53 research outputs found
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The use of made-up users
While the existence of fictitious users of financial statements has been confirmed in previous research, our study investigates how this powerful yet ‘made-up’ construct is deployed within the discourses of the main stakeholders as they shape regulatory debates in the international accounting standard-setting arena, including ‘real’ users themselves. Our study draws on Bourdieu’s theorization of dominant discourse as a form of power, and extends it with the phraseological theory of meaning, specifically the linguistic concept of collocation, which focuses on the habitual choices of words in discourse. Using this framework, we conduct a comparative analysis of the recurrent language choices around the term ‘user’ in comment letters submitted on the selected IASB’s regulatory proposals. We provide empirical evidence for the existence of commonalties and subtle differences in the ways in which made-up users are discursively operationalized by the four key accounting constituent groups, the accounting profession, prepares, regulators and ‘real’ users of financial statements. At the theoretical and methodological level, our study showcases the explanatory power of the concept of collocation to identify and interrogate implicit patterns of dominant discourse as set forth by Bourdieu. We also show that the close investigation of how the dominant discourse of the made-up users works generates a series of new why questions regarding the ‘real’ users’ role in accounting standard setting
NEUROPHYSIOLOGICAL MECHANISMS IN THE PUPILLARY CONTROL SYSTEM.
NEUROPHYSIOLOGICAL MECHANISMS IN THE PUPILLARY CONTROL SYSTEM
Advanced Visual Analytics Interfaces for Adverse Drug Event Detection
Adverse reactions to drugs are a major public health care issue. Currently, the Food and Drug Administration (FDA) publishes quarterly reports that typically contain on the order of 200,000 adverse incidents. In such numerous incidents, low frequency events that are clinically highly significant often remain undetected. In this paper, we introduce a visual analytics system to solve this problem using (1) high scalable interfaces for analyzing correlations between a number of complex variables (e.g., drug and reaction); (2) enhanced statistical computations and interactive relevance filters to quickly identify significant events including those with a low frequency; and (3) a tight integration of expert knowledge for detecting and validating adverse drug events. We applied these techniques to the FDA Adverse Event Reporting System and were able to identify important adverse drug events, such as the known association of the drug Avandia with myocardial infarction and Seroquel with diabetes mellitus, as well as low frequency events such as the association of Boniva with femur fracture. In our evaluation, we found over 90% of the adverse drug events that were published in the Institute for Safe Medication Practices (ISMP) reports from 2009 to 2012. In addition, our domain expert was able to identify some previously unknown adverse drug events
Real-Time digital libraries based on widely distributed, high performance management of large data objects
Disparities in Stroke Rehabilitation: Results of a Study in an Integrated Health System in Northern California
Does Postacute Care Site Matter? A Longitudinal Study Assessing Functional Recovery After a Stroke
Designing and Implementing a System for Tracking Functional Status After Stroke: A Feasibility Study
Serrated and Adenomatous Polyp Detection Increases With Longer Withdrawal Time: Results From the New Hampshire Colonoscopy Registry
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