Implications of Sociopolitical Context for Career Services Delivery

This article analyzes the implications of sociopolitical context for career services delivery. Beginning with a reflection on the social foundations of the practice of career counseling, 4 specific Portuguese conditions are presented and discussed in light of existing knowledge in the field. The 4 underlying issues presented are (a) the impact of political changes on career services delivery, (b) the rigidity vs. flexibility of the educational system, (c) political and psychological perspectives on employment, and (d) the relationship between power and career services delivery. A research agenda founded in political anthropology is proposed that may enhance future career services delivery.     

Positivity conditions for stochastic state space modelling of time series

This short paper clarifies some aspects of the balancing method for state space modelling of observed time series. This method may fail to satisfy the so-called positive real condition for stochastic processes. We illustrate this by theoretical spectral analysis and also by simulating univariate ARMA (1,1) models.     

The road to a world health organization global strategy for reducing the harmful use of alcohol

Harmful alcohol use and the related health effects are a global problem and therefore need to be addressed not only by individual nations but also on an international level. For example, the World Health Organization (WHO) noted that harmful alcohol use is the third leading risk factor for premature deaths and disabilities in the world, accounting for approximately 2.5 million deaths worldwide (corresponding to 3.8 percent of all deaths) in 2004 (WHO 2010). Moreover, harmful alcohol use was considered responsible for 4.5 percent of the global burden of disease as measured in disability-adjusted life-years lost in the same year. Given this scope of the impact, the WHO initiated a series of efforts that culminated in the development of a global strategy for reducing the harmful use of alcohol. This article reviews the alcohol-related activities of the WHO over the years and summarizes the central issues addressed by the global strategy.     

A new mixed first-order integer-valued autoregressive process with Poisson innovations

AStA Advances in Statistical Analysis - Integer-valued time series, seen as a collection of observations measured sequentially over time, have been studied with deep notoriety in recent years, with...     

The Impact of Complexity on Knowledge Transfer in Manufacturing Networks

Coordinating knowledge transfer within multi‐plant manufacturing networks is a challenging task. Using a computational model, we examine when it is beneficial to create production knowledge within a central unit, the “lead factory,” and transfer it to geographically dispersed plants. We demonstrate that the knowledge transfer generates a trade‐off between a positive cost‐saving effect due to fewer adaptations in each plant, and a negative transfer cost effect due to the costly knowledge transfer itself. The complexity of the production process moderates the performance implications of the knowledge transfer because it determines the relative strength of these two effects. For production processes with low complexity, knowledge transfer can engender superior network performance. Here, an optimal extent of knowledge transfer exists, and thus, a complete knowledge transfer is not performance maximizing. For production processes with medium and high levels of complexity, performance is reduced rather than enhanced through knowledge transfer so that it is optimal not to transfer any knowledge from the lead factory to the plants. While we analyze knowledge transfer within a manufacturing network, our results are transferable to other settings that consist of a knowledge sending and receiving unit.     

工业革命:过去与未来

通过全球经济增长的跨世纪比较,作者洞察出18世纪末开始的工业革命之后的经济增长与先前经济增长之根本不同在于工业世界是以人口总量相对于产出总量的增长率呈现稳定下降态势和广大普通民众生活水准的普遍提高为典型特征。进一步的分析表明,以马尔萨斯(Malthus)的人口理论为代表的传统经济增长理论可以成功解释传统农业社会里各国人均收入大致相等且基本上不随时间的变化而改变,而以贝克尔(Becker)的人力资本积累理论为代表的现代经济增长理论则可以成功解释现代工业社会中全球人均收入的持续大幅度成长、跨国人均收入的巨大不平等和人均收入跨国分布的动态变化。最后,作者指出随着仍然处在进行中的工业革命向全球各个角落扩散,世界人均收入整体上将不断提高,而解决全球低收入人群生活水准的最佳途径是不断地增加世界产出总量,而非重新分配现有的世界总产出。     

More is less? The volunteer stewardship framework and models

Scholars have devoted substantial attention to developing conditional models of volunteer administration and management, but no consensus surrounds the criteria underlying the different models or the rationale. The literature reveals a welter of possibilities but no clear choice. This study conceives the primary managerial challenges as securing access to and guiding volunteer energy into productive volunteering, and the volunteer administrator as the central actor in this process. Based on how volunteers are accessed and guided in their roles, we develop the Volunteer Stewardship Framework, which distinguishes volunteer administration according to two key dimensions: organizational access to volunteer energy (private resource vs. common pool) and guidance of volunteers (unitary vs. shared). Results of a survey of volunteer administration practitioners in the Netherlands show that respondents working under the four models emanating from the Framework recognize different elements of volunteer administration as “Very Important.”     

Bootstrap bias corrections for ensemble methods

This paper examines the use of a residual bootstrap for bias correction in machine learning regression methods. Accounting for bias is an important obstacle in recent efforts to develop statistical inference for machine learning. We demonstrate empirically that the proposed bootstrap bias correction can lead to substantial improvements in both bias and predictive accuracy. In the context of ensembles of trees, we show that this correction can be approximated at only double the cost of training the original ensemble. Our method is shown to improve test set accuracy over random forests by up to 70% on example problems from the UCI repository.     

Optimal Alarm Systems for Count Processes

In many phenomena described by stochastic processes, the implementation of an alarm system becomes fundamental to predict the occurrence of future events. In this work we develop an alarm system to predict whether a count process will upcross a certain level and give an alarm whenever the upcrossing level is predicted. We consider count models with parameters being functions of covariates of interest and varying on time. This article presents classical and Bayesian methodology for producing optimal alarm systems. Both methodologies are illustrated and their performance compared through a simulation study. The work finishes with an empirical application to a set of data concerning the number of sunspot on the surface of the sun.