Museums at the crossroad: Contributing to dialogue, curiosity and wonder in natural history museums

The first natural history collections opened to the public were inspired by a sense of curiosity and wonder about the products of nature. They were ‘cabinets of curiosities’ that offered a first-hand interaction between owner and visitors. Nowadays, these two facets of the museum experience—dialogue and wonder—have been lost, in part, due to the information overload coming via the media and the impersonal nature of the museum visit. This paper offers some reflections on the evolution of the museum visit, suggests some ways to rediscover this ‘sense of wonder’ and provides ideas on how to promote two-way communication with museum visitors. Two examples of exhibitions are offered as illustrations of the points discussed.     

Employee mistreatment and muted voices in the culturally diverse workplace

This study examines mistreatment through the perspectives of employees with different cultural backgrounds and positions in order to understand the ways in which some voices are muted and others are privileged. Mistreatment is interactional, distributive, procedural, or systemic abuse of employees taking place at both interpersonal and institutional levels on the basis of cultural diversity. Narrative analysis of semi-structured interviews with employees of a large research and development organization revealed three types of muted narratives used to respond to mistreatment (muted-but-engaged, angrily disengaged, and resigned) as well as one type of privileged response. The narratives provided evidence of two processes by which voices became muted: repeated silencing over time and silencing through ambiguity of policies.     

Forschungs- und Entwicklungsprojekte Virtuelle Maschinen: zSeries- und S/390-Partitionierung

Der gleichzeitige Betrieb mehrerer Gast-Betriebssysteme auf einem einzigen physischen Rechner unter einem Host-Betriebssystem ist eine leistungsfähige moderne Entwicklung. Bekannte Beispiele sind VMware für die IA32-Architektur sowie das Betriebssystem z/VM und die PR/SM-LPAR Einrichtungen der zSeries-Architektur. Die Nutzung eines Betriebssystems als Gast bedingt einen Leistungsverlust. Die als Partitionierung bezeichnete Zuordnung von Systemressourcen zu den einzelnen Gast-Betriebssysteme ist schwierig, wenn eine dynamische Anpassung an sich ändernde Lastprofile erforderlich ist. Diese Probleme lassen sich mittels Erweiterungen der Hardwarearchitektur adressieren, sowie durch Softwarestrukturen, welche diese Erweiterungen nutzen. Die Erweiterungen der Hardwarearchitektur gehen über das hinaus, was auf heutigen Rechnerarchitekturen wie IA32 oder Mips verfügbar ist. Der vorliegende Beitrag erläutert den optimalen Betrieb von Gast-Betriebssystemen und die begleitenden Partitionierungsmöglichkeiten auf der zSeries-Plattform und beschreibt die zusätzlichen Hardware- und Software-Einrichtungen, welche dies ermöglichen.     

传媒经济学研究的历史、方法与范例

本文主要回顾了传媒经济学在西方的发展历程、研究方法以及不同时期的研究议题。传媒经济学是构建于不同的经济学理论和分析方法之上的应用性学科,它致力于研究经济和金融力量如何影响传媒体系和传媒组织。西方传媒经济学创建于20世纪50年代,至今已发展成为一个活跃的和跨学科研究领域。文章认为,西方传媒经济学的主要研究范例包括理论型、应用型和批评型范例;其研究方法可分为行业市场研究、公司研究和影响力研究。在介绍西方传媒经济学研究的同时,本文还简要回顾了传媒经济学在中国的兴起与发展。     

Analysis of Statistical Question Classification for Fact-Based Questions

Question classification systems play an important role in question answering systems and can be used in a wide range of other domains. The goal of question classification is to accurately assign labels to questions based on expected answer type. Most approaches in the past have relied on matching questions against hand-crafted rules. However, rules require laborious effort to create and often suffer from being too specific. Statistical question classification methods overcome these issues by employing machine learning techniques. We empirically show that a statistical approach is robust and achieves good performance on three diverse data sets with little or no hand tuning. Furthermore, we examine the role different syntactic and semantic features have on performance. We find that semantic features tend to increase performance more than purely syntactic features. Finally, we analyze common causes of misclassification error and provide insight into ways they may be overcome.