Textual Mediation in Simulated Nursing Handoffs: Examining How Student Writing Coordinates Action

In clinical nursing simulations, a group of students provide care for a robotic patient during a structured scenario. As care is transferred from one group to another, they participate in a patient handoff, with outgoing students passing key information onto incoming students. In healthcare, the nursing handoff is a critical and perilous communication moment that is mediated by a range of participants and texts. Drawing on observations and video recordings of 52 simulation handoffs in the United States, this article examines how two student-designed texts – a collaborative patient chart and individual notes – are leveraged during the handoff. I also consider how handoff talk and writing changes as student nursing knowledge increases over the course of a year. By focusing on textual mediation of the simulated nursing handoff, this article contributes to existing research on professional writing pedagogy and to nursing scholarship on the handoff. Ultimately, it argues that a textual mediation framework can help bridge class room and professional contexts by evaluating student writing not for how successfully it meets a set of imposed criteria but for how effectively it supports classroom activities

Simulating the conflict between reputation and profitability for online rating portals

We simulate the process of possible interactions between a set of competitive services and a set of portals that provide online rating for these services. We argue that to have a profitable business, these portals are forced to have subscribed services that are rated by the portals. To satisfy the subscribing services, we make the assumption that the portals improve the rating of a given service by one unit per transaction that involves payment. In this study we follow the 'what-if' methodology, analysing strategies that a service may choose from to select the best portal for it to subscribe to, and strategies for a portal to accept the subscription such that its reputation loss, in terms of the integrity of its ratings, is minimised. We observe that the behaviour of the simulated agents in accordance to our model is quite natural from the real-would perspective. One conclusion from the simulations is that under reasonable conditions, if most of the services and rating portals in a given industry do not accept a subscription policy similar to the one indicated above, they will lose, respectively, their ratings and reputations, and, moreover the rating portals will have problems in making a profit. Our prediction is that the modern portal-rating based economy sector will eventually evolve into a subscription process similar to the one we suggest in this study, as an alternative to a business model based purely on advertising

Moving from Data-Constrained to Data-Enabled Research: Experiences and Challenges in Collecting, Validating and Analyzing Large-Scale e-Commerce Data

Widespread e-commerce activity on the Internet has led to new opportunities to collect vast amounts of micro-level market and nonmarket data. In this paper we share our experiences in collecting, validating, storing and analyzing large Internet-based data sets in the area of online auctions, music file sharing and online retailer pricing. We demonstrate how such data can advance knowledge by facilitating sharper and more extensive tests of existing theories and by offering observational underpinnings for the development of new theories. Just as experimental economics pushed the frontiers of economic thought by enabling the testing of numerous theories of economic behavior in the environment of a controlled laboratory, we believe that observing, often over extended periods of time, real-world agents participating in market and nonmarket activity on the Internet can lead us to develop and test a variety of new theories. Internet data gathering is not controlled experimentation. We cannot randomly assign participants to treatments or determine event orderings. Internet data gathering does offer potentially large data sets with repeated observation of individual choices and action. In addition, the automated data collection holds promise for greatly reduced cost per observation. Our methods rely on technological advances in automated data collection agents. Significant challenges remain in developing appropriate sampling techniques integrating data from heterogeneous sources in a variety of formats, constructing generalizable processes and understanding legal constraints. Despite these challenges, the early evidence from those who have harvested and analyzed large amounts of e-commerce data points toward a significant leap in our ability to understand the functioning of electronic commerce.Comment: Published at http://dx.doi.org/10.1214/088342306000000231 in the Statistical Science (http://www.imstat.org/sts/) by the Institute of Mathematical Statistics (http://www.imstat.org

LANDSAT menhaden and thread herring resources investigation

The author has identified the following significant results. The relationship between the distribution of menhaden and selected oceanographic parameters (water color, turbidity, and possibly chlorophyll concentrations) was established. Similar relationships for thread herring were not established nor were relationships relating to the abundance of either species. Use of aircraft and LANDSAT remote sensing instruments to measure or infer a set of basic oceanographic parameters was evaluated. Parameters which could be accurately inferred included surface water temperature, salinity, and color. Water turbidity (Secchi disk) was evaluated as marginally inferrable from the LANDSAT MSS data and chlorophyll-a concentrations as less than marginal. These evaluations considered the parameters only as experienced in the two test areas using available sensors and statistical techniques

Primary Surplus Behavior and Risks to Fiscal Sustainability in Emerging Market Countries: A "Fan-Chart" Approach

This paper proposes a probabilistic approach to public debt sustainability analy-sis (DSA) using "fan charts." These depict the magnitude of risks-upside and downside-surrounding public debt projections as a result of uncertain economic conditions and policies. We propose a simulation algorithm for the path of public debt under realistic shock configurations, combining pure economic disturbances (to growth, interest rates, and exchange rates), the endogenous policy response to these, and the possible shocks arising from fiscal policy itself. The paper empha-sizes the role of fiscal behavior, as well as the structure of disturbances facing the economy and due to fiscal policy, in shaping the risk profile of public debt. Fan charts for debt are derived from the "marriage" between the pattern of shocks on the one hand and the endogenous response of fiscal policy on the other. Applications to Argentina, Brazil, Mexico, South Africa, and Turkey are used to illustrate the approach and its limitations. Copyright 2006, International Monetary Fund