How to Evaluate Government Performance while Building a Rule of Law Government in China*

Building a law-based government is a central element of the comprehensive framework for promoting the rule of law in China, while using evaluation to catalyze growth is in line with the incentive principle of management studies. Since China started to implement reform and opening up over thirty years ago, rule of law development and organizational evaluation have gone through several stages, each with different characteristics. Efforts to build a law-based government have met with success, but what the country now has is essentially still goal-oriented assessment. At present, this suffers from the lack of a clear goal orientation or definition of functions, an imperfect technical system and unsound motivation mechanisms, not to mention the practical problems of each government department going its own way, duplicating evaluations or being left rudderless. Drawing on a combination of value rationality and instrumental rationality and using government performance evaluation to promote the building of a law-based government not only conforms to the spirit of the rule of law and value rationality in government performance, but also strengthens the role of evaluation as an instrument for organizational management. Therefore, we need to create new evaluation theories, expand public participation, introducing diversified evaluating entities, improve technical systems, strengthen institutional buildup, and foster a performance-based culture. In addition, replacing goal-oriented assessment with performance evaluation will help the emergence of a new discipline—the performance evaluation of rule of law government, thus promoting multidisciplinary efforts to integrate and create new public administration theories in China.     

Application of a QMRA Framework to Inform Selection of Drinking Water Interventions in the Developing Context

The aim of this study was to develop a modified quantitative microbial risk assessment (QMRA) framework that could be applied as a decision support tool to choose between alternative drinking water interventions in the developing context. The impact of different household water treatment (HWT) interventions on the overall incidence of diarrheal disease and disability adjusted life years (DALYs) was estimated, without relying on source water pathogen concentration as the starting point for the analysis. A framework was developed and a software tool constructed and then implemented for an illustrative case study for Nepal based on published scientific data. Coagulation combined with free chlorine disinfection provided the greatest estimated health gains in the short term; however, when long‐term compliance was incorporated into the calculations, the preferred intervention was porous ceramic filtration. The model demonstrates how the QMRA framework can be used to integrate evidence from different studies to inform management decisions, and in particular to prioritize the next best intervention with respect to estimated reduction in diarrheal incidence. This study only considered HWT interventions; it is recognized that a systematic consideration of sanitation, recreation, and drinking water pathways is important for effective management of waterborne transmission of pathogens, and the approach could be expanded to consider the broader water‐related context.     

Discovering hidden statistical issues through individual-level models in ecological studies

ABSTRACT

In ecological studies, individual inference is made based on results from ecological models. Interpretation of the results requires caution since ecological analysis on group level may not hold in the individual level within the groups, leading to ecological fallacy. Using an ecological regression example for analyzing voting behaviors, we highlight that the explicit use of individual-level models is crucial in understanding the results of ecological studies. In particular, we clarify three relevant statistical issues for each individual-level models: assessment of the uncertainty of parameter estimates obtained from a wrong model, the use of shrinkage estimation method for simultaneous estimation of many parameters, and the necessity of sensitivity analysis rather than adhering to one seemingly most compelling assumption.     

Identifying Changing Aviation Threat Environments Within an Adaptive Homeland Security Advisory System

A critical component of aviation security consists of screening passengers and baggage to protect airports and aircraft from terrorist threats. Advancements in screening device technology have increased the ability to detect these threats; however, specifying the operational configurations of these devices in response to changes in the threat environment can become difficult. This article proposes to use Fisher information as a statistical measure for detecting changes in the threat environment. The perceived risk of passengers, according to prescreening information and behavior analysis, is analyzed as the passengers sequentially enter the security checkpoint. The alarm responses from the devices used to detect threats are also analyzed to monitor significant changes in the frequency of threat items uncovered. The key results are that this information‐based measure can be used within the Homeland Security Advisory System to indicate changes in threat conditions in real time, and provide the flexibility of security screening detection devices to responsively and automatically adapt operational configurations to these changing threat conditions.     

The Common Assessment Framework form 9 years on: a creative process

Legislation within England states that local authorities should provide services for all those families in need. However, research has identified that regardless of the introduction of strategies to identify need and enhance family support, ongoing barriers to services adhere. Taking a social constructionist approach, this study explored professionals' experiences of the use of the Common Assessment Framework form. Data were collected in four different local authorities in two phases. Forty‐one professionals from a variety of agencies took part in semi‐structured interviews. Data were analyzed thematically. Findings demonstrate that the professionals experienced difficulties in working through the Common Assessment Framework process, for example, in completing the form and engaging families. This situation led to the more experienced and knowledgeable professionals utilising creative ways to successfully navigate the ‘referral process’. Such creative working practices included the terminology used to complete the form and how the process was ‘sold’ to parents, so that they could be in a better position to engage parents and complete the Common Assessment Framework form. Because of this, more experienced professionals seem to be able to accelerate the referral process in order to access much needed support services for children and young people.     

Therapeutic Assessment with Children in Family Therapy

Therapeutic Assessment with Children (TA‐C) is a brief semi‐structured intervention in which psychological assessment is used to help families with children and adolescents to change. In this paper we introduce the TA‐C model, describe its semi‐structured format and exemplify how it can be applied by family therapists.     

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.     

Using In Vitro High‐Throughput Screening Data for Predicting Benzo[k]Fluoranthene Human Health Hazards

Today there are more than 80,000 chemicals in commerce and the environment. The potential human health risks are unknown for the vast majority of these chemicals as they lack human health risk assessments, toxicity reference values, and risk screening values. We aim to use computational toxicology and quantitative high‐throughput screening (qHTS) technologies to fill these data gaps, and begin to prioritize these chemicals for additional assessment. In this pilot, we demonstrate how we were able to identify that benzo[k]fluoranthene may induce DNA damage and steatosis using qHTS data and two separate adverse outcome pathways (AOPs). We also demonstrate how bootstrap natural spline‐based meta‐regression can be used to integrate data across multiple assay replicates to generate a concentration–response curve. We used this analysis to calculate an in vitro point of departure of 0.751 μM and risk‐specific in vitro concentrations of 0.29 μM and 0.28 μM for 1:1,000 and 1:10,000 risk, respectively, for DNA damage. Based on the available evidence, and considering that only a single HSD17B4 assay is available, we have low overall confidence in the steatosis hazard identification. This case study suggests that coupling qHTS assays with AOPs and ontologies will facilitate hazard identification. Combining this with quantitative evidence integration methods, such as bootstrap meta‐regression, may allow risk assessors to identify points of departure and risk‐specific internal/in vitro concentrations. These results are sufficient to prioritize the chemicals; however, in the longer term we will need to estimate external doses for risk screening purposes, such as through margin of exposure methods.     

基于多维效应的能源效率评估理论——以非参数DEA方法为例

基于多维效应的能源效率评估使人们在达到经济增长目的的同时兼顾能源安全、竞争力、环境、社会和技术的可持续性。论述能源效率内涵演化发展的路径，在此基础上将能源效率的内涵扩展至多维效应。以非参数DEA（Data Envelopment Analysis）方法为例，研究基于多维效应的能源效率评估方法的演化与发展趋势。研究结果显示:采用DEA方法对基于多维效应的能源效率进行评估的发展趋势主要有以下3点:能源效率的内涵不断延伸；DEA模型向非导向非径向模型转变；能源效率评估的研究维度不断扩展。对多维效应的能源效率综合指标评价体系和评价方法还需做深入研究。