From abbey to archive: managing texts and records in early modern England

This article investigates the long-term transformations in England’s documentary storage regime wrought by the Reformation. Henry VIII’s Dissolution of the Monasteries famously resulted in the dispersal and destruction of many medieval texts and records, but he and his successors sponsored efforts to retrieve lost materials, which they then used in the formation of ecclesiastical policy. Elizabethan counselors expanded the scope of this project, applying their expertise in gathering records to secular issues and assiduously preserving their own documents. During James I’s reign, the Earl of Salisbury’s patronage gave new authority to the State Paper Office, encouraging the consolidation of a centralizing archive that integrated earlier methods of collection, preservation, and indexing in its operation and construction. The article thus offers an analytic trajectory tying the practices of Reformation to the development of expanding national archives in the seventeenth century.     

British Colonial Administrations’ registry systems: a comparative study of Northern Rhodesia and Nyasaland

Recordkeeping in twentieth century colonial states has been ignored by scholars, or at best regarded as the result of a monolithic process of migration of metropolitan practices. Registries provided the principal organ of recordkeeping in British government systems of administration. This comparative study of the registries in the neighbouring territories of Northern Rhodesia (now Zambia) and Nyasaland (now Malawi) reveals the true extent of metropolitan British influence, exposing an absence of centralised advice, and a consequent dependence upon individual innovation. This engendered divergent and sometimes weak recordkeeping regimes. The effects of this included the diminution of fiduciary responsibility and administrative accountability.     

A general approximation framework for direct optimization of information retrieval measures

Recently direct optimization of information retrieval (IR) measures has become a new trend in learning to rank. In this paper, we propose a general framework for direct optimization of IR measures, which enjoys several theoretical advantages. The general framework, which can be used to optimize most IR measures, addresses the task by approximating the IR measures and optimizing the approximated surrogate functions. Theoretical analysis shows that a high approximation accuracy can be achieved by the framework. We take average precision (AP) and normalized discounted cumulated gains (NDCG) as examples to demonstrate how to realize the proposed framework. Experiments on benchmark datasets show that the algorithms deduced from our framework are very effective when compared to existing methods. The empirical results also agree well with the theoretical results obtained in the paper.     

Entity ranking in Wikipedia: utilising categories,links and topic difficulty prediction

Entity ranking has recently emerged as a research field that aims at retrieving entities as answers to a query. Unlike entity extraction where the goal is to tag names of entities in documents, entity ranking is primarily focused on returning a ranked list of relevant entity names for the query. Many approaches to entity ranking have been proposed, and most of them were evaluated on the INEX Wikipedia test collection. In this paper, we describe a system we developed for ranking Wikipedia entities in answer to a query. The entity ranking approach implemented in our system utilises the known categories, the link structure of Wikipedia, as well as the link co-occurrences with the entity examples (when provided) to retrieve relevant entities as answers to the query. We also extend our entity ranking approach by utilising the knowledge of predicted classes of topic difficulty. To predict the topic difficulty, we generate a classifier that uses features extracted from an INEX topic definition to classify the topic into an experimentally pre-determined class. This knowledge is then utilised to dynamically set the optimal values for the retrieval parameters of our entity ranking system. Our experiments demonstrate that the use of categories and the link structure of Wikipedia can significantly improve entity ranking effectiveness, and that topic difficulty prediction is a promising approach that could also be exploited to further improve the entity ranking performance.     

A Look at Global Expansion for e-Books

Forecasts indicate a growing demand for digital content around the world. Converting to digital content can open up countless new revenue possibilities. Adding alternate channels may be worth consideration, but what are the options and what does it take to utilize them effectively? This article explores the opportunities that potentially exist for publishers with content that may be digitized and distributed to global markets. A brief review of the current marketplace is also incorporated, including current players and trends. Finally, an analysis of some of the potential issues, challenges and pitfalls is presented in context of delving into a new international digital content distribution strategy.     

