Bridging the Gap: Lottery-Based Procedures in Early Parliamentarization

AbstractHow is the use of political lotteries related to party development? This article discusses the effects of a lottery-based procedure used to distribute committee appointments that was once common across legislatures in nineteenth-century Europe. The authors analyze the effects of a political lottery in budget committee selection in the French Third Republic using a microlevel data set of French deputies from 1877 to 1914. They argue that the adoption and benefit of lottery-based procedures were to prevent the capture of early institutions by party factions or groups of self-interested political elites. The authors find that partial randomization of selection resulted in the appointment of young, skilled, middle-class deputies at the expense of influential elites. When parties gained control of committee assignments in 1910, selection once again favored elites and loyal party members. The authors link lottery-based procedures to party development by showing that cohesive parties were behind the institutional reform that ultimately dismantled this selection process. Lottery-based procedures thus played a sanitizing role during the transformation of emerging parliamentary groups into unified, cohesive political parties.

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Parteikommunikation im Zeitalter von Social Media

10.5771/9783748905424 ◽

2020 ◽

Author(s):

Mario Datts

Keyword(s):

Social Media ◽

Big Data ◽

Political Parties ◽

Explanatory Model ◽

Election Campaigns ◽

Data Set ◽

Comprehensive Data ◽

Party Members ◽

District Offices

How active are the local branches of political parties on social media? Do such parties use social media on the training ground of democracy? This study answers these questions using a comprehensive data set consisting of big data and data from surveys. It identifies political parties’ key reasons for using social media by developing and examining a complex explanatory model, the results of which reveal that the majority of parties’ district offices are active on social media, for example on WhatsApp, Twitter and YouTube in addition to Facebook. One key reason for them using social media sites is their desire to meet the expectations of their own party members. Furthermore, they appear to use social media in their election campaigns and because of their general distrust of the conventional media’s reporting. What is noticeable is that the local divisions of the AfD in particular seem to be extremely successful in using social media.

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Who brings home the pork? Parties and the role of localness in committee assignments in mixed-member proportional systems

Party Politics ◽

10.1177/1354068816678884 ◽

2016 ◽

Vol 24 (5) ◽

pp. 488-500 ◽

Cited By ~ 9

Author(s):

Thomas Gschwend ◽

Thomas Zittel

Keyword(s):

Political Parties ◽

Statistical Data ◽

Legislative Organization ◽

Data Set ◽

Electoral Incentives ◽

Self Selection ◽

Rich Data ◽

Committee Assignments ◽

Selection Of

The assignment of seats to specialized standing committees is a most consequential choice in legislative contexts. Distributive theories of legislative organization suggest that electoral incentives to cultivate personal votes result in the self-selection of legislators to committees best suited to please their constituents and, thus, to secure reelection. However, these theories discard the partisan basis of European parliaments and therefore fail to adequately assess the politics of committee assignments in these particular contexts. This article aims to explore the significance of distributive theories for the German case in differentiated ways and on the basis of a new and rich data set including statistical data for five legislative terms (1983, 1987, 1998, 2005, and 2009). It argues that in partisan assemblies, political parties might develop an interest in distributive politics themselves and might assign distinct types of legislators to distinct committees to seek personal votes contingent upon distinct electoral incentives. Particularly, we argue that Germany’s mixed proportional system provides incentives to parties to assign legislators with profound local roots to district committees best suited to please geographic constituents.

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Mekanisme Rekrutmen Calon Legislatif Perempuan dalam Pemilihan Legislatif Tahun 2019 (Studi di DPC Partai Kebangkitan Bangsa Kabupaten Malang)

Jurnal Pemerintahan dan Politik ◽

10.36982/jpg.v5i2.1030 ◽

2020 ◽

Vol 5 (2) ◽

Author(s):

Mahathir Muhammad Iqbal ◽

Ahmad Syaiful Kurniawan

Keyword(s):

