The duty to care and the need to split

This paper arises out of psychoanalytically oriented consultancy to teams of staff in the helping professions where there is a statutory 'duty to care'. It takes as its premise the seemingly paradoxical hypothesis that workers may need to split off part of their emotional experience in order to preserve their own mental health and provide reliable services to their clients. I argue that while a professional 'duty to care' requires us to be emotionally 'in touch', the demands of our clients together with the demands of the institutional response to the 'duty to care' cause us to split off parts of our awareness. I also argue that provided the splitting does not become extreme we are doing no more or less than the rest of society. In other words, there is a degree of 'normal splitting' which numbs our awareness of danger and destructiveness and seeks to protect us from too much anxiety and pain. Yet if professional workers are charged with the responsibility of assessing risk and acting accordingly for the protection of all concerned they need ways of being 'in touch' (re-integrating the splits) for some or enough of the time. Finally, I will describe ways of being 'in touch', illustrating the difficulty and the pain of re-integrating the splits and some of the insights that can arise out of this work with examples from my consultancy work.     

Communicating Conservation Status: How Different Statistical Assessment Criteria Affect Perceptions of Extinction Risk

Although alternative forms of statistical and verbal information are routinely used to convey species’ extinction risk to policymakers and the public, little is known about their effects on audience information processing and risk perceptions. To address this gap in literature, we report on an experiment that was designed to explore how perceptions of extinction risk differ as a function of five different assessment benchmarks (Criteria A–E) used by scientists to classify species within IUCN Red List risk levels (e.g., Critically Endangered, Vulnerable), as well as the role of key individual differences in these effects (e.g., rational and experiential thinking styles, environmental concern). Despite their normative equivalence within the IUCN classification system, results revealed divergent effects of specific assessment criteria: on average, describing extinction risk in terms of proportional population decline over time (Criterion A) and number of remaining individuals (Criterion D) evoked the highest level of perceived risk, whereas the single‐event probability of a species becoming extinct (Criterion E) engendered the least perceived risk. Furthermore, participants scoring high in rationality (analytic thinking) were less prone to exhibit these biases compared to those low in rationality. Our findings suggest that despite their equivalence in the eyes of scientific experts, IUCN criteria are indeed capable of engendering different levels of risk perception among lay audiences, effects that carry direct and important implications for those tasked with communicating about conservation status to diverse publics.     

Confidence distributions applied to propagating uncertainty to inference based on estimating the local false discovery rate: A fiducial continuum from confidence sets to empirical Bayes set estimates as the number of comparisons increases

Empirical Bayes estimates of the local false discovery rate can reflect uncertainty about the estimated prior by supplementing their Bayesian posterior probabilities with confidence levels as posterior probabilities. This use of coherent fiducial inference with hierarchical models generates set estimators that propagate uncertainty to varying degrees. Some of the set estimates approach estimates from plug-in empirical Bayes methods for high numbers of comparisons and can come close to the usual confidence sets given a sufficiently low number of comparisons.     

Bayesian analysis of multivariate stochastic volatility with skew return distribution

Multivariate stochastic volatility models with skew distributions are proposed. Exploiting Cholesky stochastic volatility modeling, univariate stochastic volatility processes with leverage effect and generalized hyperbolic skew t-distributions are embedded to multivariate analysis with time-varying correlations. Bayesian modeling allows this approach to provide parsimonious skew structure and to easily scale up for high-dimensional problem. Analyses of daily stock returns are illustrated. Empirical results show that the time-varying correlations and the sparse skew structure contribute to improved prediction performance and Value-at-Risk forecasts.     

The almost sure convergence rate of the estimator of optimized certainty equivalent risk measure under α-mixing sequences

Conditional value-at-risk (CVaR) model is a kind of financial risk measure that is extensively supported and accepted by international financial community. Its optimized form can be regarded as an optimized certainty equivalent (OCE) risk measurement. In this paper, we mainly discuss and analyze the strong laws of large numbers and the convergence rate of OCE's estimator under α-mixing sequences. The result shows that the almost sure convergence rate of CVaR estimator is given by the results of OCE estimator. Its convergence rate is inversely proportional to the square root of the sample size under certain conditions. Its effectiveness is verified by simulation experiments for two classical α-mixing sequences.     

