Reputation and Legitimacy : accreditation and rankings to assess organizations

A key perspective on reputation is that of assessment. Much of the communication literature focuses on the influence organizations have on impression formation. This chapter however suggests that in order to understand reputation assessment, it is also important to understand the related concept of legitimacy. It addresses two approaches to understanding reputation namely accreditation and ranking. Accreditation alludes to concepts of legitimacy in which firms may acquire credibility by meeting formalized standards of certification. Ranking deals with categorizing and rating organizational reputations so that they may be assessed relative to one another. The chapter explores the various ways in which the mechanisms of accreditation and ranking operate and the role of social actors in developing and applying them. Ranking systems that provide the mechanism for comparing organizations and assessing their relative value are also explored.

Utilising hospital data to inform product safety prioritisation : the application of RAPEX severity rankings in ICD-coded burn data

Background The implementation of the Australian Consumer Law in 2011 highlighted the need for better use of injury data to improve the effectiveness and responsiveness of product safety (PS) initiatives. In the PS system, resources are allocated to different priority issues using risk assessment tools. The rapid exchange of information (RAPEX) tool to prioritise hazards, developed by the European Commission, is currently being adopted in Australia. Injury data is required as a basic input to the RAPEX tool in the risk assessment process. One of the challenges in utilising injury data in the PS system is the complexity of translating detailed clinical coded data into broad categories such as those used in the RAPEX tool. Aims This study aims to translate hospital burns data into a simplified format by mapping the International Statistical Classification of Disease and Related Health Problems (Tenth Revision) Australian Modification (ICD-10-AM) burn codes into RAPEX severity rankings, using these rankings to identify priority areas in childhood product-related burns data. Methods ICD-10-AM burn codes were mapped into four levels of severity using the RAPEX guide table by assigning rankings from 1-4, in order of increasing severity. RAPEX rankings were determined by the thickness and surface area of the burn (BSA) with information extracted from the fourth character of T20-T30 codes for burn thickness, and the fourth and fifth characters of T31 codes for the BSA. Following the mapping process, secondary data analysis of 2008-2010 Queensland Hospital Admitted Patient Data Collection (QHAPDC) paediatric data was conducted to identify priority areas in product-related burns. Results The application of RAPEX rankings in QHAPDC burn data showed approximately 70% of paediatric burns in Queensland hospitals were categorised under RAPEX levels 1 and 2, 25% under RAPEX 3 and 4, with the remaining 5% unclassifiable. In the PS system, prioritisations are made to issues categorised under RAPEX levels 3 and 4. Analysis of external cause codes within these levels showed that flammable materials (for children aged 10-15yo) and hot substances (for children aged <2yo) were the most frequently identified products. Discussion and conclusions The mapping of ICD-10-AM burn codes into RAPEX rankings showed a favourable degree of compatibility between both classification systems, suggesting that ICD-10-AM coded burn data can be simplified to more effectively support PS initiatives. Additionally, the secondary data analysis showed that only 25% of all admitted burn cases in Queensland were severe enough to trigger a PS response.

Utilising hospital data to inform product safety prioritisation : the application of RAPEX severity rankings in ICD-coded Burn Data

Background The implementation of the Australian Consumer Law in 2011 highlighted the need for better use of injury data to improve the effectiveness and responsiveness of product safety (PS) initiatives. In the PS system, resources are allocated to different priority issues using risk assessment tools. The rapid exchange of information (RAPEX) tool to prioritise hazards, developed by the European Commission, is currently being adopted in Australia. Injury data is required as a basic input to the RAPEX tool in the risk assessment process. One of the challenges in utilising injury data in the PS system is the complexity of translating detailed clinical coded data into broad categories such as those used in the RAPEX tool. Aims This study aims to translate hospital burns data into a simplified format by mapping the International Statistical Classification of Disease and Related Health Problems (Tenth Revision) Australian Modification (ICD-10-AM) burn codes into RAPEX severity rankings, using these rankings to identify priority areas in childhood product-related burns data. Methods ICD-10-AM burn codes were mapped into four levels of severity using the RAPEX guide table by assigning rankings from 1-4, in order of increasing severity. RAPEX rankings were determined by the thickness and surface area of the burn (BSA) with information extracted from the fourth character of T20-T30 codes for burn thickness, and the fourth and fifth characters of T31 codes for the BSA. Following the mapping process, secondary data analysis of 2008-2010 Queensland Hospital Admitted Patient Data Collection (QHAPDC) paediatric data was conducted to identify priority areas in product-related burns. Results The application of RAPEX rankings in QHAPDC burn data showed approximately 70% of paediatric burns in Queensland hospitals were categorised under RAPEX levels 1 and 2, 25% under RAPEX 3 and 4, with the remaining 5% unclassifiable. In the PS system, prioritisations are made to issues categorised under RAPEX levels 3 and 4. Analysis of external cause codes within these levels showed that flammable materials (for children aged 10-15yo) and hot substances (for children aged <2yo) were the most frequently identified products. Discussion and conclusions The mapping of ICD-10-AM burn codes into RAPEX rankings showed a favourable degree of compatibility between both classification systems, suggesting that ICD-10-AM coded burn data can be simplified to more effectively support PS initiatives. Additionally, the secondary data analysis showed that only 25% of all admitted burn cases in Queensland were severe enough to trigger a PS response.