Political Parties ◽

Political System ◽

Selection Process ◽

Equal Opportunities ◽

Case Study Method ◽

Legislative Elections ◽

Recruitment Pattern ◽

Women Candidates ◽

Party Members

AbstractPolitical parties play a role as a very strategic link between government processes and citizens. Each political party has a different recruitment pattern, where the recruitment pattern of party members is adjusted to the political system it adopts. In recruiting members and candidates for the 2019 legislative elections, DPC of the Malang Regency National Awakening Party provides equal opportunities for all citizens to compete in the selection process of candidates. The theory used is the recruitment of Pippa Norris who uses three indicators, namely: the certification stage, the nomination stage, and the general election stage. The type of approach used is qualitative using the case study method. The results of this study indicate that there are considerations taken by the National Awakening Party DPC to determine female members and candidates based on party regulations regarding the recruitment mechanism of members and candidates. Regarding this, the National Awakening Party DPC gave equal freedom to all citizens, both women and men, to become candidates. This is based on 3 indicators of the recruitment pattern of Pippa Norris, namely: first, the certification stage for candidates, the National Awakening Party DPC provides equal opportunities for everyone to run for party according to party regulations. Second, in the nomination stage, women candidates are given knowledge and skills by being obliged to enter the party underbow organization. Third, the election stage where women candidates are carried by parties to compete in legislative elections. Where women are only used as fulfillment of the 30% quota of women's representation in 2019 legislative electionsKeywords : Recruitment, women, political partiesAbstrakPartai politik memainkan peran sebagai penghubung yang sangat strategis antara proses-proses pemerintahan dengan warga negara. Setiap partai politik memiliki pola rekrutmen yang berbeda, dimana pola perekrutan anggota partai disesuaikan dengan sistem politik yang dianutnya. Dalam melakukan perekrutan anggota dan Caleg untuk pemilihan legislatif tahun 2019, DPC Partai Kebangkitan Bangsa Kabupaten Malang memberikan kesempatan yang sama kepada seluruh warga negara untuk ikut bersaing dalam proses penyeleksian Caleg. Teori yang digunakan adalah rekrutmen dari Pippa Norris yang memakai tiga indikator, yakni: tahap sertifikasi, tahap nominasi, dan tahap pemilihan umum. Jenis pendekatan yang digunakan adalah kualitatif dengan memakai metode studi kasus Hasil penelitian ini menunjukan bahwa adanya pertimbangan yang diambil oleh DPC Partai Kebangkitan Bangsa untuk menetapkan anggota dan Caleg perempuan berdasarkan peraturan partai tentang mekanisme perekrutan anggota dan Caleg. Perihal ini DPC Partai Kebangkitan Bangsa memberikan kebebasan yang sama kepada semua warga Negara baik perempuan maupun laki- laki untuk menjadi Caleg. Ini berdasarkan 3 indikator pola rekrutmen Pippa Norris yaitu: pertama, tahap sertifikasi terhadap Caleg, DPC Partai Kebangkitan Bangsa menyediakan kesempatan yang sama kepada semua orang untuk mencalonkan diri sesuai dengan peraturan partai. Kedua, tahap nominasi, caleg perempuan diberikan pengetahuan dan ketrampilan dengan berkewajiban masuk pada organisasi underbow partai. Ketiga, tahap pemilu dimana caleg perempuan diusung partai untuk bersaing pada pemilihan legsilatif. Dimana perempuan hanya dijadikan sebagai pemenuhan kuota 30% keterwakilan perempuan dalam pileg 2019.Kata kunci : Rekrutmen, perempuan, partai politik

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The Effects of Manifesto Politics on Programmatic Change

10.1093/oso/9780198758631.003.0011 ◽

2017 ◽

Author(s):

Annika Hennl ◽

Simon Tobias Franzmann

Keyword(s):

Political Parties ◽

Policy Change ◽

Political Party ◽

Causal Link ◽

The Political ◽

The Novel ◽

Core Business ◽

Party Members ◽

Decision Mode ◽

Programmatic Change

The formulation of policies constitutes a core business of political parties in modern democracies. Using the novel data of the Political Party Database (PPDB) Project and the data of the Manifesto Project (MARPOR), the authors of this chapter aim at a systematic test of the causal link between the intra-party decision mode on the electoral manifestos and the extent of programmatic change. What are the effects of the politics of manifesto formulation on the degree of policy change? Theoretically, the authors distinguish the drafting process from the final enactment of the manifesto. Empirically, they show that a higher autonomy of the party elite in formulating the manifesto leads to a higher degree of programmatic change. If party members constrain party elite’s autonomy, they tend to veto major changes.

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Remedying Diploma Democracy

10.1093/oso/9780198790631.003.0009 ◽

2017 ◽

Author(s):

Mark Bovens ◽

Anchrit Wille

Keyword(s):

Political Parties ◽

Implicit Bias ◽

Descriptive Representation ◽

The Political ◽

Political Elites ◽

Negative Effects ◽

Political Skills ◽

Compulsory Voting ◽

European Unification ◽

Nationalist Parties

How can we remedy some of the negative effects of diploma democracy? First, we discuss the rise of nationalist parties. They have forced the mainstream political parties to pay more attention to the negative effects of immigration, globalization, and European unification. Next we discuss strategies to mitigate the dominance of the well-educated in politics. We start with remedies that address differences in political skills and knowledge. Then we discuss the deliberative arenas. Many democratic reforms contain an implicit bias towards the well-educated. A more realistic citizenship model is required. This can be achieved by bringing the ballot back in, for example, by merging deliberative and more direct forms of democracy through deliberative polling, corrective referendums, and more compulsory voting. The chapter ends with a discussion of ways to make the political elites more inclusive and responsive, such as descriptive representation, sortition, and plebiscitary elements.

