Is the holocaust relevant to sociobiology?

Sociobiologists have emphasized that altruism and benevolent behavior are part of the genetic repertoire of most animals and certainly of man. They have constructed a theory of ethics as a biological phenomenon without reference to the concept of evil. It is concluded here however, that holocaust behavior is not equivalent to the natural manifestation of an incompletely tamed animal flashing its teeth. Biologists have been too rigid in trying to equate ethical behavior with social behavior. The added dimension of ethical behavior is a special kind of sensitivity to the needs of others, just as evil is the total lack of it. The evolution of this moral sense may itself have important selective value for the human species, whose survival depends on creating maximal diversity in its gene pool.     

What predicts anti‐Roma prejudice? Qualitative and quantitative analysis of everyday sentiments about the Roma

The present research focused on two primary goals: (a) identifying the content of sentiments about the Roma to which Hungarians are exposed during everyday family conversations, and (b) determining which types of everyday sentiments about the Roma most strongly predict Hungarian respondents’ anti‐Roma prejudice. Content analyzing open‐ended responses from a representative sample of Hungarians (N = 505), we found that more than 76% of the respondents reported being exposed to negative stereotypes about the Roma, 27% to threats posed by Roma, and 16% to overt dehumanization of Roma; additionally more than 20% reported hearing no positive sentiments about the Roma in everyday family conversations. We then examined which negative and positive sentiments most strongly predicted respondents’ anti‐Roma prejudice (using measures of social distance and modern racism). Higher social distance scores were predicted by a lack of positive sentiments, whereas lower social distance scores were most strongly predicted by unambiguously positive sentiments expressed during family conversations. Higher modern racism scores were further predicted by sentiments expressing dehumanization, threat, and violence against Roma. Together, these results attest to the extremity of anti‐Roma sentiments expressed regularly by Hungarians, and suggest how exposure to specific sentiments may foster anti‐Roma hostility. Moreover, these findings provide guidance regarding the specific negative anti‐Roma sentiments that should be combated to enhance the effectiveness of anti‐prejudice interventions.     

Children's academic attainment is linked to the global organization of the white matter connectome

Literacy and numeracy are important skills that are typically learned during childhood, a time that coincides with considerable shifts in large‐scale brain organization. However, most studies emphasize focal brain contributions to literacy and numeracy development by employing case‐control designs and voxel‐by‐voxel statistical comparisons. This approach has been valuable, but may underestimate the contribution of overall brain network organization. The current study includes children (N = 133 children; 86 male; mean age = 9.42, SD = 1.715; age range = 5.92–13.75y) with a broad range of abilities, and uses whole‐brain structural connectomics based on diffusion‐weighted MRI data. The results indicate that academic attainment is associated with differences in structural brain organization, something not seen when focusing on the integrity of specific regions. Furthermore, simulated disruption of highly‐connected brain regions known as hubs suggests that the role of these regions for maintaining the architecture of the network may be more important than specific aspects of processing. Our findings indicate that distributed brain systems contribute to the etiology of difficulties with academic learning, which cannot be captured using a more traditional voxel‐wise statistical approach.     

Improving fairness in coverage decisions: performance expectations for quality improvement

Patients and physicians often perceive the current health care system to be unfair, in part because of the ways in which coverage decisions appear to be made. To address this problem the Ethical Force Program, a collaborative effort to create quality improvement tools for ethics in health care, has developed five content areas specifying ethical criteria for fair health care benefits design and administration. Each content area includes concrete recommendations and measurable expectations for performance improvement, which can be used by those organizations involved in the design and administration of health benefits packages, such as purchasers, health plans, benefits consultants, and practitioner groups.     

Ethical guidelines for use of electronic mail between patients and physicians

This report examines the ethical implications of electronic communication, focusing on the use of electronic mail (e-mail), considers its impact on a previously established patient-physician relationship, and the limitations in using e-mail to create a new patient-physician relationship. In its recommendations, this report offers guidance to physicians who use electronic mail to communicate with patients and online users. These guidelines maintain that e-mail should not be used to establish a patient-physician relationship, but rather to supplement personal encounters. When using e-mail, physicians hold the same ethical responsibilities to their patients as they do during other encounters and that information must be presented in a manner that meets professional standards. The report requires that physicians notify patients of e-mail's inherent limitations and that patients be given the opportunity to accept these limitations prior to the communication of privileged information. Finally, physicians should be aware of privacy and confidentiality concerns when using e-mail to communicate with patients.     

成人日常问题解决的老化研究

日常问题解决能力是近十几年来老年心理学中研究比较活跃的一个领域。本文介绍了有关日常问题解决研究的四种理论,即心理测量的智力内隐理论、形式后思维的辨证思维理论、信息加工理论和社会认知与智慧理论,及其初步的研究成果,并进一步指出在理论上整合和在实践中开展干预的研究方向。     

Towards end-to-end likelihood-free inference with convolutional neural networks

Complex simulator-based models with non-standard sampling distributions require sophisticated design choices for reliable approximate parameter inference. We introduce a fast, end-to-end approach for approximate Bayesian computation (ABC) based on fully convolutional neural networks. The method enables users of ABC to derive simultaneously the posterior mean and variance of multidimensional posterior distributions directly from raw simulated data. Once trained on simulated data, the convolutional neural network is able to map real data samples of variable size to the first two posterior moments of the relevant parameter's distributions. Thus, in contrast to other machine learning approaches to ABC, our approach allows us to generate reusable models that can be applied by different researchers employing the same model. We verify the utility of our method on two common statistical models (i.e., a multivariate normal distribution and a multiple regression scenario), for which the posterior parameter distributions can be derived analytically. We then apply our method to recover the parameters of the leaky competing accumulator (LCA) model and we reference our results to the current state-of-the-art technique, which is the probability density estimation (PDA). Results show that our method exhibits a lower approximation error compared with other machine learning approaches to ABC. It also performs similarly to PDA in recovering the parameters of the LCA model.