Developing a Freely Accessible/Open Access Resource Management Policy at Duke University Libraries: A Case Study

Abstract

Freely accessible and open access resources present unique challenges for librarians working with electronic resources. Due to the fact that many of these resources lack high-quality metadata or the technical support provided by traditional publishers, making them discoverable and maintaining access over time can be tricky. Creating a policy allows for a systematic approach to the management of freely accessible/open access (OA) resources, alleviating problems surrounding lack of staff time or expertise. Many of these resources are already important parts of collections and will only continue to grow in importance. Freely accessible/OA resources allow for a more diverse representation of content, both by subject and format type, and allow a wider array of authors to have their work appear in library collections. This case study will provide a review of freely accessible/OA policies in other libraries, describe why these resources are important to add to our collections, discuss challenges libraries face with managing these resources, and explain how Duke University Libraries is addressing some of these challenges through the development of a policy.     

Changing from Single to Separate Records: A Case Study from the University of Nevada,Reno

The University of Nevada, Reno Libraries made the decision in early 2012 to convert its bibliographic records from a single record approach, with multiple formats of a title on one bibliographic record, to a separate record approach, where each format receives its own record. This decision was several years in the making, as it was a change that would potentially require breaking apart more than 20,000 records. It would involve numerous staff from different departments and would require adjustments for all staff who worked with library users. This article will discuss the factors that pushed the UNR Libraries to make this decision to split its records and the challenges technical services staff faced in managing the project. The authors will present the different procedures developed for splitting monographic and serial records and the different tools that were used to make the process work: Millennium (especially the ERM and Global Update modules), MarcEdit, and Serials Solutions' MARC Updates service.     

印度国家抽样调查组织近况简介

印度是目前世界上公认的抽样调查比较发达的一个国家。国家抽样调查组织(以下简称NSSO)是当前印度社会、经济调查方面最权威的机构,在很多方面值得我们借鉴。 一、机构设置。印度国家抽样调查组织进行的调查称为国家抽样调查(简称NSS)。NSS最早是1950年开始的。当时的调查内容有限,调查技术也不发达,主要是照搬欧美国家的方法。随着调查内容扩展和调查水平的提高,经过改组,到七十年代,目前的印度国家抽样调查组织就形成了。     

Refusal to Answer Specific Questions in a Survey: A Case Study

It is well known that non ignorable item non response may occur when the cause of the non response is the value of the latent variable of interest. In these cases, a refusal by a respondent to answer specific questions in a survey should be treated sometimes as a non ignorable item non response. The Rasch-Rasch model (RRM) is a new two-dimensional item response theory model for addressing non ignorable non response. This article demonstrates the use of the RRM on data from an Italian survey focused on assessment of healthcare workers’ knowledge about sudden infant death syndrome (that is, a context in which non response is presumed to be more likely among individuals with a low level of competence). We compare the performance of the RRM with other models within the Rasch model family that assume the unidimensionality of the latent trait. We conclude that this assumption should be considered unreliable for the data at hand, whereas the RRM provides a better fit of the data.     

Benefits of Model-based Drug Development: A Rigorous,Planned Case Study

Model-based drug development (MBDD) is useful to make better quantitative decisions within drug development. However, rigorous evaluation of the benefits has been scarce in the literature. In this study, we take a completed development program, retrospectively repeat it in a virtual setting using MBDD methodologies, and compare it to the traditional drug development process. The conclusion is that the use of MBDD could have facilitated more efficient use of resources.     

Predictive Inference,Causal Reasoning,and Model Assessment in Nonparametric Bayesian Analysis: A Case Study

This paper continuesour earlier analysis of a data set on acute ear infections insmall children, presented in Andreev and Arjas (1998). The maingoal here is to provide a method, based on the use of predictivedistributions, for assessing the possible causal influence whichthe type of day care will have on the incidence of ear infections.A closely related technique is used for the assessment of thenonparametric Bayesian intensity model applied in the paper.Two graphical methods, supported by formal tests, are suggestedfor this purpose.     

Prior Density Selection as a Particular Case of Bayesian Model Selection: A Predictive Approach

A Bayesian model consists of two elements: a sampling model and a prior density. The problem of selecting a prior density is nothing but the problem of selecting a Bayesian model where the sampling model is fixed. A predictive approach is used through a decision problem where the loss function is the squared L ² distance between the sampling density and the posterior predictive density, because the aim of the method is to choose the prior that provides a posterior predictive density as good as possible. An algorithm is developed for solving the problem; this algorithm is based on Lavine's linearization technique.     

