Majority Voting Rule Research Articles

A characterization of majority voting rules with quorums

We give a characterization of majority voting rules with quorums in the framework of May (Econometrica 20:680–684, 1952)’s seminal article. According to these voting rules, an alternative is socially chosen if and only if it obtains the relative majority of votes and the total number of voters not abstaining reaches the quorum.

A Theory of Corporate Boards with Endogenous Information Collection, Optimal Compensation and Strategic Voting: When Do Independent Boards Dominate Rubberstamping Ones?

This paper presents a model of the collective decision making of corporate boards. Each director collects costly private information and votes to maximize his welfare given his compensation. We derive optimal contracts that induce first-best outcomes for shareholders despite directors' incentive to free-ride on each others' information and votes. Our model highlights important frictions between information collection and information sharing, and between board accountability and independence. We identify conditions under which a rubber-stamping or captive board achieve higher shareholder value than an independent or active board and conditions under which the reverse is true. Our findings hold whether board decisions are made through majority, supermajority or unanimity voting rules and whether balloting is open or secret.

Automatic segmentation of the prostate in 3D MR images by atlas matching using localized mutual information

An automatic method for delineating the prostate (including the seminal vesicles) in three-dimensional magnetic resonance scans is presented. The method is based on nonrigid registration of a set of prelabeled atlas images. Each atlas image is nonrigidly registered with the target patient image. Subsequently, the deformed atlas label images are fused to yield a single segmentation of the patient image. The proposed method is evaluated on 50 clinical scans, which were manually segmented by three experts. The Dice similarity coefficient (DSC) is used to quantify the overlap between the automatic and manual segmentations. We investigate the impact of several factors on the performance of the segmentation method. For the registration, two similarity measures are compared: Mutual information and a localized version of mutual information. The latter turns out to be superior (median DeltaDSC approximately equal 0.02, p < 0.01 with a paired two-sided Wilcoxon test) and comes at no added computational cost, thanks to the use of a novel stochastic optimization scheme. For the atlas fusion step we consider a majority voting rule and the "simultaneous truth and performance level estimation" algorithm, both with and without a preceding atlas selection stage. The differences between the various fusion methods appear to be small and mostly not statistically significant (p > 0.05). To assess the influence of the atlas composition, two atlas sets are compared. The first set consists of 38 scans of healthy volunteers. The second set is constructed by a leave-one-out approach using the 50 clinical scans that are used for evaluation. The second atlas set gives substantially better performance (DeltaDSC=0.04, p < 0.01), stressing the importance of a careful atlas definition. With the best settings, a median DSC of around 0.85 is achieved, which is close to the median interobserver DSC of 0.87. The segmentation quality is especially good at the prostate-rectum interface, where the segmentation error remains below 1 mm in 50% of the cases and below 1.5 mm in 75% of the cases.

Majority rule when voters like to win

I analyze symmetric majority rule voting equilibria when voters wish to elect the better candidate and to vote for the winner. When voters care only about the winning candidate (the standard formulation) a unique responsive equilibrium exists. The addition of a desire to win creates multiple equilibria, some with unusual properties. In most of these equilibria information is not aggregated effectively, and I uncover the novel possibility of negative information aggregation in which information aggregated in equilibrium is used to select the worse rather than the better candidate. I then characterize the efficiency of optimal equilibria as the population becomes large and show that a discontinuity arises in the information aggregation capabilities of the majority rule voting mechanism: in elections without a dominant front-running candidate the better candidate is almost surely elected, whereas in races with a front-runner information cannot be effectively aggregated in equilibrium.

Local binary pattern and wavelet-based spoof fingerprint detection

Perspiration phenomenon is very significant to detect liveness of a finger. It requires two consecutive fingerprints to notice perspiration and therefore the method is slow. Some other methods in the literature need extra hardware to detect liveness. To alleviate these problems, in this paper, a new texture-based method which needs only one fingerprint is proposed. It is based on the observation that, real and spoof fingerprints exhibit different textural characteristics. Local binary pattern (LBP) histograms are used to capture these textural details. Wavelet energy features characterising ridge frequency and orientation information are also used for improving the efficiency of the proposed method. Dimensionalities of the feature sets are reduced by running sequential forward floating selection (SFFS). LBP features and wavelet energy features are independently tested on various classifiers: AdaBoost.M1, support vector machine and k-nearest neighbour. Features are also tested on a hybrid classifier formed by fusing all the mentioned earlier classifiers by the 'majority voting rule'. Fingerprint databases consisting of 185 real, 90 fun-doh and 150 gummy fingerprints are created. Experimental results indicate that, the performance of new liveness detection approach is very promising, as it needs only one fingerprint and no extra hardware to detect vitality.

