Who Does What Work in a Ministerial Office: Politically Appointed Staff and the Descriptive Representation of Women in Australian Political Offices, 1979–2010

2019 ◽  
Vol 68 (2) ◽  
pp. 463-485 ◽  
Author(s):  
Marija Taflaga ◽  
Matthew Kerby
Keyword(s):  
Political Institutions ◽  
Career Paths ◽  
Descriptive Representation ◽  
Policy Outcomes ◽  
Political Elites ◽  
Data Set ◽  
Systematic Data ◽  
Representation Of Women ◽  
Policy Work ◽  
First Time

Women are underrepresented within political institutions, which can (negatively) impact policy outcomes. We examine women’s descriptive representation as politically appointed staff within ministerial offices. Politically appointed staff are now institutionalised into the policy process, so who they are is important. To date, collecting systematic data on political staff has proved impossible. However, for the first time we demonstrate how to build a systematic data set of this previously unobservable population. We use Australian Ministerial Directories (telephone records) from 1979 to 2010 (a method that can notionally be replicated in advanced democratic jurisdictions), to examine political advising careers in a similar manner as elected political elites. We find that work in political offices is divided on gender lines: men undertake more policy work, begin and end their careers in higher status roles and experience greater career progression than women. We find evidence that this negatively impacts women’s representation and their later career paths into parliament.

Political Support

2007 ◽  
Vol 40 (12) ◽  
pp. 1511-1532 ◽  
Author(s):  
Henar Criado ◽  
Francisco Herreros
Keyword(s):  
Political Institutions ◽  
European Social Survey ◽  
Political Support ◽  
Policy Outcomes ◽  
Attribution Of Responsibility ◽  
Data Set ◽  
Social Survey ◽  
Individual Variables ◽  
The Government

The analysis of the causes of political support for political institutions has been focused either on one-case studies that stress the relevance of individual variables or cross-national studies that stress the role of institutions. In this article, the authors suggest that to understand the logic of political support, it is necessary to combine both types of explanations. Using evidence from 17 European countries of the 2002 to 2003 European Social Survey data set, the authors show that the effect of the performance of the institution on political support is higher in majoritarian democracies, where the attribution of responsibility for policy outcomes is clear, than in proportional democracies. They also show that the effect of ideology on political support depends on the type of democracy: Those citizens ideologically far from the government will show higher levels of political support in proportional democracies than in majoritarian ones.

Identity in Campaign Finance and Elections: The Impact of Gender and Race on Money Raised in 2010–2018 U.S. House Elections

2021 ◽  
pp. 106591292110228
Author(s):  
Ashley Sorensen ◽  
Philip Chen
Keyword(s):  
Campaign Finance ◽  
Original Data ◽  
Descriptive Representation ◽  
Data Set ◽  
Gender And Race ◽  
Race And Gender ◽  
Representation Of Women ◽  
Unequal Access ◽  
And Gender ◽  
The Impact

Disproportionate rates of congressional representation based on gender and race are especially stark considering the symbolic and substantive meaning derived from descriptive representation (Mansbridge 1999). Using an original data set consisting of candidate demographics, district characteristics, and campaign finance reports, we analyze an understudied barrier to representation: unequal access to campaign receipts. We argue that it is the simultaneous gendering and racialization of the campaign finance system that produces gaps in campaign fundraising and representation (Crenshaw 1989). Our results underscore the limitations of unitary approaches which conclude that women no longer face a disadvantage in campaign fundraising. Unequal access to campaign receipts serve as a barrier to the descriptive representation of women of color. By analyzing the interaction of both race and gender on campaign receipt totals in U.S. House elections from 2010 to 2018, we assert the path to representation is not equal for all.

Remedying Diploma Democracy

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.

Intuitionistic fuzzy two-factor variance analysis of movie ticket sales

2021 ◽  
pp. 1-11
Author(s):  
Velichka Traneva ◽  
Stoyan Tranev
Keyword(s):  
Comparative Analysis ◽  
Real Data ◽  
Intuitionistic Fuzzy Sets ◽  
Real Numbers ◽  
Data Set ◽  
Important Method ◽  
Ticket Sales ◽  
Intuitionistic Fuzzy ◽  
The One ◽  
First Time

Analysis of variance (ANOVA) is an important method in data analysis, which was developed by Fisher. There are situations when there is impreciseness in data In order to analyze such data, the aim of this paper is to introduce for the first time an intuitionistic fuzzy two-factor ANOVA (2-D IFANOVA) without replication as an extension of the classical ANOVA and the one-way IFANOVA for a case where the data are intuitionistic fuzzy rather than real numbers. The proposed approach employs the apparatus of intuitionistic fuzzy sets (IFSs) and index matrices (IMs). The paper also analyzes a unique set of data on daily ticket sales for a year in a multiplex of Cinema City Bulgaria, part of Cineworld PLC Group, applying the two-factor ANOVA and the proposed 2-D IFANOVA to study the influence of “ season ” and “ ticket price ” factors. A comparative analysis of the results, obtained after the application of ANOVA and 2-D IFANOVA over the real data set, is also presented.