Research Online: Digital Commons as a Publishing Platform at the University of Wollongong, Australia

Since 2006, Research Online, the University of Wollongong's open access institutional repository has utilised Bepress' Digital Commons software to make available published research outputs and digital theses. This article discusses the outcomes of recent academic demand for its use as a publishing tool of university journals and conference proceedings. The Journal of University Teaching and Learning Practice is provided as an example. Digital Commons includes the editorial management software, EdiKit, which assists in managing submissions, editorial functions, and peer review. Also considered are changes to scholarly communication patterns arising out of the new open access, electronic only, publication regimes.     

中国国民核算演变的公共品视角:模式选择、知识生产与体系构建

国民核算作为一种国际标准统计体系的制度安排和一种宏观经济统计信息,具备了非排他性和非竞争性,因而属于一种公共品。本文不是中国国民核算理论和实践发展过程的全面论述,而是从公共品视角对核算模式选择、知识生产和体系构建补充一些认知。研究提出:(1)中国统计改革起点是口径符合物质平衡表范围的产值指标,从未系统实施过物质平衡表体系;中国国民核算模式转换和体系改革是内在动力和外在压力共同作用的结果;中国国民核算实践发展不够平衡,总体上大致处于1953年版至1993年版之间,部分项目达到了SNA 2008年版的水平。(2)中国学者在国民核算领域的学术增加值主要是论证中国核算模式的确立,对SNA的引进和系统、深入解读,SNA的中国化探索;国民核算的知识生产事关国家经济安全和质量提升,需要学者坚守阵地、贡献智慧,以奠定坚实的社会基础;国民核算需要脑书Handbook进一步研究学理和方法论。(3)SNA自身面临的困局和中国高质量发展,对国民核算提出了要求,通过中国SNA体系的构建路线图,给出了中国SNA体系化发展的路径。     

Federal Statistics in a Complex Environment: The Case of the 1980 Census

The taking and the interpretation of something as big and as complicated as the national census is more than an exercise in statistical thinking. It involves other diverse fields such as ethics, epistemology, law, and politics. This article shows that a national census is more akin to so-called ill-structured problems. Unlike well-structured problems, the formulation of an ill-structured problem varies from field to field and from person to person, and the various aspects of an ill-structured problem (i.e., ethics, epistemology, etc.) cannot be clearly separated from one another. The 1980 census is discussed as an ill-structured problem, and a method for treating such problems is presented, within which statistical information is only one component.     

A Case Study in Nonresponse: Plaintiff vs. California State Board of Equalization

In any sample survey, nonresponse bias is a potential issue. Even with a moderately high nonresponse rate, however, covariates can sometimes be used to show that the nonresponse bias is likely to be small. This note presents such an argument, which was used by the winning side in a tax case.     

Uncertainty Quantification in Case of Imperfect Models: A Non‐Bayesian Approach

The starting point in uncertainty quantification is a stochastic model, which is fitted to a technical system in a suitable way, and prediction of uncertainty is carried out within this stochastic model. In any application, such a model will not be perfect, so any uncertainty quantification from such a model has to take into account the inadequacy of the model. In this paper, we rigorously show how the observed data of the technical system can be used to build a conservative non‐asymptotic confidence interval on quantiles related to experiments with the technical system. The construction of this confidence interval is based on concentration inequalities and order statistics. An asymptotic bound on the length of this confidence interval is presented. Here we assume that engineers use more and more of their knowledge to build models with order of errors bounded by . The results are illustrated by applying the newly proposed approach to real and simulated data.     

A Second-order Adjustment to the Profile Likelihood in the Case of a Multidimensional Parameter of Interest

Inference in the presence of nuisance parameters is often carried out by using the χ²-approximation to the profile likelihood ratio statistic. However, in small samples, the accuracy of such procedures may be poor, in part because the profile likelihood does not behave as a true likelihood, in particular having a profile score bias and information bias which do not vanish. To account better for nuisance parameters, various researchers have suggested that inference be based on an additively adjusted version of the profile likelihood function. Each of these adjustments to the profile likelihood generally has the effect of reducing the bias of the associated profile score statistic. However, these adjustments are not applicable outside the specific parametric framework for which they were developed. In particular, it is often difficult or even impossible to apply them where the parameter about which inference is desired is multidimensional. In this paper, we propose a new adjustment function which leads to an adjusted profile likelihood having reduced score and information biases and is readily applicable to a general parametric framework, including the case of vector-valued parameters of interest. Examples are given to examine the performance of the new adjusted profile likelihood in small samples, and also to compare its performance with other adjusted profile likelihoods.     

