The effect of social homogeneity on coincidence probabilities for pairwise proportional lottery and simple majority rules

1992 ◽  
Vol 9 (4) ◽  
Author(s):  
WilliamV. Gehrlein ◽  
Sven Berg
Keyword(s):  
Simple Majority ◽  
Majority Rules

Multi-level dynamo and opinion spreading

2015 ◽  
Vol 27 (2) ◽  
pp. 234-256 ◽  
Author(s):  
SARA BRUNETTI ◽  
GENNARO CORDASCO ◽  
ELENA LODI ◽  
LUISA GARGANO ◽  
WALTER QUATTROCIOCCHI
Keyword(s):  
Lower Bounds ◽  
Maximum Level ◽  
Upper Bounds ◽  
Simple Majority ◽  
Spreading Model ◽  
Multi Level ◽  
Majority Rules ◽  
The Individual

We consider the following multi-level opinion spreading model on networks. Initially, each node gets a weight, from the set {0,. . .,k – 1}, which measures the individual conviction of a new idea or product. Then, by proceeding in rounds, each node updates its weight according to those of its neighbours. We study k-dynamos that are initial assignments of weights leading each node to get the value k – 1 – e.g. unanimous maximum level of acceptance – within a given number of rounds; the goal is to minimize the sum of the initial weights of the nodes. We determine lower bounds on the sum of the initial weights under the irreversible simple majority rules, where a node increases its weight if and only if the majority of its neighbours have a weight that is higher than its own. We study the relations among 2-dynamos and k-dynamos, with and without a bound on the number of rounds needed to reach the desired all-(k – 1) configuration. Moreover, we provide constructive tight upper bounds for some classes of regular topologies: rings, tori and cliques.

Between the expert and majority rules

2003 ◽  
Vol 35 (4) ◽  
pp. 941-960 ◽  
Author(s):  
Daniel Berend ◽  
Luba Sapir
Keyword(s):  
Majority Rule ◽  
Simple Majority ◽  
Simple Majority Rule ◽  
Expert Rule ◽  
Special Cases ◽  
The Family ◽  
Majority Rules

Sapir (1998) calculated the probabilities of the expert rule and of the simple majority rule being optimal under the assumption of exponentially distributed logarithmic expertise levels. Here we find the analogous probabilities for the family of restricted majority rules, including the above two extreme rules as special cases, and the family of balanced expert rules. We compare the two families, the rules within each family, and all rules of the two families with the extreme rules.

Between the expert and majority rules

2003 ◽  
Vol 35 (04) ◽  
pp. 941-960 ◽  
Author(s):  
Daniel Berend ◽  
Luba Sapir
Keyword(s):  
Majority Rule ◽  
Simple Majority ◽  
Simple Majority Rule ◽  
Expert Rule ◽  
Special Cases ◽  
The Family ◽  
Majority Rules

Sapir (1998) calculated the probabilities of the expert rule and of the simple majority rule being optimal under the assumption of exponentially distributed logarithmic expertise levels. Here we find the analogous probabilities for the family of restricted majority rules, including the above two extreme rules as special cases, and the family of balanced expert rules. We compare the two families, the rules within each family, and all rules of the two families with the extreme rules.

Absolute Majority Rules

2007 ◽  
Vol 37 (4) ◽  
pp. 643-658 ◽  
Author(s):  
ADRIAN VERMEULE
Keyword(s):  
Simple Majority ◽  
Strategic Behaviour ◽  
Absolute Majority ◽  
Majority Rules

This article considers absolute majority rules, which require the affirmative vote of a majority of all those eligible to vote in the institution. I compare absolute majority rules to simple majority rules under which only those present and voting are counted, and to simple supermajority rules. Under plausible conditions, absolute majority rules prove superior. Absolute majority rules insure majorities against strategic behaviour by minorities and combine supermajoritarian effects with majoritarian symbolism.

Enhanced Recognition Accuracy with the Simultaneous Use of Three Automated Speech Recognition Systems

1992 ◽  
Vol 36 (4) ◽  
pp. 288-292 ◽  
Author(s):  
Timothy P. Barry ◽  
Kristen K. Liggett ◽  
David T. Williamson ◽  
John M. Reising
Keyword(s):  
Speech Recognition ◽  
Recognition Accuracy ◽  
Simple Majority ◽  
Intelligent Software ◽  
Automated Speech Recognition ◽  
Recognition Systems ◽  
Majority Rules ◽  
The Individual ◽  
Sophisticated Algorithm ◽  
Better Than

Two studies were performed to test the efficacy of using three different automated speech recognition devices in parallel to obtain speech recognition accuracies better than those produced by each of the individual systems alone. The first experiment compared the recognition accuracy of each of the three individual systems with the accuracy obtained by combining the data from all three systems using a simple “Majority Rules” algorithm. The second experiment made the same comparison, but used a more sophisticated algorithm developed using the performance data obtained from experiment 1. Results from the first experiment revealed a modest increase in speech recognition accuracy using all three systems in concert along with the Simple Majority Rules (SMR) algorithm. Results from the second experiment showed an even greater improvement in recognition accuracy using the three systems in concert and an Enhanced Majority Rules (EMR) algorithm. The implications of using intelligent software and multiple speech recognition devices to improve speech recognition accuracy are discussed.

scholarly journals Special Majorities Rationalized

2006 ◽  
Vol 36 (2) ◽  
pp. 213-241 ◽  
Author(s):  
ROBERT E. GOODIN ◽  
CHRISTIAN LIST
Keyword(s):  
Majority Rule ◽  
Federal System ◽  
Simple Majority ◽  
Simple Majority Rule ◽  
Majority Rules ◽  
The Cost ◽  
Conservative Bias

Complaints are common about the arbitrary and conservative bias of special-majority rules. Such complaints, however, apply to asymmetrical versions of those rules alone. Symmetrical special-majority rules remedy that defect, albeit at the cost of often rendering no determinate verdict. Here what is formally at stake, both procedurally and epistemically, is explored in the choice between those two forms of special-majority rule and simple-majority rule; and practical ways are suggested of resolving matters left open by symmetrical special-majority rules – such as ‘judicial extrapolation’ or ‘subsidiarity’ in a federal system.

