local level—often because of biased allocation on the part of local intermediaries—generates demand for help from higher-level officials, and also creates incentives for those politicians to bypass intermediaries by providing direct assistance. It draws on elite and citizen surveys, interviews, qualitative shadowing, and experiments to explore the dynamics of both the demand for constituency service and its supply. The book’s findings highlight the potential for an underappreciated form of democratic accountability, one that is however rooted in the character of patronage-based politics.

Constituency Service in Comparative Perspective

2019 ◽  
pp. 295-314
Author(s):  
Jennifer Bussell
Keyword(s):  
Distributive Politics ◽  
Individual Level ◽  
Public Benefits ◽  
Common Trend ◽  
The World ◽  
Contextual Characteristics ◽  
Constituency Service ◽  
High Level ◽  
Local Levels

Chapter 11 considers the extent to which we should expect to observe similar dynamics of distributive politics in other parts of the world. It draws on a range of cross-national data to show that the contextual characteristics supporting constituency service—the dynamics of patronage democracy, difficulty in access to public benefits, and partisan allocation of benefits at local levels, accompanied by the presence of high-level representatives with little ability to monitor individual electoral behavior—coexist across a range of democracies around the world. It offers evidence to suggest that high-level politicians in countries across Africa, Asia, and Latin America also engage in individual-level distribution to build a personal vote, rather than support for their party, and that highly partisan distribution by local operatives may ironically heighten their incentives to assist constituents in a nonpartisan manner. Thus, India is an exemplar of a common trend, rather than a global outlier.

scholarly journals The Association Between Dental Anxiety And Psychiatric Disorders And Symptoms: A Systematic Review

2018 ◽  
Vol 14 (1) ◽  
pp. 207-222 ◽  
Author(s):  
Harri Halonen ◽  
Jenna Nissinen ◽  
Heli Lehtiniemi ◽  
Tuula Salo ◽  
Pirkko Riipinen ◽  
...  
Keyword(s):  
Systematic Review ◽  
Psychiatric Disorders ◽  
Web Of Science ◽  
Dental Anxiety ◽  
Data Sources ◽  
Inclusion Criteria ◽  
Clinical Interviews ◽  
Specific Phobias ◽  
Axis I ◽  
High Level

Background:A growing amount of evidence suggests that dental anxiety is associated with other psychiatric disorders and symptoms. A systematic review was conducted to critically evaluate the studies of comorbidity of dental anxiety with other specific phobias and other Axis I psychiatric disorders.Objective:The aim of the review was to explore how dental anxiety is associated with other psychiatric disorders and to estimate the level of comorbid symptoms in dental anxiety patients.Methods:The review was conducted and reported in accordance with the MOOSE statement. Data sources included PubMed, PsycInfo, Web of Science and Scopus.Results:The search produced 631 hits, of which 16 unique records fulfilled the inclusion criteria. The number of eligible papers was low. Study populations were heterogeneous including 6,486 participants, and a total of 25 tests and in few cases clinical interviews were used in the evaluation processes. The results enhanced the idea about the comorbidity between dental anxiety and other psychiatric disorders. The effect was found strong in several studies.Conclusion:Patients with a high level of dental anxiety are more prone to have a high level of comorbid phobias, depression, mood disorders and other psychiatric disorders and symptoms.

Big Data Architecture Components

2018 ◽  
pp. 10-31
Keyword(s):  
Big Data ◽  
Missing Values ◽  
Noise Removal ◽  
Data Sources ◽  
Data Types ◽  
Layer Analysis ◽  
External Sources ◽  
Internal Sources ◽  
High Level

The previous chapter overviewed big data including its types, sources, analytic techniques, and applications. This chapter briefly discusses the architecture components dealing with the huge volume of data. The complexity of big data types defines a logical architecture with layers and high-level components to obtain a big data solution that includes data sources with the relation to atomic patterns. The dimensions of the approach include volume, variety, velocity, veracity, and governance. The diverse layers of the architecture are big data sources, data massaging and store layer, analysis layer, and consumption layer. Big data sources are data collected from various sources to perform analytics by data scientists. Data can be from internal and external sources. Internal sources comprise transactional data, device sensors, business documents, internal files, etc. External sources can be from social network profiles, geographical data, data stores, etc. Data massage is the process of extracting data by preprocessing like removal of missing values, dimensionality reduction, and noise removal to attain a useful format to be stored. Analysis layer is to provide insight with preferred analytics techniques and tools. The analytics methods, issues to be considered, requirements, and tools are widely mentioned. Consumption layer being the result of business insight can be outsourced to sources like retail marketing, public sector, financial body, and media. Finally, a case study of architectural drivers is applied on a retail industry application and its challenges and usecases are discussed.

scholarly journals Helping Novices Avoid the Hazards of Data: Leveraging Ontologies to Improve Model Generalization Automatically with Online Data Sources

AI Magazine ◽  
2016 ◽  
Vol 37 (2) ◽  
pp. 19-32 ◽  
Author(s):  
Sasin Janpuangtong ◽  
Dylan A. Shell
Keyword(s):  
Domain Knowledge ◽  
Large Scale ◽  
Model Building ◽  
Data Extraction ◽  
Data Sources ◽  
Online Data ◽  
Model Generalization ◽  
Improve Model ◽  
Building Process ◽  
High Level