Learning to rank with (a lot of) word features

In this article we present Supervised Semantic Indexing which defines a class of nonlinear (quadratic) models that are discriminatively trained to directly map from the word content in a query-document or document-document pair to a ranking score. Like Latent Semantic Indexing (LSI), our models take account of correlations between words (synonymy, polysemy). However, unlike LSI our models are trained from a supervised signal directly on the ranking task of interest, which we argue is the reason for our superior results. As the query and target texts are modeled separately, our approach is easily generalized to different retrieval tasks, such as cross-language retrieval or online advertising placement. Dealing with models on all pairs of words features is computationally challenging. We propose several improvements to our basic model for addressing this issue, including low rank (but diagonal preserving) representations, correlated feature hashing and sparsification. We provide an empirical study of all these methods on retrieval tasks based on Wikipedia documents as well as an Internet advertisement task. We obtain state-of-the-art performance while providing realistically scalable methods.     

Characteristics of project management at institutions sponsoring National Library of Medicine MedlinePlus Go Local

Objectives:

Through interviews with the National Library of Medicine''s MedlinePlus Go Local collaborators, an evaluation team sought to identify process characteristics that are critical for long-term sustainability of Go Local projects and to describe the impact that Go Local projects have on sponsoring institutions.

Methods:

Go Local project coordinators (n = 44) at 31 sponsor institutions participated in semi-structured interviews about their experiences developing and maintaining Go Local sites. Interviews were summarized, checked for accuracy by the participating librarians, and analyzed using a general inductive methodology.

Results:

Institutional factors that support Go Local projects were identified through the interviews, as well as strategies for staffing and partnerships with external organizations. Positive outcomes for sponsoring institutions also were identified.

Conclusions:

The findings may influence the National Library of Medicine team''s decisions about improvements to its Go Local system and the support it provides to sponsoring institutions. The findings may benefit current sponsoring institutions as well as those considering or planning a Go Local project.

Highlights

• Many project coordinators said they underestimated the level of work their National Library of Medicine (NLM) MedlinePlus Go Local projects would require, but most expressed dedication to the project and optimism about project sustainability.
• An institutional record of community service or outreach and a director who was supportive of the project were important factors in the progress and sustainability of Go Local projects.
• Go Local projects brought recognition to some sponsoring institutions from their parent institutions or their communities and provided opportunities to establish better relations with other libraries and institutions.
• Go Local projects ran more smoothly when a person, even a temporary hire, with dedicated time for the project was in charge during the initial building phase. Volunteer assistance has been difficult to motivate and sustain.

Implications

• NLM''s Go Local proposal guidelines accurately identify the factors that institutions should pay close attention to when planning a Go Local project.
• NLM should emphasize continuity plans to address project coordinator turnover.
• NLM should develop a more formal orientation plan for new project coordinators to assist program continuity at the sponsoring institutions.

     

Situated Self-Regulation: Modeling the Interrelationships Among Instruction,Assessment, Learning Strategies and Academic Performance

To succeed academically, college students must actively construct course information, synthesize this information with information from texts and other resources, understand this information so that they can succeed on various forms of assessments and ultimately retain this information for the long term. While the complexity of these demands has been modeled somewhat metaphorically, there has been little ecologically valid research into learning in authentic classroom contexts. The present study examines the interrelationships among student perceptions of the learning context, test complexity, study strategies, and academic performance. Results of a path analysis demonstrated that perceptions of the teaching format and test complexity were positively related to the study strategies reported, and these study strategies were further related to the reported course performance.     

The development of beginning mathematics teacher pedagogical content knowledge

Recent research efforts (Schmidt et al. in The preparation gap: teacher education for middle school mathematics in six countries, MSU Center for Research in Mathematics and Science Education, 2007) demonstrate that teacher development programs in high-performing countries offer experiences that are designed to develop both mathematical knowledge and pedagogical knowledge. However, identifying the nature of the mathematical knowledge and the pedagogical content knowledge (PCK) required for effective teaching remains elusive (Ball et al. in J Teacher Educ 59:389–407, 2008). Building on the initial conceptual framework of Magnusson et al. (Examining pedagogical content knowledge, Kluwer, Dordrecht, pp 95–132, 1999), we examined the PCK development for two beginning middle and secondary mathematics teachers in an alternative certification program. The PCK development of these two individuals varied due to their focus on developing particular aspects of their PCK, with one individual focusing on assessment and student understanding, and the other individual focusing on curricular knowledge. Our findings indicate that these individuals privileged particular aspects of their knowledge, leading to differences in their PCK development. This study provides insight into the specific aspects of PCK that developed through the course of actual instructional practice, providing a lens for future research in this area.