林业生态、产业和民生系统耦合协调的动态演进——以黑龙江省国有林区为例

通过构建黑龙江省国有林区林业生态、产业和民生系统协调发展评价的指标体系,结合变异系数法测算出林业生态、产业和民生各子系统及综合发展指数。在此基础上引入二元和三元系统耦合协调模型,并借助灰色系统GM(1,1)预测模型预测2017—2020年三系统耦合协调发展水平。结果显示:黑龙江省国有林区林业生态、产业和民生各子系统发展指数表现出阶段性差异,但综合发展指数呈现出向好态势;三系统耦合协调度实现由低到高的梯度演进,但目前仍处于协调发展的一般水平;预计到2020年,三系统耦合协调发展水平将接近于中级协调,但距离优质协调还有一定差距。     

Teaching Communication in a Statistical Collaboration Course: A Feasible,Project-Based,Multimodal Curriculum

Many schools offer a statistical collaboration curriculum using standard instructional methods such as lectures whereby students are taught to successfully apply their training. The process of building statisticians' collaborative skills and characteristics can be challenging due to logistical issues, time constraints, unstructured research problems, and resources. Instructors vary in their pedagogy and topics taught, and students' experiences vary. There is a dearth of literature describing how to implement a course integrating communication skills, critical thinking, collaboration, and the integration of team members in a learner-centered format. Few courses integrate behavior-based learning using role-playing, video demonstration and feedback, case-based teaching activities, and presentation of basic statistical concepts. We have developed and implemented a two-semester biostatistics collaboration course, of which the purpose is to develop the students' knowledge, skills, attitudes, and behaviors necessary to interact effectively with investigators. Our innovative curriculum uses a multimodal, project-based, experiential process to address real-world problems provided by real and/or simulated collaborators while minimizing usual challenges. Rubrics and peer evaluation forms are offered as online supplementary materials. This article describes how a collaboration curriculum focusing on communication and team practice is feasible, how it enhances skill and professionalism, and how it can be implemented at other institutions.     

环境规制对中国油料作物产出影响的研究——基于距离函数对技术效率的测度

在综述环境规制对技术效率影响的国内外文献基础上,通过距离函数测算了2001-2010年环境规制对中国东部、中部和西部地区四种油料作物的影响,从无规制、宽松规制及严格规制这三个层次揭示了环境规制对不同区域的大豆、油菜、花生及芝麻在产出技术效率和生产力发挥方面的差异化影响。研究表明:对于所研究的绝大多数地区,环境规制水平的提高能够提升该地区油料作物的产出技术效率,并有利于更大程度地发挥潜在生产力;而在极少数地区,较高的环境规制水平对技术效率的发挥已经起到了微弱的阻碍作用。最后,阐释了同一环境规制对不同产业产生迥异影响的普遍规律,论证了较为完善的环境规制应该是做为一个体系而存在的,为本国制定与完善环境规制提供了一定的参考。     

陕西省居民消费、投资与经济增长关系的协整研究

一、引言消费、投资与我国GDP之间的关系一直以来是宏观经济领域讨论的热点,学者们在这方面已经做出了很多有意义的分析和研究,他们普遍都认为消费和投资对我国的经济增长有促进作用,但是在消费、投资对我国GDP作用的大小以及它们之间的相互因果关系上面却存在着不同的观点。在     

农村居民消费融资需求及影响因素分析——以陕西省渭南市为例

基于渭南市2 636户农户问卷调查数据,从农户分化与演变视觉分析农村居民消费融资需求状况。采用概率模型分析了影响农户融资消费的主要因素是收支的＂非均衡性＂、户主个性、消费环境、城乡融合程度和存贷款利率水平高低。建议调整国民收入分配结构,完善农村基本社会保障体系,推进农村居民生产生活集聚,构建以农户需求为导向的农村金融体系。     

The Role of Classification Trees and Expert Knowledge in Building Bayesian Networks: A Case Study in Medicine

In clinical research an early and prompt detection of the risk class of a new patient may really play a crucial role in determining the effectiveness of the treatment and, consequently, achieving a satisfying prognosis of the patient's chances. There exists a number of popular rule-based algorithms for classification, whose performances are very attractive whenever data of large number of patients are available. However, when datasets only include data of a few hundred patients, the most common approaches give unstable results and developing effective decision-support systems become scientifically challenging. Since rules can be derived from different models as well as expert knowledge resources, each of them having its advantages and weaknesses, this article suggests a “hybrid” approach to address the classification problem when the number of patients is too small to effectively use a single technique only. The hybrid strategy was applied to a case study and its predictive performance was compared with performances of each single approach: due to the seriousness of a misclassification of high-risk patients, special attention was paid on the specificity. The results show that the hybrid strategy outperforms each single strategy involved.