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Prioritizing and Analyzing the Role of Climate and Urban Parameters in the Confirmed Cases of COVID-19 Based on Artificial Intelligence Applications

International Journal of Environmental Research and Public Health ◽

10.3390/ijerph17103730 ◽

2020 ◽

Vol 17 (10) ◽

pp. 3730 ◽

Cited By ~ 9

Author(s):

Sina Shaffiee Haghshenas ◽

Behrouz Pirouz ◽

Sami Shaffiee Haghshenas ◽

Behzad Pirouz ◽

Patrizia Piro ◽

...

Keyword(s):

Artificial Intelligence ◽

Infectious Disease ◽

Relative Humidity ◽

Cost Function ◽

Selection Process ◽

Environmental Parameters ◽

Pso Algorithm ◽

Data Set ◽

De Algorithm

Nowadays, an infectious disease outbreak is considered one of the most destructive effects in the sustainable development process. The outbreak of new coronavirus (COVID-19) as an infectious disease showed that it has undesirable social, environmental, and economic impacts, and leads to serious challenges and threats. Additionally, investigating the prioritization parameters is of vital importance to reducing the negative impacts of this global crisis. Hence, the main aim of this study is to prioritize and analyze the role of certain environmental parameters. For this purpose, four cities in Italy were selected as a case study and some notable climate parameters—such as daily average temperature, relative humidity, wind speed—and an urban parameter, population density, were considered as input data set, with confirmed cases of COVID-19 being the output dataset. In this paper, two artificial intelligence techniques, including an artificial neural network (ANN) based on particle swarm optimization (PSO) algorithm and differential evolution (DE) algorithm, were used for prioritizing climate and urban parameters. The analysis is based on the feature selection process and then the obtained results from the proposed models compared to select the best one. Finally, the difference in cost function was about 0.0001 between the performances of the two models, hence, the two methods were not different in cost function, however, ANN-PSO was found to be better, because it reached to the desired precision level in lesser iterations than ANN-DE. In addition, the priority of two variables, urban parameter, and relative humidity, were the highest to predict the confirmed cases of COVID-19.

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Crowded Space, Fertile Ground: Party Entry and the Effective Number of Parties

Political Science Research and Methods ◽

10.1017/psrm.2015.22 ◽

2015 ◽

Vol 4 (2) ◽

pp. 317-342 ◽

Cited By ~ 5

Author(s):

Daniel M. Kselman ◽

Eleanor Neff Powell ◽

Joshua A. Tucker

Keyword(s):

Political Parties ◽

Party System ◽

Status Quo ◽

Policy Implications ◽

Policy Outcomes ◽

Effective Number ◽

Data Set ◽

Fertile Ground ◽

Effective Number Of Parties ◽

Number Of Parties

This paper develops a novel argument as to the conditions under which new political parties will form in democratic states. Our approach hinges on the manner in which politicians evaluate the policy implications of new party entry alongside considerations of incumbency for its own sake. We demonstrate that if candidates care sufficiently about policy outcomes, then the likelihood of party entry shouldincreasewith the effective number of status quo parties in the party system. This relationship weakens, and eventually disappears, as politicians’ emphasis on “office-seeking” motivations increases relative to their interest in public policy. We test these predictions with both aggregate electoral data in contemporary Europe and a data set on legislative volatility in Turkey, uncovering support for the argument that party system fragmentation should positively affect the likelihood of entry when policy-seeking motivations are relevant, but not otherwise.

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A systematic review of machine learning-based missing value imputation techniques

Data Technologies and Applications ◽

10.1108/dta-12-2020-0298 ◽

2021 ◽

Vol ahead-of-print (ahead-of-print) ◽

Author(s):

Tressy Thomas ◽

Enayat Rajabi

Keyword(s):