Design of a multi-classifier system for discriminating benign from malignant thyroid nodules using routinely H&E-stained cytological images

A multi-classifier diagnostic system was designed for distinguishing between benign and malignant thyroid nodules from routinely taken (FNA, H&E-stained) cytological images. To construct the multi-classifier system, several combination rules and different mixtures of ensemble classifier members, employing morphological and textural nuclear features, were comparatively evaluated. Experimental results illustrated that the classifier combination k-NN/PNN/Bayesian and the majority vote rule enhanced significantly classification accuracy (95.7%) as compared to best single classifier (PNN: 89.6%). The proposed system was designed with purpose to be utilized in daily clinical practice as a second opinion tool to support cytopathologists’ decisions, when a definite diagnosis is difficult to be obtained.

A Scheme to Determine Tax Rates Fairly and Quantitatively

Abstract. This article discusses a scheme to quantitatively determine a personal income tax rate structure based on the principle of democratic voting. Previous attempts to apply the majority voting rule largely call for voting on predetermined tax positions. In the approach presented here, each taxpayer proposes an egocentric rate system encompassing his or her own obligation as well as all other taxpayers' under generally accepted constraints. The egocentric rate systems proposed by all taxpayers are weight‐averaged to determine the actual tax obligation for all taxpayers. The weights used for the average are in general proportional to the tax contribution. The rate structure can be quantitatively determined from solving simultaneous equations if the weights are predetermined. Although there are an infinite number of choices for the weights, it is argued that the “fair” manner of averaging ranges from equal representation by all taxpayers to equal representation by all tax contributions. An appropriate rate structure should be a linear combination of the tax rates derived from the two limiting scenarios. Alternative egocentric voting schemes under equal representation by all taxpayers are also discussed. While these alternative schemes are politically more acceptable, measures need to be taken to counterbalance the confiscating nature desired by the majority of the voters. Such measures may marginalize the democratic voting process and produce rate structures less progressive than those assuming equal representation of tax contributions. Although the method discussed here allows flexibility on the marginal rate progressivity, it sets the high limit that the lowest and highest income classes ought to pay.

From dynamic classifier selection to dynamic ensemble selection

In handwritten pattern recognition, the multiple classifier system has been shown to be useful for improving recognition rates. One of the most important tasks in optimizing a multiple classifier system is to select a group of adequate classifiers, known as an Ensemble of Classifiers (EoC), from a pool of classifiers. Static selection schemes select an EoC for all test patterns, and dynamic selection schemes select different classifiers for different test patterns. Nevertheless, it has been shown that traditional dynamic selection performs no better than static selection. We propose four new dynamic selection schemes which explore the properties of the oracle concept. Our results suggest that the proposed schemes, using the majority voting rule for combining classifiers, perform better than the static selection method.

Intergenerational risk shifting through social security and bailout politics

Abstract This paper adopts a stochastic overlapping generations framework to analyze the allocation of aggregate financial risks under different social security systems and a majority voting rule. We study whether there will be switches between pay-as-you-go (PAYG) and fully funded (FF) systems in such an economy. We show that in case of a negative aggregate shock, low-income young individuals will form a political coalition with the elderly to implement a PAYG system. PAYG scheme is shown to persist even after a good aggregate shock if the system is redistributive enough.

Texture analysis of tissue surrounding microcalcifications on mammograms for breast cancer diagnosis

Diagnosis of microcalcifications (MCs) is challenged by the presence of dense breast parenchyma, resulting in low specificity values and thus in unnecessary biopsies. The current study investigates whether texture properties of the tissue surrounding MCs can contribute to breast cancer diagnosis. A case sample of 100 biopsy-proved MC clusters (46 benign, 54 malignant) from 85 dense mammographic images, included in the Digital Database for Screening Mammography, was analysed. Regions of interest (ROIs) containing the MCs were pre-processed using a wavelet-based contrast enhancement method, followed by local thresholding to segment MCs; the segmented MCs were excluded from original image ROIs, and the remaining area (surrounding tissue) was subjected to texture analysis. Four categories of textural features (first order statistics, co-occurrence matrices features, run length matrices features and Laws' texture energy measures) were extracted from the surrounding tissue. The ability of each feature category in discriminating malignant from benign tissue was investigated using a k-nearest neighbour (kNN) classifier. An additional classification scheme was performed by combining classification outputs of three textural feature categories (the most discriminating ones) with a majority voting rule. Receiver operating characteristic (ROC) analysis was conducted for classifier performance evaluation of the individual textural feature categories and of the combined classification scheme. The best performance was achieved by the combined classification scheme yielding an area under the ROC curve (A(z)) of 0.96 (sensitivity 94.4%, specificity 80.0%). Texture analysis of tissue surrounding MCs shows promising results in computer-aided diagnosis of breast cancer and may contribute to the reduction of unnecessary biopsies.

