Audience effects on solitary faces during imagery: Displaying to the people in your head

Subjects imagined situations in which they reported enjoying themselves either alone or with others. Electromyographic (EMG) activity was recorded bilaterally from regions overlying thezygomatic major muscles responsible for smiling. Controlling for equal rated happiness in the two conditions, subjects showed more smiling in high-sociality than low-sociality imagery. In confirming imaginary audience effects during imagery, these data corroborate hypotheses that solitary facial displays are mediated by the presence of imaginary interactants, and suggest caution in employing them as measures of felt emotion.Avery Gilbert and Amy Jaffey had compelling insights throughout the course of study. We thank Paul Ekman, Carroll Izard, and Paul Rozin for extensive comments on earlier drafts. We also thank Bernard Apfelbaum, Jon Baron, Janet Bavelas, John Cacioppo, Linda Camras, Dean Delis, Rob DeRubeis, Alan Fiske, Stephen Fowler, Greg McHugo, Harriet Oster, David Premack, W. John Smith, and David Williams for their valuable comments and suggestions.     

何时推进，何时退后

如何从不太重要的信息中找出重要的信息呢?在同老板的交往中通过了解他想从你那里了解什么,从而提前进行区分要达到企业所希望的结果,你需要依赖员工分享重要信息．提出他们在同客户、合作伙伴甚至是竞争对手的交往中形成的创意。但鼓励员工分享他们的深刻见解的同时．你也希望他们有自己的判断力。你不需要了解资料的所有细节。     

GM Foods and the Misperception of Risk Perception

Public opposition to genetically modified (GM) food and crops is widely interpreted as the result of the public's misperception of the risks. With scientific assessment pointing to no unique risks from GM crops and foods, a strategy of accurate risk communication from trusted sources has been advocated. This is based on the assumption that the benefits of GM crops and foods are self-evident. Informed by the interpretation of some qualitative interviews with lay people, we use data from the Eurobarometer survey on biotechnology to explore the hypothesis that it is not so much the perception of risks as the absence of benefits that is the basis of the widespread rejection of GM foods and crops by the European public. Some respondents perceive both risks and benefits, and may be trading off these attributes along the lines of a rational choice model. However, for others, one attribute-benefit-appears to dominate their judgments: the lexicographic heuristic. For these respondents, their perception of risk is of limited importance in the formation of attitudes toward GM food and crops. The implication is that the absence of perceived benefits from GM foods and crops calls into question the relevance of risk communication strategies for bringing about change in public opinion.     

南充市城区已婚育龄妇女二孩生育意愿研究

2018年4—5月在四川省南充市城区采用便利抽样,以已婚且未育或已育一个小孩的育龄妇女为研究对象,采用自制匿名问卷,以面对面的形式收集资料,了解实施全面二孩政策后南充市育龄妇女的生育意愿,为南充市的人口研究提供参考依据。在213名调查对象中,56人(26.3%)有二孩生育意愿,140人(65.7%)无二孩生育意愿,17人(8.0%)不确定是否生育二孩。南充市被调查者的理想子女个数均值为1.46,意愿子女个数均值为1.27。不同文化程度(χ2=7.512)、配偶月收入(χ2=12.641)、理想子女数(χ2=66.401)、一孩性别(χ2=5.441)的育龄妇女间二孩生育意愿差异有统计学意义(P<0.05)。Logistic回归分析显示,第一个孩子性别为女孩(OR=2.641,P=0.021)、丈夫月收入越高(OR=1.761,P=0.028)、理想子女数多于1个(OR=29.040,P<0.001)的育龄妇女更有意愿生育二孩。南充市城区二孩生育意愿处于较低水平,经济收入、理想子女数、一孩性别会影响育龄妇女的二孩生育意愿。全面二孩政策对于促进育龄妇女生育二孩的效应有限,应当建立相关的配套政策,以促进全面二孩政策的实施。     

Using Technology to Facilitate Collaboration in Community-Based Participatory Research (CBPR)

This study explores the use of Computer-Supported Collaborative Work (CSCW) technologies, by way of a computer-based system called iCohere. This system was used to facilitate collaboration conducting Community-Based Participatory Research (CBPR). Data was gathered from 13 members of a Community Collaborative Board (CCB). Analysis revealed that iCohere served the following functions: facilitating communication, providing a depository for information and resource sharing, and allowing for remote meeting attendance. Results indicated that while iCohere was useful in performing these functions, less expensive technologies had the potential to achieve similar goals if properly implemented. Implications for future research on CSCW systems and CBPR are discussed.     

The complexity of diversity and importance for equitable philanthropy

The current U.S. climate of racial and social injustice has prompted a renewed call for diverse and equitable ways to rethink community philanthropy. Community foundations are vehicles for community philanthropy which offer vast benefits for social improvement and community development. The board of directors ensures these organizations fulfill their mission, making decisions on funding priorities and holding the organization functionally and fiscally responsible. Drawing on constructs of diversity and representative bureaucracy and a case study of Florida community foundations, we suggest that diversity is understood in different ways and the presence of diverse board members may be linked to advancing the interests of diverse communities and in achieving outcomes that assist in the needs of certain social groups. Increased understanding of diversity can improve foundation and philanthropic effectiveness and bring broader social change by promoting equity and social justice among community‐based philanthropic organizations.     

MIMCA: multiple imputation for categorical variables with multiple correspondence analysis

We propose a multiple imputation method to deal with incomplete categorical data. This method imputes the missing entries using the principal component method dedicated to categorical data: multiple correspondence analysis (MCA). The uncertainty concerning the parameters of the imputation model is reflected using a non-parametric bootstrap. Multiple imputation using MCA (MIMCA) requires estimating a small number of parameters due to the dimensionality reduction property of MCA. It allows the user to impute a large range of data sets. In particular, a high number of categories per variable, a high number of variables or a small number of individuals are not an issue for MIMCA. Through a simulation study based on real data sets, the method is assessed and compared to the reference methods (multiple imputation using the loglinear model, multiple imputation by logistic regressions) as well to the latest works on the topic (multiple imputation by random forests or by the Dirichlet process mixture of products of multinomial distributions model). The proposed method provides a good point estimate of the parameters of the analysis model considered, such as the coefficients of a main effects logistic regression model, and a reliable estimate of the variability of the estimators. In addition, MIMCA has the great advantage that it is substantially less time consuming on data sets of high dimensions than the other multiple imputation methods.