Machine Learning ◽

Selection Process ◽

Evaluation Metrics ◽

Correct Prediction ◽

Data Sets ◽

Data Set ◽

Missing Value ◽

Content Type ◽

Missing Value Imputation ◽

Literature Reviews

PurposeThe primary aim of this study is to review the studies from different dimensions including type of methods, experimentation setup and evaluation metrics used in the novel approaches proposed for data imputation, particularly in the machine learning (ML) area. This ultimately provides an understanding about how well the proposed framework is evaluated and what type and ratio of missingness are addressed in the proposals. The review questions in this study are (1) what are the ML-based imputation methods studied and proposed during 2010–2020? (2) How the experimentation setup, characteristics of data sets and missingness are employed in these studies? (3) What metrics were used for the evaluation of imputation method?Design/methodology/approachThe review process went through the standard identification, screening and selection process. The initial search on electronic databases for missing value imputation (MVI) based on ML algorithms returned a large number of papers totaling at 2,883. Most of the papers at this stage were not exactly an MVI technique relevant to this study. The literature reviews are first scanned in the title for relevancy, and 306 literature reviews were identified as appropriate. Upon reviewing the abstract text, 151 literature reviews that are not eligible for this study are dropped. This resulted in 155 research papers suitable for full-text review. From this, 117 papers are used in assessment of the review questions.FindingsThis study shows that clustering- and instance-based algorithms are the most proposed MVI methods. Percentage of correct prediction (PCP) and root mean square error (RMSE) are most used evaluation metrics in these studies. For experimentation, majority of the studies sourced the data sets from publicly available data set repositories. A common approach is that the complete data set is set as baseline to evaluate the effectiveness of imputation on the test data sets with artificially induced missingness. The data set size and missingness ratio varied across the experimentations, while missing datatype and mechanism are pertaining to the capability of imputation. Computational expense is a concern, and experimentation using large data sets appears to be a challenge.Originality/valueIt is understood from the review that there is no single universal solution to missing data problem. Variants of ML approaches work well with the missingness based on the characteristics of the data set. Most of the methods reviewed lack generalization with regard to applicability. Another concern related to applicability is the complexity of the formulation and implementation of the algorithm. Imputations based on k-nearest neighbors (kNN) and clustering algorithms which are simple and easy to implement make it popular across various domains.

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Watermelon Sorting Process by Frequency Identification and Artificial Neural Network

Applied Science and Engineering Progress ◽

10.14416/j.asep.2021.12.004 ◽

2021 ◽

Author(s):

Komsan Wongkalasin ◽

Teerapon Upachaban ◽

Wacharawish Daosawang ◽

Nattadon Pannucharoenwong ◽

Phadungsak Ratanadecho

Keyword(s):

Neural Network ◽

Artificial Neural Network ◽

Selection Process ◽

Network Processor ◽

Data Set ◽

The Neural Network ◽

Frequency Identification ◽

Sorting Process ◽

Artificial Neural ◽

Reasonable Prediction

This research aims to enhance the watermelon’s quality selection process, which was traditionally conducted by knocking the watermelon fruit and sort out by the sound’s character. The proposed method in this research is generating the sound spectrum through the watermelon and then analyzes the response signal’s frequency and the amplitude by Fast Fourier Transform (FFT). Then the obtained data were used to train and verify the neural network processor. The result shows that, the frequencies of 129 and 172 Hz were suit to be used in the comparison. Thirty watermelons, which were randomly selected from the orchard, were used to create a data set, and then were cut to manually check and match to the fruits’ quality. The 129 Hz frequency gave the response ranging from 13.57 and above in 3 groups of watermelons quality, including, not fully ripened, fully ripened, and close to rotten watermelons. When the 172 Hz gave the response between 11.11–12.72 in not fully ripened watermelons and those of 13.00 or more in the group of close to rotten and hollow watermelons. The response was then used as a training condition for the artificial neural network processor of the sorting machine prototype. The verification results provided a reasonable prediction of the ripeness level of watermelon and can be used as a pilot prototype to improve the efficiency of the tools to obtain a modern-watermelon quality selection tool, which could enhance the competitiveness of the local farmers on the product quality control.

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A Support Based Initialization Algorithm for Categorical Data Clustering

Journal of Information Technology Research ◽

10.4018/jitr.2018040104 ◽

2018 ◽

Vol 11 (2) ◽

pp. 53-67

Author(s):

Ajay Kumar ◽

Shishir Kumar

Keyword(s):

Categorical Data ◽

Selection Process ◽

Numerical Data ◽

Real Data ◽

Data Sets ◽

Data Set ◽

Data Object ◽

Data Points ◽

Wu Method ◽

Selection Algorithms

Several initial center selection algorithms are proposed in the literature for numerical data, but the values of the categorical data are unordered so, these methods are not applicable to a categorical data set. This article investigates the initial center selection process for the categorical data and after that present a new support based initial center selection algorithm. The proposed algorithm measures the weight of unique data points of an attribute with the help of support and then integrates these weights along the rows, to get the support of every row. Further, a data object having the largest support is chosen as an initial center followed by finding other centers that are at the greatest distance from the initially selected center. The quality of the proposed algorithm is compared with the random initial center selection method, Cao's method, Wu method and the method introduced by Khan and Ahmad. Experimental analysis on real data sets shows the effectiveness of the proposed algorithm.

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