The infrastructure and tools necessary for large-scale data analytics, formerly the exclusive purview of experts, are increasingly available. Whereas a knowledgeable data-miner or domain expert can rightly be expected to exercise caution when required (for example, around fallacious conclusions supposedly supported by the data), the nonexpert may benefit from some judicious assistance. This article describes an end-to-end learning framework that allows a novice to create models from data easily by helping structure the model building process and capturing extended aspects of domain knowledge. By treating the whole modeling process interactively and exploiting high-level knowledge in the form of an ontology, the framework is able to aid the user in a number of ways, including in helping to avoid pitfalls such as data dredging. Prudence must be exercised to avoid these hazards as certain conclusions may only be supported if, for example, there is extra knowledge which gives reason to trust a narrower set of hypotheses. This article adopts the solution of using higher-level knowledge to allow this sort of domain knowledge to be used automatically, selecting relevant input attributes, and thence constraining the hypothesis space. We describe how the framework automatically exploits structured knowledge in an ontology to identify relevant concepts, and how a data extraction component can make use of online data sources to find measurements of those concepts so that their relevance can be evaluated. To validate our approach, models of four different problem domains were built using our implementation of the framework. Prediction error on unseen examples of these models show that our framework, making use of the ontology, helps to improve model generalization.

scholarly journals What You Need to Know Before Implementing a Clinical Research Data Warehouse: Comparative Review of Integrated Data Repositories in Health Care Institutions

10.2196/17687 ◽  
2020 ◽  
Vol 4 (8) ◽  
pp. e17687
Author(s):  
Kristina K Gagalova ◽  
M Angelica Leon Elizalde ◽  
Elodie Portales-Casamar ◽  
Matthias Görges
Keyword(s):  
Data Processing ◽  
Clinical Data ◽  
Data Reuse ◽  
Data Sources ◽  
Primary Data ◽  
Data Repositories ◽  
Planning Stage ◽  
Common Features ◽  
Comparative Review ◽  
High Level

Background Integrated data repositories (IDRs), also referred to as clinical data warehouses, are platforms used for the integration of several data sources through specialized analytical tools that facilitate data processing and analysis. IDRs offer several opportunities for clinical data reuse, and the number of institutions implementing an IDR has grown steadily in the past decade. Objective The architectural choices of major IDRs are highly diverse and determining their differences can be overwhelming. This review aims to explore the underlying models and common features of IDRs, provide a high-level overview for those entering the field, and propose a set of guiding principles for small- to medium-sized health institutions embarking on IDR implementation. Methods We reviewed manuscripts published in peer-reviewed scientific literature between 2008 and 2020, and selected those that specifically describe IDR architectures. Of 255 shortlisted articles, we found 34 articles describing 29 different architectures. The different IDRs were analyzed for common features and classified according to their data processing and integration solution choices. Results Despite common trends in the selection of standard terminologies and data models, the IDRs examined showed heterogeneity in the underlying architecture design. We identified 4 common architecture models that use different approaches for data processing and integration. These different approaches were driven by a variety of features such as data sources, whether the IDR was for a single institution or a collaborative project, the intended primary data user, and purpose (research-only or including clinical or operational decision making). Conclusions IDR implementations are diverse and complex undertakings, which benefit from being preceded by an evaluation of requirements and definition of scope in the early planning stage. Factors such as data source diversity and intended users of the IDR influence data flow and synchronization, both of which are crucial factors in IDR architecture planning.

scholarly journals ANALISIS BUKU AJAR MARUGOTO: BAHASA DAN KEBUDAYAAN JEPANG A1 DITINJAU DARI RANAH KOGNITIF TAKSONOMI BLOOM

2018 ◽  
Vol 3 (1) ◽  
pp. 24
Author(s):  
Rakhmania Wulandari ◽  
Febi Ariani Saragih
Keyword(s):  
Bloom's Taxonomy ◽  
Data Sources ◽  
Learning Needs ◽  
Language And Culture ◽  
Low Level ◽  
Descriptive Research ◽  
Bloom’S Taxonomy ◽  
Qualitative Descriptive ◽  
High Level

