Measuring Group Structures, Structural Centrality and Total Expected Participation

2018 ◽  
pp. 38-55
Author(s):  
Kenneth D. Mackenzie
2021 ◽  
Author(s):  
Yasuteru Mawatari ◽  
Muneki Oouchi ◽  
Yoshiaki Yoshida ◽  
Toshifumi Hiraoki ◽  
Masayoshi Tabata

2019 ◽  
Author(s):  
Jia Chen

Summary This paper studies the estimation of latent group structures in heterogeneous time-varying coefficient panel data models. While allowing the coefficient functions to vary over cross-sections provides a good way to model cross-sectional heterogeneity, it reduces the degree of freedom and leads to poor estimation accuracy when the time-series length is short. On the other hand, in a lot of empirical studies, it is not uncommon to find that heterogeneous coefficients exhibit group structures where coefficients belonging to the same group are similar or identical. This paper aims to provide an easy and straightforward approach for estimating the underlying latent groups. This approach is based on the hierarchical agglomerative clustering (HAC) of kernel estimates of the heterogeneous time-varying coefficients when the number of groups is known. We establish the consistency of this clustering method and also propose a generalised information criterion for estimating the number of groups when it is unknown. Simulation studies are carried out to examine the finite-sample properties of the proposed clustering method as well as the post-clustering estimation of the group-specific time-varying coefficients. The simulation results show that our methods give comparable performance to the penalised-sieve-estimation-based classifier-LASSO approach by Su et al. (2018), but are computationally easier. An application to a panel study of economic growth is also provided.


2017 ◽  
Vol 319 ◽  
pp. 522-566 ◽  
Author(s):  
Gi-Sang Cheon ◽  
Ana Luzón ◽  
Manuel A. Morón ◽  
L. Felipe Prieto-Martinez ◽  
Minho Song

Author(s):  
Carol Johnson ◽  
Laurie Hill ◽  
Jennifer Lock ◽  
Noha Altowairiki ◽  
Christopher Ostrowski ◽  
...  

<p class="3">From a design perspective, the intentionality of students to engage in surface or deep learning is often experienced through prescribed activities and learning tasks. Educators understand that meaningful learning can be furthered through the structural and organizational design of the online environment that motivates the student towards task completion. However, learning engagement is unique for each student. It is dependent on both how students learn and their intentions for learning. Based on this challenge, the design of online discussions becomes a pedagogical means in developing students’ intentionality for the adoption of strategies leading to deep learning. Through a Design-Based Research (DBR) approach, iterative design of online learning components for undergraduate field experience courses were studied. For this paper, the focus of the research is on examining factors that influenced deep and surface levels of learning in online discussion forums. The results indicate that design factors (i.e., student engagement, group structures, and organization) influence the nature and degree of deep learning. From the findings, two implications for practice are shared to inform the design and scaffolding of online discussion forums to foster deep approaches to student learning.</p>


2009 ◽  
Vol 7 (2) ◽  
pp. 344-362 ◽  
Author(s):  
Markose Thomas ◽  
Suhas Phand ◽  
Arobinda Gupta

2020 ◽  
pp. 185-199
Author(s):  
Aurelija Pūraitė

Organised crime is changing and becoming increasingly diverse in its methods, group structures and impact on society. This article aims to research, on the one hand, the impact of organized crime on state’s economy, on the other hand – to analyse the possible legal and economic measures tackling and preventing organized crime activities. The article contains results of the analysis of international, regional and national legal acts and the secondary analysis of statistical data of European Union agencies and international organizations. The author used a variety of methods: from selection and analysis of primary and secondary sources to descriptive, comparative and synthesis methods. Such analysis required multitudinous, broad and diverse base of empirical data, which were collected from the international, regional, national organizations and agencies, as well as scientific, operational and theoretical reports related to the issue of organised crime and impact of this phenomenon to the state and the society.


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