长三角地区农民资金互助合作社运行满意度及影响因素分析 ——以泰州市苏陈资金互助合作社为例

农民资金互助合作社是目前准新型农村金融机构在长三角地区的典型代表。基于对江苏省泰州市苏陈资金互助合作社的实地调研,重点考察社员对样本农民资金互助合作社运行的满意度及影响因素。研究发现：样本社社员对于农民资金互助合作社的整体运行情况基本持肯定态度;社员的家庭总收入、政府对农民资金互助合作社的支持力度以及社员在农民资金互助合作社借用的互助金额度,是影响社员对于农民资金互助合作社满意度的主要因素;农民资金互助合作社融资业务的开展,对于社员的农业和二三产业经营均具有正向促进作用;农民资金互助合作社的互助金投放的覆盖面与农村信用合作社等传统农村正规金融机构形成了互补关系。在此基础上,提出了相关政策建议。     

对译入译出的文化思考

从理论上说中国人可以进行中译英,但事实表明对外译出并不成功。此外,什么人适合译出、译什么、以什么方式译出值得思考。因此,就目前情况看,中国应以译入为主,要成为真正意义上的翻译输出国尚需时日。     

Zero-inflated sum of Conway-Maxwell-Poissons (ZISCMP) regression

While excess zeros are often thought to cause data over-dispersion (i.e. when the variance exceeds the mean), this implication is not absolute. One should instead consider a flexible class of distributions that can address data dispersion along with excess zeros. This work develops a zero-inflated sum-of-Conway-Maxwell-Poissons (ZISCMP) regression as a flexible analysis tool to model count data that express significant data dispersion and contain excess zeros. This class of models contains several special case zero-inflated regressions, including zero-inflated Poisson (ZIP), zero-inflated negative binomial (ZINB), zero-inflated binomial (ZIB), and the zero-inflated Conway-Maxwell-Poisson (ZICMP). Through simulated and real data examples, we demonstrate class flexibility and usefulness. We further utilize it to analyze shark species data from Australia's Great Barrier Reef to assess the environmental impact of human action on the number of various species of sharks.     

Improved two-parameter estimators for the negative binomial and Poisson regression models

Negative binomial regression (NBR) and Poisson regression (PR) applications have become very popular in the analysis of count data in recent years. However, if there is a high degree of relationship between the independent variables, the problem of multicollinearity arises in these models. We introduce new two-parameter estimators (TPEs) for the NBR and the PR models by unifying the two-parameter estimator (TPE) of Özkale and Kaç?ranlar [The restricted and unrestricted two-parameter estimators. Commun Stat Theory Methods. 2007;36:2707–2725]. These new estimators are general estimators which include maximum likelihood (ML) estimator, ridge estimator (RE), Liu estimator (LE) and contraction estimator (CE) as special cases. Furthermore, biasing parameters of these estimators are given and a Monte Carlo simulation is done to evaluate the performance of these estimators using mean square error (MSE) criterion. The benefits of the new TPEs are also illustrated in an empirical application. The results show that the new proposed TPEs for the NBR and the PR models are better than the ML estimator, the RE and the LE.     

Kernel density estimation under negative superadditive dependence and its application for real data

In this paper, the kernel density estimator for negatively superadditive dependent random variables is studied. The exponential inequalities and the exponential rate for the kernel estimator of density function with a uniform version, over compact sets are investigated. Also, the optimal bandwidth rate of the estimator is obtained using mean integrated squared error. The results are generalized and used to improve the ones obtained for the case of associated sequences. As an application, FGM sequences that fulfil our assumptions are investigated. Also, the convergence rate of the kernel density estimator is illustrated via a simulation study. Moreover, a real data analysis is presented.     

