Unique unto itself: The records of the Federal Bureau of Investigation 1908 to 1945

This paper addresses several misunderstandings about the nature of the FBI's Central Records System. Although depicted in popular culture and much of FBI historiography as a tool for the Cold War suppression of American radicals, the FBI's records system grew out of Department of Justice systems already in place before J. Edgar Hoover became Director in 1924. The system grew in size and complexity according to the demands placed on it by the changing priorities of the FBI's criminal and intelligence missions, guided by a “progressive” drive for efficiency through centralization.     

概说虚拟存储

虚拟是今天存储业界的热门话题,对数据的管理就是对存储的管理。大小客户如何利用虚拟存储解决方案并通过存储软件和存储硬件自身内部的分区来最大程度地利用自身的存储基础架构呢?与此同时,客户们仍在问究竟什么是虚拟存储呢?如何实现这些技术呢?企业自身的基础架构是否适合实现存储虚拟化呢?     

Validating the Willingness to Self-Censor Scale: Individual Differences in the Effect of the Climate of Opinion on Opinion Expression

Hayes, Glynn, and Shanahan (2005) defined self-censorship asthe withholding of one’s opinion around an audience perceivedto disagree with that opinion. They argued that people differin their willingness to self-censor and introduced an 8-itemself-report instrument, the Willingness to Self-Censor scale,to measure this individual difference. The results of an experimentalstudy presented here provide further evidence of the constructvalidity of the scale. Each participant in the study was presentedwith a hypothetical scenario that contained information suggestinga group of people the participant was conversing with abouta controversial topic held opinions that were either uniformlysimilar to or different from the participant’s own opinion.Four weeks prior, each participant had responded to the Willingnessto Self-Censor scale and a measure of dispositional shyness.As expected, the manipulation of the climate of opinion affectedwillingness to express an opinion to the group, but more soamong those who scored relatively high on the Willingness toSelf-Censor scale. These results support the notion that somepeople rely on information about the climate of opinion moreso than do others when they decide whether or not to voice theiropinion publicly, and they suggest that the Willingness to Self-Censorscale measures this individual difference.     

Lighting the Shroud of Turin for Exhibition in 2015

ABSTRACT

Lighting a cultural heritage artifact requires balancing visual perception with preventive conservation, by providing the best lighting (in terms of spectral distribution and quantity) to enable the viewer to appreciate details and color, while limiting photo-induced degradation. The paper outlines the methodology applied by a multi-disciplinary team while lighting the Shroud of Turin at its last public exhibition in 2015. The methodology considered the special requirements of the Shroud, including exposure to ultraviolet light, while providing appropriate display conditions that would meet audience expectations. The desired appearance (readability of the body image and color) was defined with the help of Shroud researchers and confirmed by subjective tests, while appropriate light levels for preservation were set in agreement with standard requirements and using knowledge of the degradation of linen in visible and UV light. The installation provided a controlled environment and a managed visitor route to the Shroud, assuring excellent perception of both details and color, with the lowest illuminance level about 15?lx.     

Reasons for Student Engagement in Extra-Class Communication

This study extends instructional communication research on extra-class communication (ECC) by presenting an integrative analysis comparing the explanatory utility of student- and instructor-oriented reasons for student engagement in frequent ECC. Results from 495 college students suggested that student-oriented reasons, specifically the relational and functional student motives, were the only significant, positive predictors of students’ perceptions of frequent ECC engagement. Other student motives (excuse making, participation, sycophancy) and perceptions of instructor approachability did not significantly predict perceived frequency of ECC engagement.     

Retrieving and classifying instances of source code plagiarism

Automatic detection of source code plagiarism is an important research field for both the commercial software industry and within the research community. Existing methods of plagiarism detection primarily involve exhaustive pairwise document comparison, which does not scale well for large software collections. To achieve scalability, we approach the problem from an information retrieval (IR) perspective. We retrieve a ranked list of candidate documents in response to a pseudo-query representation constructed from each source code document in the collection. The challenge in source code document retrieval is that the standard bag-of-words (BoW) representation model for such documents is likely to result in many false positives being retrieved, because of the use of identical programming language specific constructs and keywords. To address this problem, we make use of an abstract syntax tree (AST) representation of the source code documents. While the IR approach is efficient, it is essentially unsupervised in nature. To further improve its effectiveness, we apply a supervised classifier (pre-trained with features extracted from sample plagiarized source code pairs) on the top ranked retrieved documents. We report experiments on the SOCO-2014 dataset comprising 12K Java source files with almost 1M lines of code. Our experiments confirm that the AST based approach produces significantly better retrieval effectiveness than a standard BoW representation, i.e., the AST based approach is able to identify a higher number of plagiarized source code documents at top ranks in response to a query source code document. The supervised classifier, trained on features extracted from sample plagiarized source code pairs, is shown to effectively filter and thus further improve the ranked list of retrieved candidate plagiarized documents.     

Back to Reality: The Complex Relationship Between Patterns in Immigration News Coverage and Real-World Developments in Dutch and Flemish Newspapers (1999–2015)

Although prior studies investigating immigration news typically documented a dominant focus on negativity and threats, only limited empirical research is available, which scrutinizes the way real-world developments affect these patterns in immigration news. This study aims to fill this void. First, we report results of a large-scale and longitudinal content analysis (N = 4,340,757) of trends in immigration news coverage in two Western European cases, Flanders (the northern, Dutch-speaking, largest region of Belgium) and the Netherlands, from 1999 to 2015. Both the salience of immigration as a news topic on itself and its linkages with three prominent issues (i.e., crime, terrorism, and socioeconomic issues) are explored. Second, this study builds on previous insights by comparing dynamics in immigration news to real-world events and developments. Overall, the results show that the linkage of immigration to issues of crime, terrorism, and the economy in Flemish and Dutch newspapers was considerable throughout the 17-year period under study. Yet there is limited evidence for a close relationship between news and real-life developments; hence, trends in immigration news seem largely unaffected by trends in society.     

Scaling up Content Analysis

ABSTRACT

Employing a number of different standalone programs is a prevalent approach among communication scholars who use computational methods to analyze media content. For instance, a researcher might use a specific program or a paid service to scrape some content from the Web, then use another program to process the resulting data, and finally conduct statistical analysis or produce some visualizations in yet another program. This makes it hard to build reproducible workflows, and even harder to build on the work of earlier studies. To improve this situation, we propose and discuss four criteria that a framework for automated content analysis should fulfill: scalability, free and open source, adaptability, and accessibility via multiple interfaces. We also describe how to put these considerations into practice, discuss their feasibility, and point toward future developments.