The Benefits and Costs of Using Metadata to Improve Enterprise Document Search

The literature shows that there are many problems with enterprise document search. Studies reveal that typical knowledge workers spend between 10% and 20% of their time searching for documents they never find. While many argue that metadata can improve enterprise document search, in reality few organizations use metadata. This represents a missed opportunity. This article describes the results of two experiments that use simulation to evaluate the actual impact of metadata on the costs and benefits of enterprise search. The first study provides quantitative evidence of the increase in recall and precision that stems from the use of metadata‐enhanced document searches. The second study demonstrates that simple metadata structures can be nearly as effective as complex ones, implying that the cost of creating and maintaining metadata is likely to be lower than generally thought. This is the first study to provide explicit quantitative evidence of the gains that can be achieved from the use of metadata, and one of only a handful of studies that examines the cost of creating and maintaining metadata.     

A house divided: deinstitutionalization, medicare and the Canadian Mental Health Association in Saskatchewan, 1944-1964

Defined as a set of distinct processes that included the declining use of large psychiatric institutions and the increasing use of outpatient services and general hospitals, deinstitutionalization occurred earlier in Saskatchewan than other provinces in Canada. It was led by a CCF government dedicated to major change across a number of sectors including mental health, assisted by one of the most influential and well-organized social movement organizations of the 1950s, the Saskatchewan Division of the Canadian Mental Health Association (SCMHA). However, by the late 1950s and early 1960s, the SCMHA opposed the CCF government's policy priority on medicare which it felt came at the expense of mental health care, in particular the implementation of a regional psychiatric hospital system called the Saskatchewan Plan. As a consequence, the SCMHA, once such a powerful ally of the CCF government in health reform, formed a strategic and temporary coalition with the anti-medicare forces in the province. Given the fact that a number of medical staff within the government's department of public health were prominent members of the SCMHA, the CCF government found that it occupied an increasingly divided house at the very time it was struggling to introduce medicare in the midst of civil unrest and a doctors' strike.     

Selective Authenticity: Civil War Reenactors and Credible Reenactments

This article addresses authenticity and how it is selectively used by Civil War reenactors to create credible reenactments. The Civil War provides a structured set of scenarios for reenactors to use as a backdrop for their participation. Some use this backdrop to bring objects to the forefront and others use this setting as a way to interact with an audience person to person. This research indicates that authenticity may come through on different levels for individuals participating in the same activity. An authentic experience or object is authentic because it has an important immediate meaning. The objects and narratives displayed by reenactors may be set in specific history but this does not mean that these same objects and narratives are part of that history. This paper contributes to the study of authenticity by examining groups of Civil War reenactors and where their focus of authenticity lies whether it is on authentic objects or interactions.     

Potential Lives,Impossible Deaths

The number of civilian casualties in Afghanistan has increased dramatically in recent years as the International Security Assistance Force (ISAF) has tried to put down the Taliban insurgency. Reports of civilian casualties are, however, frequently dismissed as being examples of Taliban propaganda or blamed on the actions of enemy fighters, while the tragic loss of civilians is rarely marked or even acknowledged within the dominant frames of war. At first glance, the fact that civilians are so easily expendable appears to be at odds with the humanitarian intentions underpinning the war. However, I argue that the rhetoric of humanitarianism operates to preclude Afghans from appearing as recognizable human beings, foreclosing the possibility that they possess a life worthy of protection. Drawing on the work of Judith Butler, I will trace the ways in which Afghans have been reduced to the status of absolute victims, denied the very essence of their humanity and therefore a publically grievable death. By effectively constructing them as the living-dead, existing in a state of abeyance, Afghans have been exposed to a deathly logic in which their lives are expendable in the quest to make them liveable once again.     

Statistical estimation and comparison of group-specific bivariate correlation coefficients in family-type clustered studies

Bivariate correlation coefficients (BCCs) are often calculated to gauge the relationship between two variables in medical research. In a family-type clustered design where multiple participants from same units/families are enrolled, BCCs can be defined and estimated at various hierarchical levels (subject level, family level and marginal BCC). Heterogeneity usually exists between subject groups and, as a result, subject level BCCs may differ between subject groups. In the framework of bivariate linear mixed effects modeling, we define and estimate BCCs at various hierarchical levels in a family-type clustered design, accommodating subject group heterogeneity. Simplified and modified asymptotic confidence intervals are constructed to the BCC differences and Wald type tests are conducted. A real-world family-type clustered study of Alzheimer disease (AD) is analyzed to estimate and compare BCCs among well-established AD biomarkers between mutation carriers and non-carriers in autosomal dominant AD asymptomatic individuals. Extensive simulation studies are conducted across a wide range of scenarios to evaluate the performance of the proposed estimators and the type-I error rate and power of the proposed statistical tests.Abbreviations: BCC: bivariate correlation coefficient; BLM: bivariate linear mixed effects model; CI: confidence interval; AD: Alzheimer’s disease; DIAN: The Dominantly Inherited Alzheimer Network; SA: simple asymptotic; MA: modified asymptoticKEYWORDS: Bivariate correlation coefficient, bivariate linear mixed effects model, parameter estimation, confidence interval, hypothesis testing, type-I error/size and power     

Optimal Abort Rules for Multiattempt Missions

Many real‐world systems use mission aborts to enhance their survivability. Specifically, a mission can be aborted when a certain malfunction condition is met and a risk of a system loss in the case of a mission continuation becomes too high. Usually, the rescue or recovery procedure is initiated upon the mission abort. Previous works have discussed a setting when only one attempt to complete a mission is allowed and this attempt can be aborted. However, missions with a possibility of multiple attempts can occur in different real‐world settings when accomplishing a mission is really important and the cost‐related and the time‐wise restrictions for this are not very severe. The probabilistic model for the multiattempt case is suggested and the tradeoff between the overall mission success probability (MSP) and a system loss probability is discussed. The corresponding optimization problems are formulated. For the considered illustrative example, a detailed sensitivity analysis is performed that shows specifically that even when the system's survival is not so important, mission aborting can be used to maximize the multiattempt MSP.     

Feeling at Risk Matters: Water Managers and the Decision to Use Forecasts

Experts contend that weather and climate forecasts could have an important role in risk management strategies for community water systems. Yet, most water managers make minimal use of these forecasts. This research explores the determinants of the use of weather and climate forecasts by surveying managers of community water systems in two eastern American states (South Carolina and the Susquehanna River Basin of Pennsylvania). Assessments of the reliability of weather and climate forecasts are not driving their use as water managers who find forecasts reliable are no more likely to use them than are managers who find them unreliable. Although larger systems and those depending on surface water are more likely to use forecasts for some (but not all) purposes, the strongest determinant of forecast use is risk perceptions. Water managers who expect to face problems from weather events in the next decade are much more likely to use forecasts than are water managers who expect few problems. Their expectations of future problems are closely linked with past experience: water managers who have had problems with specific types of weather events (e.g., flood emergencies) in the last 5 years are likely to expect to experience problems in the next decade. Feeling at risk, regardless of the specific source of that weather-related risk, stimulates a decision to use weather and climate forecasts.