An Integrated Risk Assessment Model of Township‐Scaled Land Subsidence Based on an Evidential Reasoning Algorithm and Fuzzy Set Theory

Land subsidence risk assessment (LSRA) is a multi‐attribute decision analysis (MADA) problem and is often characterized by both quantitative and qualitative attributes with various types of uncertainty. Therefore, the problem needs to be modeled and analyzed using methods that can handle uncertainty. In this article, we propose an integrated assessment model based on the evidential reasoning (ER) algorithm and fuzzy set theory. The assessment model is structured as a hierarchical framework that regards land subsidence risk as a composite of two key factors: hazard and vulnerability. These factors can be described by a set of basic indicators defined by assessment grades with attributes for transforming both numerical data and subjective judgments into a belief structure. The factor‐level attributes of hazard and vulnerability are combined using the ER algorithm, which is based on the information from a belief structure calculated by the Dempster‐Shafer (D‐S) theory, and a distributed fuzzy belief structure calculated by fuzzy set theory. The results from the combined algorithms yield distributed assessment grade matrices. The application of the model to the Xixi‐Chengnan area, China, illustrates its usefulness and validity for LSRA. The model utilizes a combination of all types of evidence, including all assessment information—quantitative or qualitative, complete or incomplete, and precise or imprecise—to provide assessment grades that define risk assessment on the basis of hazard and vulnerability. The results will enable risk managers to apply different risk prevention measures and mitigation planning based on the calculated risk states.     

中国石油股份实施ERP的思考——基于中国石油华北天然气销售公司的实践

自2007年底开始,中石油在地区公司推行ERP,华北天然气销售公司从2008年5月开始组织ERP项目建设,2008年11月开始实施。华北天然气销售公司在实施ERP过程中对传统会计务实理念产生了冲击,对公司的会计基础工作也产生了影响。从长期看,实施ERP与FMIS融合系统能整合中石油的技术平台,提高企业的整体竞争力。因此,中石油在ERP的实施中,应改变传统会计观念,加强基础数据的维护,保证基础数据的准确性和实效性,完善ERP系统的配套管理机制和运行机制,建立配套的内部控制机制,做好风险管理工作。     

An improved two-stage procedure to compare hazard curves

Qiu and Sheng has proposed a powerful and robust two-stage procedure to compare two hazard rate functions. In this paper we improve their method by using the Fisher test to combine the asymptotically independent p-values obtained from the two stages of their procedure. In addition, we extend the procedure to situations with multiple hazard rate functions. Our comprehensive simulation study shows that the proposed method has a good performance in terms of controlling the type I error rate and of detecting power. Three real data applications are considered for illustrating the use of the new method.     

对外交流中专有名词翻译

随着全球化步伐的不断加快,中国与世界各国的交流也日益频繁,如何让中国更好地走向世界,同时让中国更好地了解世界就显得尤为重要。语言文化作为文化的重要载体和标志,其传播必将促进中国的对外交流,而专有名词作为语言文化的浓缩和精髓,其翻译在对外交流中将起着举足轻重的作用。     

Daily Inhalation Rate and Time‐Activity/Location Pattern in Japanese Preschool Children

Lack of data on daily inhalation rate and activity of children has been an issue in health risk assessment of air pollutants. This study aimed to obtain the daily inhalation rate and intensity and frequency of physical activity in relation to the environment in Japanese preschool children. Children aged four–six years (n= 138) in the suburbs of Tokyo participated in this study, which involved three days' continuous monitoring of physical activity using a tri‐axial accelerometer and parent's completion of a time/location diary during daily life. The estimated three‐day mean daily inhalation rate (body temperature, pressure, saturated with water vapor) was 9.9 ± 1.6 m³/day (0.52 ± 0.09 m³/kg/day). The current daily inhalation rate value of 0.580 m³/kg/day proposed for use in health risk assessment in Japan is confirmed to be valid to calculate central value of inhaled dose of air pollutants in five‐ to six‐year‐old children. However, the 95th percentile daily inhalation rate of 0.83 m³/kg/day based on measurement for five‐year‐old children is recommended to be used to provide an upper bound estimate of exposure that ensure the protection of all five‐ to six‐year‐old children from the health risk of air pollutants. Children spent the majority of their time in sedentary and light level of physical activity (LPA) when indoors, while 85% of their time when outdoors was spent in LPA and moderate‐to‐vigorous physical activity. The results suggest the need to consider variability of minute respiratory ventilation rate according to the environment for more refined short‐term health risk assessment.