A Theory of Organizational Dynamics: Internal Politics and Efficiency

In this paper, we develop a stylized model to study how internal politics affects an organization's hiring of new members and investigate the implications of the dynamic interactions between internal politics and hiring of new members on the organization's long run outcomes and welfare. We consider an organization with a fixed size in which one of the incumbent members retires in each period and the incumbent members vote to admit a candidate to fill the vacancy. Agents differ by quality that is valued equally by every member in the organization. In addition, each agent belongs to one of the two types, where members of the majority type in any period control the rent distribution of the organization and share the total rent of that period among themselves. We characterize the conditions for a Markov equilibrium of the dynamic game, and the long run equilibrium outcome and welfare. Then we solve the model of a three member club with uniformly distributed quality, under both majority and unanimity voting rule in admitting new Among other things, we find that some politics can be a good thing if it is done right, in that under certain conditions the club achieves greater total welfare in the long run in the presence of internal politics than when internal politics is absent, if unanimity voting rule is used to admit new members. Moreover, too much politics is surely a bad thing, in that the club obtains low welfare in the long run when politics becomes very intense. In that case, majority voting rule is better than unanimity voting rule because the club can suffer more welfare loss from politics under unanimity voting.

Stability in Spatial Voting Games with Restricted Preference Maximizing

Spatial models of simple majority rule voting suggest that stable decisions are not likely to exist under normal circumstances. Yet this instability result stands in contrast to the stability observed in experiments. This article examines the effect of relaxing the assumption that voting is costless by requiring a proposal to be a finite distance closer to a member’s ideal point than the pending proposal before it is regarded as attractive. Using the concept of the epsilon-core the article estimates the minimal decision costs that guarantee stable outcomes. It shows that the minimal costs are equal to the minimal finagle radius (Wuffle et al., 1989) and that the epsilon-core contains the finagle point which is close to the center of the yolk. While the analytical model establishes that the minimal costs are smaller than the yolk radius, computational simulations of majority voting by committees of size 3 to 101 suggest that this is a weak upper bound, only, as the ratio of minimal costs to the yolk radius usually is small and decreases as committee size approaches infinity.

Enlargement and the balance of power: an experimental study

Theoretical analysis suggests that enlargement of a voting body may affect the balance of power between the original members even if their number of votes and the decision rule remain constant. Some of the existing voters may actually gain, a phenomenon known as the paradox of new members. We test for this effect using laboratory experiments. Participants propose and vote on how to divide a budget according to weighted majority voting rules, and we measure the voting power of a player by his average payoff in the experiment. By comparing voting power across voting bodies of varying size, we find empirical support for the paradox of new members.

Enlargement and the Balance of Power: An Experimental Study

Many important decisions are taken according to weighted majority rule. Power indices predict that enlargement of the voting body may affect the balance of power between the original members even if their number of votes and the decision rule remain constant. Some of the existing voters may actually gain, a phenomenon known as the paradox of new members. We test for this effect using laboratory experiments. Participants propose and vote on how to divide a budget according to weighted majority voting rules, and we measure the voting power of a player by his average payoff in the experiment. By comparing voting power across voting bodies of varying size, we find empirical support for the paradox of new members. Our results also allow an assessment of the predictive performance of standard power indices.

How independent should the board be? Corporate board structure from a voting perspective

This paper proposes a model of corporate voting in which private information and individual preferences of board directors drive the board decisions. The optimal board structure and optimal firm value are solved numerically and their dependence on director and firm characteristics are studied. The optimal board structure is determined by outside and inside directors’ relative unforcedness about the firm, insiders’ bias, outsiders’ advisory ability as well as the characteristics of the projects that the firm have. Voting rules other than the majority voting rule are considered. It is found that the majority rule often is not the optimal rule and it is optimal for a firm to have more inside directors while adopting a tougher voting rule. By studying strategic voting equilibria theoretically, insights about how board directors vote strategically are also provided

Social Carrying Capacity of Mass Tourist Sites: Theoretical and Practical Issues about its Measurement

