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In this article, we show how the Eigenfactor score, originally designed for ranking scholarly journals, can be adapted to rank the scholarly output of authors, institutions, and countries based on author-level citation data. Using the methods described in this article, we provide Eigenfactor rankings for 84,808 disambiguated authors of 240,804 papers in the Social Science Research Network (SSRN)—a preprint and postprint archive devoted to the rapid dissemination of scholarly research in the social sciences and humanities. As an additive metric, the Eigenfactor scores are readily computed for collectives such as departments or institutions as well. We show that a collective's Eigenfactor score can be computed either by summing the Eigenfactor scores of its members or by working directly with a collective-level cross-citation matrix. We provide Eigenfactor rankings for institutions and countries in the SSRN repository. With a network-wide comparison of Eigenfactor scores and download tallies, we demonstrate that Eigenfactor scores provide information that is both different from and complementary to that provided by download counts. We see author-level ranking as one filter for navigating the scholarly literature, and note that such rankings generate incentives for more open scholarship, because authors are rewarded for making their work available to the community as early as possible and before formal publication.

Interest in and use of article-level metrics (ALMs) has grown rapidly amongst the research community, by researchers, publishers, funders, and research institutions. As this happens, it is critical to ensure secure and reliable data that is trustworthy and can be used by all. Two case studies are presented, which illustrate different approaches to establishing ALM data integrity., Article-level metric (ALM) data need to be secure and reliable if they are to be trusted and used by all. This Perspective explores the different approaches taken by two organizations to establish ALM data integrity.

Severe muscular dystrophy (MD) has historically led to death in early adulthood, due to mainly cardiopulmonary complications. However, with newer methods of cardiac and respiratory management, survival has improved, and patients with MD are more frequently undergoing procedures requiring deep sedation or anesthesia. Respiratory management of these patients during procedures is challenging; safe and effective options for respiratory support are needed. In this report, we describe our experience using the laryngeal mask airway (LMA) to provide respiratory support during deep sedation or anesthesia for eight patients with severe MD during the following medical procedures: eight percutaneous endoscopic gastrostomy (PEG) placements, three lithotripsies, and placement of an implantable cardioverter-defibrillator. We also review the benefits and risks of the LMA in the context of other respiratory support options for people with MD, and the integral role of non-invasive positive pressure ventilation (NPPV) during induction of and recovery from deep sedation or general anesthesia.

We review the anesthetic implications of Joubert syndrome and report that spinal anesthesia under intravenous propofol sedation proved satisfactory for repair of an inguinal hernia in a spontaneously ventilating infant with this syndrome. We caution that anatomical peculiarities may complicate performance of a caudal epidural block and suggest consideration of the use of caffeine to ameliorate the apneic episodes seen in early infancy in this syndrome.

These are the slides from my presentation at the AACSB meeting on 30 April 2011 in New York, NY. The session was titled "The Impact of Research" and my co-presenters were John Peters, President, GSE Research Limited and Howard Thomas, Dean and LKCSB Chair in Strategic Management, Singapore Management University.

In this paper, we show how the Eigenfactor(R) score, originally designed for ranking scholarly journals, can be adapted to rank the scholarly output of authors, institutions, and countries based on authorlevel citation data. Using the methods described herein, we provide Eigenfactor rankings for 84,808 disambiguated authors of 240,804 papers in the Social Science Research Network (SSRN) — a pre and post-print archive devoted to the rapid dissemination of scholarly research in the social sciences and humanities. As an additive metric, the Eigenfactor scores are readily computed for collectives such as departments or institutions as well. We show that a collective’s Eigenfactor score can be computed either by summing the Eigenfactor scores of its members, or by working directly with a collective-level cross-citation matrix. To illustrate, we provide Eigenfactor rankings for institutions and countries in the SSRN repository. With a network-wide comparison of Eigenfactor scores and download tallies, we demonstrate that Eigenfactor scores provide information that is both different from and complementary to that provided by download counts. We see author-level ranking as one filter for navigating the scholarly literature, and note that such rankings generate incentives for more open scholarship, as authors are rewarded for making their work available to the community as early as possible and prior to formal publication. NOTE: Because of the incompleteness of the SSRN CiteReader data at this time, please check back at this URL for updated versions of this paper for updated results over the next 2 years. In addition, when citing this paper please include the following: Data as of March 14, 2011.

Do you read everything in your field today? Do you even know what everything means any more? Readers of scholarly research are faced with an overabundance of information due to interdisciplinary subject areas, access to research at earlier and multiple stages, and simply more research from more scholars. My simple definition of innovation is the ability to create new things by being exposed to a broader and deeper set of existing things, but broader and deeper have their limits. There is no substitute for reading and truly comprehending a specific article, but there aren’t enough hours in the day to read everything. We need better tools to know what research we need to read. We need to know what we don’t know.

Individuals with Duchenne muscular dystrophy may benefit from gastrostomy tube feeding due to progressive dysphagia and malnutrition. However, due to their severely impaired pulmonary function, these individuals are at risk of severe complications when they are sedated or undergo anesthesia for the procedure. We previously described a technique of noninvasive positive pressure ventilation to provide respiratory support during gastrostomy tube placement in such patients, but this technique had risks and limitations. In this case report, we examine two alternative techniques we used to provide respiratory support successfully to patients with severe muscular dystrophy and malnutrition who underwent percutaneous endoscopic gastrostomy tube placement. We then review the literature and discuss the potential benefits, risks, and limitations of the above techniques and of other options for gastrostomy placement in people with severe muscular dystrophy.

These are the slides from my presentation at the AALS meeting on 7 January 2005 in San Francisco, CA. The session was 'Electronic Repositories for Legal Scholarship' and was moderated by Claire M. Germain.

Economic growth relies in part on efficient advancement and application of research and development (R&D) knowledge. This requires access to data about science—in particular, R&D inputs and outputs such as grants, patents, publications, and data sets, to support an understanding of how R&D information is produced and what affects its availability. But there is a cacophony of R&D-related data across countries, disciplines, data providers, and sectors. Burdened with data that are inconsistently specified, researchers and policy-makers have few incentives or mechanisms to share or interlink cleaned data sets. Access to these data is limited by a patchwork of laws, regulations, and practices that are unevenly applied and interpreted ( 1 ). A Web-based infrastructure for data sharing and analysis could help. Data exchange standards are a first step. We describe administrative and technical demands and opportunities to meet them.

A 6-month-old infant presenting with pericardial effusion was found to have a malignant rhabdoid tumor of the heart. As visualized by two-dimensional echocardiography and subsequently by contrast-enhanced computerized axial tomographic scanning, the tumor arose from the left ventricular free wall and grew into the pericardial space. Despite two courses of single-agent chemotherapy with doxorubicin, the child died 3 months later. This is the first reported case of malignant rhabdoid tumor of the heart, and the fifth case of a primary cardiac malignancy in an infant.

Intracranial volume-pressure response was assessed in 6 children suffering from metabolic coma and ranging in age 2 months-13 years. No untoward pressure or infectious complications occurred. The relationship between baseline mean intracranial pressure (MICP) and volume-pressure response assessment (VPRA) in these patients seems to be exponential rather than linear. By itself, the test is no better than baseline MICP at identifying patients at greatest risk of developing significantly increased intracranial pressure (ICP). When used in conjunction with baseline MICP, this method of VPRA identifies a population with an 80% risk of developing serious ICP elevations within a 4 h time period. Patients with best overall prognosis had significantly lower mean VPRA values than those with poorest overall prognosis.