A comparison of methodological approaches to the subfamilial classification of the Naididae (Oligochaeta)

1987 ◽  
Vol 65 (3) ◽  
pp. 691-707 ◽  
Author(s):  
A. F. L. Nemec ◽  
R. O. Brinkhurst
Keyword(s):  
Data Matrix ◽  
Jaccard Coefficient ◽  
Data Set ◽  
Parsimony Method ◽  
Fit Statistics ◽  
Reconstruction Methods ◽  
Linkage Methods ◽  
The Family ◽  
First Time

A data matrix of 23 generic or subgeneric taxa versus 24 characters and a shorter matrix of 15 characters were analyzed by means of ordination, cluster analyses, parsimony, and compatibility methods (the last two of which are phylogenetic tree reconstruction methods) and the results were compared inter alia and with traditional methods. Various measures of fit for evaluating the parsimony methods were employed. There were few compatible characters in the data set, and much homoplasy, but most analyses separated a group based on Stylaria from the rest of the family, which could then be separated into four groups, recognized here for the first time as tribes (Naidini, Derini, Pristinini, and Chaetogastrini). There was less consistency of results within these groups. Modern methods produced results that do not conflict with traditional groupings. The Jaccard coefficient minimizes the significance of symplesiomorphy and complete linkage avoids chaining effects and corresponds to actual similarities, unlike single or average linkage methods, respectively. Ordination complements cluster analysis. The Wagner parsimony method was superior to the less flexible Camin–Sokal approach and produced better measure of fit statistics. All of the aforementioned methods contain areas susceptible to subjective decisions but, nevertheless, they lead to a complete disclosure of both the methods used and the assumptions made, and facilitate objective hypothesis testing rather than the presentation of conflicting phylogenies based on the different, undisclosed premises of manual approaches.

Institution, network and elites’ political attitudes: An analysis of the “Wen Jiabao Phenomenon”

2012 ◽  
Vol 45 (1-2) ◽  
pp. 105-115
Author(s):  
Sangkuk Lee
Keyword(s):  
Network Analysis ◽  
Policy Making ◽  
Political Attitudes ◽  
Political Reform ◽  
Political Elites ◽  
Standing Committee ◽  
Political Views ◽  
Policy Work

Unlike China’s other top leaders, PremierWen Jiabao has presented his political views after the 17th CCP Congress. Wen’s assertive attitude for further political reform has attracted attention from international as well as domestic media. This article utilizes both institutionalism and network analysis to explain this uncommon political phenomenon, while it illuminates the drawback of the attribute perspective which has been used popularly to infer the attitudes of China’s political elites. This study argues that Wen’s attitude with personality has been produced by some institutional and network factors. They include: the decline of a powerful rival, different functions of the party and state in China’s policy-making and implementation, division of policy work among Politburo Standing Committee leaders.

scholarly journals What Countries Select More Experienced Leaders? The PolEx Measure of Political Experience

2021 ◽  
pp. 1-10
Author(s):  
Alexander Baturo ◽  
Johan A. Elkink
Keyword(s):  
Career Paths ◽  
Latent Variable ◽  
Empirical Studies ◽  
Future Research ◽  
Variable Model ◽  
Data Set ◽  
Political Experience ◽  
National Leaders ◽  
Regime Types ◽  
The Difference

Abstract How can one assess which countries select more experienced leaders for the highest office? There is wide variation in prior career paths of national leaders within, and even more so between, regime types. It is therefore challenging to obtain a truly comparative measure of political experience; empirical studies have to rely on proxies instead. This article proposes PolEx, a measure of political experience that abstracts away from the details of career paths and generalizes based on the duration, quality and breadth of an individual's experience in politics. The analysis draws on a novel data set of around 2,000 leaders from 1950 to 2017 and uses a Bayesian latent variable model to estimate PolEx. The article illustrates how the new measure can be used comparatively to assess whether democracies select more experienced leaders. The authors find that while on average they do, the difference with non-democracies has declined dramatically since the early 2000s. Future research may leverage PolEx to investigate the role of prior political experience in, for example, policy making and crisis management.

scholarly journals Do Women Need Women Representatives?