Macro-Economic Factors in Credit Risk Calculations: Including Time-Varying Covariates in Mixture Cure Models

The prediction of the time of default in a credit risk setting via survival analysis needs to take a high censoring rate into account. This rate is because default does not occur for the majority of debtors. Mixture cure models allow the part of the loan population that is unsusceptible to default to be modeled, distinct from time of default for the susceptible population. In this article, we extend the mixture cure model to include time-varying covariates. We illustrate the method via simulations and by incorporating macro-economic factors as predictors for an actual bank dataset.     

Analysing facilitating and hindering factors for implementing gender equality interventions in R&I: Structures and processes

This article analyses the facilitating and hindering factors that have affected the implementation of gender equality interventions in research and innovation in Europe. It applies the evaluation framework developed in the EFFORTI project that recognizes the complexity of evaluating gender equality interventions in R&I, the importance of factoring in context to any sound evaluation as well as the need to distinguish between the design and implementation of interventions in evaluations. It is based on the analysis of 19 empirical case studies carried out throughout Europe and focuses on those structural and procedural factors that have either facilitated or hindered the implementation process of these interventions. Findings include how the governance framework; top-management commitment; bottom-up participation; framing synergies with other initiatives, strategies for tackling resistance; resources; sustainability of actions; gender competence, experience and knowledge and transparency, targets, standards and monitoring; and accessible data and information all contributed to the successful implementation of the interventions.     

What are you thinking? Acculturation as an activating event for negative evaluative beliefs among Latinos/as

Negative evaluative beliefs and other cognitive structures have been tied to psychological distress across various populations but have not been sufficiently incorporated into acculturation models. The current study examines the relationships between acculturation and various activating events and mediating sources of support related to negative evaluative beliefs among people of Mexican descent (N = 319). Overall, model variables explained 26% of the variance in negative evaluative beliefs. Acculturation, marital commitment, and social capital associated with friends were negatively related to negative evaluative beliefs. Conversely, single relationship status, marital reward value, psychosocial stressors, and bridging social capital were positively related, and likely serve as activating events for negative evaluative beliefs. Identifying mechanisms related to psychological distress as well as supportive structures may help in constructing interventions that will address the specific needs of different groups. Future research should continue to explore appraisal and associated beliefs in acculturation models to understand why acculturative experiences may become stressful.     

Risk factors for child maltreatment in South Korea: An investigation of a nationally representative sample

This study investigated the risk factors associated with the occurrence of child physical and psychological abuse in South Korea based on the ecological theory of child maltreatment. A subsample of 3‐ to 18‐year‐old children from “A Study on the Current State of Child Abuse and Neglect,” a nationally representative study on child abuse and neglect, was utilized for secondary data analysis. The sample was divided into two age groups (third graders in elementary school and below and fourth graders and above). We utilized hierarchical logistic regression for each age group separately to analyze the data. The variables at each level of the system (i.e., ontogenic development, microsystem, and exosystem) were entered into the model in sequential order. The results showed the common risk factors for both age groups are the caregiver's experience of abuse in childhood, the child's problem behavior, exposure to domestic violence, community size, and informal social control. The child's age was also significant in both groups but in the opposite direction. Social support was a significant predictor for the younger age group only, while the caregiver's level of education was significant for the older age group only. Implications for future research and practice are discussed based on the study results.     

Modeling stereotypes and negative self‐stereotypes as a function of interactions among groups with power asymmetries

Stereotypes is one of the most researched topics in social psychology. Within this context, negative self‐stereotypes pose a particular challenge for theories. In the current work, we propose a model that suggests that negative self‐stereotypes can theoretically be accounted for by the need to communicate in a social system made up by groups with unequal power. Because our theory is dynamic, probabilistic, and interactionist, we use a computational simulation technique to show that the proposed model is able to reproduce the phenomenon of interest, to provide novel accounts of related phenomena, and to suggest novel empirical predictions. We describe our computational model, our variables' dynamic behavior and interactions, and link our analyses to the literature on stereotypes and self‐stereotypes, the stability of stereotypes (in particular, gender and racial stereotypes), the effects of power asymmetries, and the effects of intergroup contact.