Minimizing inequality versus maximizing joint gains: On the relation between personality traits and different prosocial motivations

The Social Value Orientation (SVO) Slider Measure allows a differentiation between two prosocial motivations: minimizing inequality versus maximizing joint gains. In two studies (N = 1202), we investigated the relation between this suggested continuum from Inequality Aversion (IA) to Joint Gain Maximization (JGM), the HEXACO personality dimensions, and SVO. To account for differences in fairness perception, we also considered whether inequality favored oneself or the other. As hypothesized, Honesty-Humility was the best basic trait predictor of IA, showing a slightly stronger positive link when inequality was self-advantageous. SVO, in turn, showed a stronger (negative) link when inequality was disadvantageous for the self. Overall, the results show that IA is related to (basic) personality traits in a theoretically meaningful way.     

Les limites de l’approche fondée sur le risque de la loi du 5 mars 2012 relative aux recherches impliquant la personne humaine,dite « loi Jardé »: Lecture critique des arrêtés du 12 avril 2018

Thanks to the publication of the two decrees of 12 April 2018, and six years after the promulgation of the Jardé law, the scope of the law of 5 March 2012 as well as the different categories of research involving the human person finally appear clearly. Beside interventional research that includes intervention on the person that is not justified by usual care, the contours of two categories of research have been precised: interventional research with minimal risk and minimal burden and “non-interventional” research, whose name is questionable. If the latest decrees have managed to reach a more coherent set of rules, the French legal and regulatory provisions remain complex and incomplete. Complex, in view of the multiplicity of statutory texts adopted since the promulgation of the Jardé law. Incomplete, because the needs for ethical evaluation provided for by the international ethical principles of research are not systematically covered by French law.     

Rolling element bearing fault diagnosis using convolutional neural network and vibration image

Detecting in prior bearing faults is an essential task of machine health monitoring because bearings are the vital components of rotary machines. The performance of traditional intelligent fault diagnosis methods depend on feature extraction of fault signals, which requires signal processing techniques, expert knowledge, and human labor. Recently, deep learning algorithms have been applied widely in machine health monitoring. With the capacity of automatically learning complex features of input data, deep learning architectures have great potential to overcome drawbacks of traditional intelligent fault diagnosis. This paper proposes a method for diagnosing bearing faults based on a deep structure of convolutional neural network. Using vibration signals directly as input data, the proposed method is an automatic fault diagnosis system which does not require any feature extraction techniques and achieves very high accuracy and robustness under noisy environments.     

Feature selection using Ant Colony Optimization (ACO) and Road Sign Detection and Recognition (RSDR) system

Road Sign Detection and Recognition (RSDR) is aimed to enable drivers maintain basic functionality with the aim of identifying and notifying driver through the existing restrictions so that the process is a success on the present widened road. Examples for RSDR include ‘traffic light ahead’ or ‘pedestrian crossing’ signs. An innovative RSDR system has been introduced which comprises of pre-processing, edge detection, feature extraction, features selection and Ensemble Fuzzy Support Vector Machine (EFSVM) classifier. Feature selection is carried out successfully by deployment of Ant Colony Optimization (ACO) algorithm to determine most prominent and definitive features. These features are then fed into the ensemble SVM to enable both road side traffic detection as well as recognition. Suggested system’s performance is analyzed and evaluated with respect to road signs having a capable recognition rate.     

伦理型领导影响员工建言的多重中介效应比较研究

采用问卷调查法,对244名企业员工进行调查,构建了伦理型领导对员工建言行为的多重中介模型,比较建言效能感、心理安全感与上下级关系的个别中介效应。结果显示:伦理型领导通过建言效能感、心理安全感与上下级关系的并行多重中介作用对员工建言行为产生影响;建言效能感与心理安全感的个别中介效应均显著大于上下级关系,建言效能感与心理安全感的中介效应无显著差异。     

社会支配倾向研究的回顾与展望

社会支配倾向指个体对基于群体产生的等级制度及社会存在不平等现象的偏好程度。高社会支配倾向者认为高能力者应比低能力者获得更多的社会权利与社会资源;低社会支配倾向者认为社会应该按需分配,不存在等级差异。社会支配倾向会对社会阶层、偏见、政治态度、公平等现象的作用产生影响,是这些现象的重要影响因素。今后需要立足于社会支配倾向的本质与社会应用开展整合性研究。     

Political consumer behaviour among university students in Brazil and Germany: The role of contextual features and core political values

This study investigates the relationship between political consumerism and core political values (CPVs) among university students in Brazil (N = 414) and Germany (N = 222). Despite the prerequisite to endorse values that are compatible with political consumerism, contextual features of one's immediate environment might affect overall levels of political consumerism. Our results show that political consumerism is significantly associated with higher income in Brazil (but not in Germany). After controlling for income, political consumerism was practised more frequently in Germany than in Brazil, in urban compared with rural areas, and was not dependent on gender. The urban–rural split was stronger in Brazil than in Germany. These results confirm our hypothesis that contextual features are associated with political consumerism. Furthermore, the political value Equality positively predicted political consumerism in both countries. In contrast, Traditional Morality and support of Free Enterprise negatively predicted political consumerism, although the effect sizes of these relationships were only small. These results suggest that political consumerism among university students is widespread in Germany but not in Brazil. Interestingly, regardless of its low prevalence in Brazil, political consumerism is positively associated with the CPV of Equality among university students in both countries.     

The Stories We Tell: Introduction to the Special Issue on Ethical Challenges in Community Psychology Research and Practice

This Special Issue examines ethical challenges in community psychology research and practice. The literature on ethics in community psychology has remained largely abstract and aspirational, with few concrete examples and case studies, so the goal of this Special Issue was to expand our written discourse about ethical dilemmas in our field. In these articles, researchers and practitioners share stories of specific ethical challenges they faced and how they sought to resolve them. These first‐person narratives examine how ethical challenges come about, how community psychology values inform ethical decision making, and how lessons learned from these experiences can inform an ethical framework for community psychology.     

Contrastive Constraints Guide Explanation‐Based Category Learning

This paper provides evidence for a contrastive account of explanation that is motivated by pragmatic theories that recognize the contribution that context makes to the interpretation of a prompt for explanation. This study replicates the primary findings of previous work in explanation‐based category learning (Williams & Lombrozo, 2010), extending that work by illustrating the critical role of the context in this type of learning. Participants interacted with items from two categories either by describing the items or explaining their category membership. We manipulated the feature overlap between the categories and examined both the explanations generated and acquired knowledge of the categories. Explanations for membership in a given category were influenced by the unprompted contrast category, indicating an important role for contrastive processing in the generation of explanations. The influence of the contrast category was similarly seen in the transfer performance of the participants.     

EEG and fMRI agree: Mental arithmetic is the easiest form of imagery to detect

fMRI and EEG during mental imagery provide alternative methods of detecting awareness in patients with disorders of consciousness (DOC) without reliance on behaviour. Because using fMRI in patients with DOC is difficult, studies increasingly employ EEG. However, there has been no verification that these modalities provide converging information at the individual subject level. The present study examined simultaneous EEG and fMRI in healthy volunteers during six mental imagery tasks to determine whether one mental imagery task generates more robust activation across subjects; whether activation can be predicted from familiarity with the imagined activity; and whether EEG and fMRI converge upon the same conclusions about individual imagery performance. Mental arithmetic generated the most robust activation in the majority of subjects for both EEG and fMRI, and level of activation could not be predicted from familiarity, with either modality. We conclude that overall, EEG and fMRI agree regarding individual mental imagery performance.