Congestion is an important management problem at mass tourist sites. This essay focuses on the social carrying capacity (SCC) of a tourist site as indicator of residents' and visitors' perception of crowding, intended as the maximum number of visitors (MNV) tolerated. In case of conflict between the residents' MNV tolerated and the visitors' MNV tolerated, the policy-maker has to mediate. We consider the case in which the residents' SCC is lower than the visitors' SCC, and the site SCC is the result of a compromise between these two aspects of the SCC. This can be measured by making reference to two criteria of choice: the utility maximisation criterion and the voting rule. The use of one method rather than the other depends on the data available about the individual preferences on crowding. Assuming that individual preferences are known, a maximisation model for the computation of the site SCC is conceived. It represents the case in which the residents' SCC is the limiting factor. The site SCC is intended as the number of visitors which maximises the social welfare function. Because a local policy-maker maximises the welfare of residents, in this model visitors are represented by those residents whose welfare wholly depends on the tourism sector, while the social costs due to crowding are borne by those residents who are partially or totally independent from tourism. Nevertheless, in practice, the individual preferences about crowding are not always known. In this case, the MNV tolerated can be computed by applying the majority voting rule. It is shown that, under certain conditions, the optimum number of visitors, obtained through a maximisation model, is equal to the MNV tolerated by the majority of voters.

A Gaussian Mixture Model Based Classification Scheme for Myoelectric Control of Powered Upper Limb Prostheses

This paper introduces and evaluates the use of Gaussian mixture models (GMMs) for multiple limb motion classification using continuous myoelectric signals. The focus of this work is to optimize the configuration of this classification scheme. To that end, a complete experimental evaluation of this system is conducted on a 12 subject database. The experiments examine the GMMs algorithmic issues including the model order selection and variance limiting, the segmentation of the data, and various feature sets including time-domain features and autoregressive features. The benefits of postprocessing the results using a majority vote rule are demonstrated. The performance of the GMM is compared to three commonly used classifiers: a linear discriminant analysis, a linear perceptron network, and a multilayer perceptron neural network. The GMM-based limb motion classification system demonstrates exceptional classification accuracy and results in a robust method of motion classification with low computational load.

Can Co-owners Agree to Disagree? A Theoretical Examination of Voting Rules in Co-ownerships

We analyze the optimal voting rule for co-owners whose future debates are resolved by voting. Each co-owner independently forms an ex ante expectation regarding the likelihood of each member to favor any arbitrary future proposal. We examine the conditions under which a co-owner optimally opts for unanimous, special majority, simple majority, and minority voting rules. Interestingly, it follows from our analysis that co-owners with distinct characteristics may yet unanimously agree on the optimal voting rule. Among the other results: the optimal level of the voting rule is non-decreasing (non-increasing) in one's level of disutility from opposing (favoring) an accepted (a rejected) proposal. Also, while our results are generally in line with the predictions of Ellickson (1982) and the evidence of Barzel and Sass (1990), according to which heterogeneous (homogeneous) voters require (less than) a super majority voting rule, we show a possible exception to this generalization, under which heterogeneity, in some circumstances, may optimally lead to a minority voting rule. The results are applicable for groups such as general assemblies in apartment buildings, neighborhood councils, and others.

Controlling firms through the majority voting rule

Pyramids, cross-ownership, rings and other complex features inducing control tunnelling are frequent in the European and Asian industrial world. Based on the matrix methodology, this paper offers a model for measuring integrated ownership and threshold-based control, applicable to any group of interrelated firms. In line with the theory on pyramidal control, the model avoids the double counting problem and sets the full control threshold at the conservative—but incontestable—majority level of 50% of the voting shares. Any lower threshold leads to potential inconsistencies and leaves the observed high level of ownership of many dominant shareholders unexplained. Furthermore, the models leads to ultimate shareholders’ control ratios consistent with the majority voting rule. Finally, it is applied to the Frère Group, a large European pyramidal holding company known for mastering control leverages.

Controlling Firms Through the Majority Voting Rule

Pyramids, cross-ownership, rings and other complex features inducing control tunnelling are frequent in the European and Asian industrial world. Based on the matrix methodology, this paper offers a model for measuring integrated ownership and threshold-based control, applicable to any group of interrelated firms. In line with the theory on pyramidal control, the model avoids the double counting problem and sets the full-control threshold at the conservative - but incontestable - majority level of 50% of the voting shares. Any lower threshold leads to potential inconsistencies and leaves unexplained the observed high level of ownership of many dominant shareholders. Furthermore, the models leads to ultimate shareholders' control ratios consistent with the majority voting rule. Finally, it is applied to the Frere Group, a large European pyramidal holding company known for mastering control leverages.