Institution-Induced Stability

2019 ◽  
pp. 84-102
Author(s):  
Kenneth A. Shepsle
Keyword(s):  
Political Theory ◽  
Majority Rule ◽  
Institutional Arrangements ◽  
Lessons Learned ◽  
Lewis Carroll ◽  
Simple Majority ◽  
Simple Majority Rule ◽  
Technical Literature ◽  
Marquis De Condorcet ◽  
Charles Dodgson

Simple majority rule is badly behaved. This is one of the earliest lessons learned by political scientists in the positive political theory tradition. Discovered and rediscovered by theorists over the centuries (including, famously, the Majorcan Franciscan monk Raymon Llull in the thirteenth century, the Marquis de Condorcet in the eighteenth, the Reverend Charles Dodgson (Lewis Carroll) in the eighteenth, and Duncan Black in the twentieth), the method of majority rule cannot be counted on to produce a rational collective choice. In many circumstances (made precise in the technical literature), it is very likely (a claim also made precise) that whatever choice is produced will suffer the property of not being “best” in the preferences of all majorities: for any candidate alternative, there will always exist another alternative that some majority prefers to it. This chapter suggests that while a collection of preferences often cannot provide a collectively “best” choice, institutional arrangements, which restrict comparisons of alternatives, may allow majority rule to function more smoothly. That is, where equilibrium induced by preferences alone may fail to exist, institutional structure may induce stability.

An Evaluation of the Effectiveness of Image-based Texture Features Extracted from Static B-mode Ultrasound Images in Distinguishing between Benign and Malignant Ovarian Masses

2021 ◽  
pp. 016173462199809
Author(s):  
Dhurgham Al-karawi ◽  
Hisham Al-Assam ◽  
Hongbo Du ◽  
Ahmad Sayasneh ◽  
Chiara Landolfo ◽  
...  
Keyword(s):  
Gabor Filter ◽  
Empirical Evaluation ◽  
Texture Features ◽  
Image Texture ◽  
Support Vector ◽  
Simple Majority ◽  
Ultrasound Scan ◽  
Histograms Of Oriented Gradients ◽  
The Individual ◽  
Ovarian Masses

Significant successes in machine learning approaches to image analysis for various applications have energized strong interest in automated diagnostic support systems for medical images. The evolving in-depth understanding of the way carcinogenesis changes the texture of cellular networks of a mass/tumor has been informing such diagnostics systems with use of more suitable image texture features and their extraction methods. Several texture features have been recently applied in discriminating malignant and benign ovarian masses by analysing B-mode images from ultrasound scan of the ovary with different levels of performance. However, comparative performance evaluation of these reported features using common sets of clinically approved images is lacking. This paper presents an empirical evaluation of seven commonly used texture features (histograms, moments of histogram, local binary patterns [256-bin and 59-bin], histograms of oriented gradients, fractal dimensions, and Gabor filter), using a collection of 242 ultrasound scan images of ovarian masses of various pathological characteristics. The evaluation examines not only the effectiveness of classification schemes based on the individual texture features but also the effectiveness of various combinations of these schemes using the simple majority-rule decision level fusion. Trained support vector machine classifiers on the individual texture features without any specific pre-processing, achieve levels of accuracy between 75% and 85% where the seven moments and the 256-bin LBP are at the lower end while the Gabor filter is at the upper end. Combining the classification results of the top k ( k = 3, 5, 7) best performing features further improve the overall accuracy to a level between 86% and 90%. These evaluation results demonstrate that each of the investigated image-based texture features provides informative support in distinguishing benign or malignant ovarian masses.

The Revision Acetabulum: Dealing With Bone Loss: Cementless Socket Revision: The Majority Rules

Orthopedics ◽  
2000 ◽  
Vol 23 (9) ◽  
pp. 967-968
Author(s):  
Aaron G Rosenberg
Keyword(s):  
Bone Loss ◽  
Majority Rules

Preference–Approval Structures in Group Decision Making: Axiomatic Distance and Aggregation

2021 ◽  
Author(s):  
Yucheng Dong ◽  
Yao Li ◽  
Ying He ◽  
Xia Chen
Keyword(s):  
Decision Making ◽  
Group Decision Making ◽  
Distance Function ◽  
Group Decision ◽  
Simple Majority ◽  
Simulation Experiments ◽  
Group Preference ◽  
Aggregation Model ◽  
Modeling Process ◽  
Ordinal Preference

Preference–approval structure combines the preference information of both ranking and approval, which extends the ordinal preference model by incorporating two categories of choice alternatives, that is, acceptable (good) and unacceptable (bad), in the preference modeling process. In this study, we present some axioms that imply the existence of a unique distance function of preference–approval structures. Based on theoretical analysis and simulation experiments, we further study a preferences aggregation model in the group decision-making context based on the proposed axiomatic distance function. In this model, the group preference is defined as a preference–approval structure that minimizes the sum of its distances to all preference–approval structures of individuals in the group under consideration. Particularly, we show that the group preference defined by the axiomatic distance–based aggregation model has close relationships with the simple majority rule and Cook and Seiford’s ranking.

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