Penelitian ini bertujuan untuk mengetahui kualitas isi buku ajar Marugoto: Bahasa dan Kebudayaan Jepang A1 ditinjau dari ranah kognitif taksonomi Bloom.  Kualitas buku ajar menjadi pertimbangan pengajar dalam menentukan buku ajar yang baik untuk digunakan. Menelaah kualitas buku ajar dapat dilakukan dengan menggunakan teori belajar taksonomi Bloom. Taksonomi Bloom adalah pengelompokan belajar berdasarkan tingkatan belajar. Yaitu belajar tingkat rendah yang terdiri dari kualifikasi C1 (mengingat), C2 (memahami), dan C3 (mengaplikasikan), serta belajar tingkat tinggi yang terdiri dari kualifikasi  C4 (menganalisis), C5 (mengevaluasi), dan C6 (mencipta).Penelitian ini merupakan penelitian deskriptif kualitatif. Sumber data utama adalah buku ajar Marugoto rikai dan katsudou. Analisis dilakukan dengan menganalisis bahan ajar menggunakan kualifikasi kognitif pada taksonomi Bloom. Hasil Analisis menunjukkan bahwa buku Marugoto A1 mencapai hasil yang sangat baik pada kualifikasi C1, C2, C3, C4; hasil analisis baik pada C5, dan  hasil analisis sangat kurang pada C6. Materi yang disajikan mewakili kata kerja operasioanal dalam memenuhi kebutuhan belajar tingkat rendah dengan sangat baik, namun hanya cukup mewakili kata kerja operasional dalam memenuhi kebutuhan belajar tingkat tinggi.   This research is aimed to find out the quality of Marugoto's textbook content: Japanese Language and Culture A1 from the cognitive aspects of Bloom's taxonomy. The quality of textbooks becomes the teacher's consideration in determining which textbooks are best used. Reviewing the quality of textbooks can be done using Bloom's theory of taxonomic learning. Bloom's Taxonomy is a learning grouping based on the level of learning. That is a low level study consisting of qualifications C1 (remembering), C2 (understanding), and C3 (applying), as well as a high-level learning consisting of C4 qualifying (analyzing), C5 (evaluating), and C6 (creating). is a qualitative descriptive research. The main data sources are Marugoto rikai and katsudou textbooks. The analysis was done by analyzing the teaching materials using cognitive qualifications on Bloom's taxonomy. The analysis shows that Marugoto: Language and Culture of Japan A1 achieved excellent results on qualification C1, C2, C3, C4, good analytical results on C5, and the result of analysis is very less on C6. The material presented represents operational verbs in meeting low-level learning needs very well, but only enough to represent operational verbs in meeting high-level learning needs.

scholarly journals Using the RECORD guidelines to improve transparent reporting of studies based on routinely collected data

2018 ◽  
Vol 3 (1) ◽  
Author(s):  
Katie Harron ◽  
Eric Benchimol ◽  
Sinead Langan
Keyword(s):  
Patient Care ◽  
Health Systems ◽  
Data Sources ◽  
Transparent Reporting ◽  
Routinely Collected Data ◽  
Data Record ◽  
High Level

Transparent reporting of routinely-collected data studies is key to producing valid and reliableresearch that can inform decisions about patient care and health systems. This article discussessome of the unique challenges in using these data sources, and explains how the REporting of studiesConducted using Observational Routinely-collected Data (RECORD) guidelines were developed tohelp researchers and journals to maintain a high level of quality in reporting of healthcare studiesusing routinely-collected data.

scholarly journals A Review of Semantic Sensor Technologies in Internet of Things Architectures

Complexity ◽  
2019 ◽  
Vol 2019 ◽  
pp. 1-21 ◽  
Author(s):  
Gergely Marcell Honti ◽  
Janos Abonyi
Keyword(s):  
Internet Of Things ◽  
Essential Role ◽  
Contextual Information ◽  
Data Sources ◽  
Intelligent Sensor ◽  
Semantic Metadata ◽  
Sensory Data ◽  
Intelligent Sensors ◽  
High Level

Intelligent sensors should be seamlessly, securely, and trustworthy interconnected to enable automated high-level smart applications. Semantic metadata can provide contextual information to support the accessibility of these features, making it easier for machines and humans to process the sensory data and achieve interoperability. The unique overview of sensor ontologies according to the semantic needs of the layers of IoT solutions can serve a guideline of engineers and researchers interested in the development of intelligent sensor-based solutions. The explored trends show that ontologies will play an even more essential role in interlinked IoT systems as interoperability and the generation of controlled linkable data sources should be based on semantically enriched sensory data.

scholarly journals Is there a partisan bias in the perception of the state of the economy? A comparative investigation of European countries, 2002–2016

2020 ◽  
pp. 019251212091590 ◽  
Author(s):  
Martin Okolikj ◽  
Marc Hooghe
Keyword(s):  
Economic Performance ◽  
Real Life ◽  
Economic Voting ◽  
Comparative Investigation ◽  
European Social Survey ◽  
The State ◽  
Partisan Bias ◽  
State Of The Economy ◽  
High Level ◽  
Economic Perceptions

The literature on economic voting starts from the assumptions that citizens have a sufficiently high level of knowledge about their country’s economic situation, and that they vote according to their perception of the state of the economy. However, these assumptions have been challenged as economic perceptions could be plagued by partisan bias. We use the comparative dataset of the European Social Survey to investigate partisan bias in the perception of economic performance. Firstly, we observe that the economic perceptions of both supporters and opponents of governing parties are strongly related to real-life economic indicators such as gross domestic product growth and unemployment levels. Secondly, we find that shifts in economic performance (growth and unemployment) are strongly associated with similar changes in economic perceptions among both supporters of governing parties and opposition parties. There is, however, a significant but limited partisan bias in economic perceptions in countries with high levels of unemployment.

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