2009 ◽  
Vol 40 (1) ◽  
pp. 171-194 ◽  
Author(s):  
Rosie Campbell ◽  
Sarah Childs ◽  
Joni Lovenduski
Keyword(s):  
Gender Equality ◽  
Empirical Research ◽  
Political Elites ◽  
Election Study ◽  
Substantive Representation ◽  
Men And Women ◽  
Representation Of Women ◽  
Mass Attitudes ◽  
The Relationship ◽  
Mass Level

This article analyses the relationship between the representatives and the represented by comparing elite and mass attitudes to gender equality and women’s representation in Britain. In so doing, the authors take up arguments in the recent theoretical literature on representation that question the value of empirical research of Pitkin’s distinction between substantive and descriptive representation. They argue that if men and women have different attitudes at the mass level, which are reproduced amongst political elites, then the numerical under-representation of women may have negative implications for women’s substantive representation. The analysis is conducted on the British Election Study (BES) and the British Representation Study (BRS) series.

scholarly journals Prediction of IL4 Inducing Peptides

2013 ◽  
Vol 2013 ◽  
pp. 1-9 ◽  
Author(s):  
Sandeep Kumar Dhanda ◽  
Sudheer Gupta ◽  
Pooja Vir ◽  
G. P. S. Raghava
Keyword(s):  
Mhc Class Ii ◽  
Critical Role ◽  
Interleukin 4 ◽  
Th2 Response ◽  
Data Set ◽  
T Helper 2 ◽  
Cell Responses ◽  
Antibody Class ◽  
First Time ◽  
Motif Information

The secretion of Interleukin-4 (IL4) is the characteristic of T-helper 2 responses. IL4 is a cytokine produced by CD4+ T cells in response to helminthes and other extracellular parasites. It has a critical role in guiding antibody class switching, hematopoiesis and inflammation, and the development of appropriate effector T-cell responses. In this study, it is the first time an attempt has been made to understand whether it is possible to predict IL4 inducing peptides. The data set used in this study comprises 904 experimentally validated IL4 inducing and 742 noninducing MHC class II binders. Our analysis revealed that certain types of residues are preferred at certain positions in IL4 inducing peptides. It was also observed that IL4 inducing and noninducing epitopes differ in compositional and motif pattern. Based on our analysis we developed classification models where the hybrid method of amino acid pairs and motif information performed the best with maximum accuracy of 75.76% and MCC of 0.51. These results indicate that it is possible to predict IL4 inducing peptides with reasonable precession. These models would be useful in designing the peptides that may induce desired Th2 response.

Decision fusion-based approach for content-based image classification

2017 ◽  
Vol 10 (3) ◽  
pp. 310-331 ◽  
Author(s):  
Sudeep Thepade ◽  
Rik Das ◽  
Saurav Ghosh
Keyword(s):  
Feature Extraction ◽  
Image Classification ◽  
Image Recognition ◽  
Extraction Techniques ◽  
Data Set ◽  
Content Type ◽  
Knowledge Fusion ◽  
Knn Classifier ◽  
Query Classification ◽  
First Time

Purpose Current practices in data classification and retrieval have experienced a surge in the use of multimedia content. Identification of desired information from the huge image databases has been facing increased complexities for designing an efficient feature extraction process. Conventional approaches of image classification with text-based image annotation have faced assorted limitations due to erroneous interpretation of vocabulary and huge time consumption involved due to manual annotation. Content-based image recognition has emerged as an alternative to combat the aforesaid limitations. However, exploring rich feature content in an image with a single technique has lesser probability of extract meaningful signatures compared to multi-technique feature extraction. Therefore, the purpose of this paper is to explore the possibilities of enhanced content-based image recognition by fusion of classification decision obtained using diverse feature extraction techniques. Design/methodology/approach Three novel techniques of feature extraction have been introduced in this paper and have been tested with four different classifiers individually. The four classifiers used for performance testing were K nearest neighbor (KNN) classifier, RIDOR classifier, artificial neural network classifier and support vector machine classifier. Thereafter, classification decisions obtained using KNN classifier for different feature extraction techniques have been integrated by Z-score normalization and feature scaling to create fusion-based framework of image recognition. It has been followed by the introduction of a fusion-based retrieval model to validate the retrieval performance with classified query. Earlier works on content-based image identification have adopted fusion-based approach. However, to the best of the authors’ knowledge, fusion-based query classification has been addressed for the first time as a precursor of retrieval in this work. Findings The proposed fusion techniques have successfully outclassed the state-of-the-art techniques in classification and retrieval performances. Four public data sets, namely, Wang data set, Oliva and Torralba (OT-scene) data set, Corel data set and Caltech data set comprising of 22,615 images on the whole are used for the evaluation purpose. Originality/value To the best of the authors’ knowledge, fusion-based query classification has been addressed for the first time as a precursor of retrieval in this work. The novel idea of exploring rich image features by fusion of multiple feature extraction techniques has also encouraged further research on dimensionality reduction of feature vectors for enhanced classification results.

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