The interactive PRP for diversifying document rankings

The assumptions underlying the Probability Ranking Principle (PRP) have led to a number of alternative approaches that cater or compensate for the PRP's limitations. In this poster we focus on the Interactive PRP (iPRP), which rejects the assumption of independence between documents made by the PRP. Although the theoretical framework of the iPRP is appealing, no instantiation has been proposed and investigated. In this poster, we propose a possible instantiation of the principle, performing the first empirical comparison of the iPRP against the PRP. For document diversification, our results show that the iPRP is significantly better than the PRP, and comparable to or better than other methods such as Modern Portfolio Theory.

Using emotion to diversify document rankings

The aim of this paper is to investigate the role of emotion features in diversifying document rankings to improve the effectiveness of Information Retrieval (IR) systems. For this purpose, two approaches are proposed to consider emotion features for diversification, and they are empirically tested on the TREC 678 Interactive Track collection. The results show that emotion features are capable of enhancing retrieval effectiveness.

Outdated journal rankings and the ERA exercise

As the results of the latest Excellence in Research Australia (ERA) exercise come closer to being announced, universities around Australia are holding their collective breaths. The ERA claims to be an assessment of research strengths and quality at Australian universities. While it is not supposed to produce a set of league tables, ultimately that is what tends to happen...

BoostMap: A Method for Efficient Approximate Similarity Rankings

This paper introduces BoostMap, a method that can significantly reduce retrieval time in image and video database systems that employ computationally expensive distance measures, metric or non-metric. Database and query objects are embedded into a Euclidean space, in which similarities can be rapidly measured using a weighted Manhattan distance. Embedding construction is formulated as a machine learning task, where AdaBoost is used to combine many simple, 1D embeddings into a multidimensional embedding that preserves a significant amount of the proximity structure in the original space. Performance is evaluated in a hand pose estimation system, and a dynamic gesture recognition system, where the proposed method is used to retrieve approximate nearest neighbors under expensive image and video similarity measures. In both systems, BoostMap significantly increases efficiency, with minimal losses in accuracy. Moreover, the experiments indicate that BoostMap compares favorably with existing embedding methods that have been employed in computer vision and database applications, i.e., FastMap and Bourgain embeddings.

Relative Uncertainty and Additively Representable Set Rankings

This paper proposes a definition of relative uncertainty aversion for decision models under complete uncertainty. It is shown that, for a large class of decision rules characterized by a set of plausible axioms, the new criterion yields a complete ranking of those rules with respect to the relative degree of uncertainty aversion they represent. In addition, we address a combinatorial question that arises in this context, and we examine conditions for the additive representability of our rules.

¿Rankings educativos : indicadores de resultados o de diferencias socioeconómicas?

Resumen tomado de la publicación

Los rankings universitarios : estado de la cuestión y posibles aplicaciones al caso español.

Resumen tomado de la publicación

Rankings internacionales y calidad de los sistemas universitarios.

Resumen tomado de la publicación. Monográfico con el título: Tiempos de cambio universitario en Europa

Gu??a de buenas pr??cticas para la participaci??n de las universidades espa??olas en los rankings internacionales

Resumen basado en el de la publicaci??n

Rankings internacionales : metodolog??a y posicionamiento de las universidades espa??olas

Se analiza un grupo de rankings internacionales, los denominados League Tables (ARWU, THE, QS); un segundo grupo de rankings centrados en resultados de investigaci??n (CWTS, HEEACT, SCIMAGO Institutions Ranking, URAP); y un tercer grupo de rankings internacionales basados en varios indicadores sin intenci??n de crear tablas ordenadas de instituciones (CHE, UMultirank, U-Ranking).

An??lisis de los datos de las universidades espa??olas en los rankings internacionales

Se analiza la informaci??n con la que los rankings globales ( Arwu, THE y QS, SCIMAGO; CWTS, HEEACT y CHE; U-Multirank y U-Ranking.) elaboran sus indicadores as?? como las puntuaciones y posiciones resultantes obtenidas por las universidades espa??olas. A partir de una solicitud de participaci??n canalizada desde el Ministerio de Educaci??n, Cultura y Deporte a las 72 universidades espa??olas, p??blicas y privadas que presentan datos de investigaci??n en el Observatorio IUNE, se obtienen y analizan los cuestionarios e informes de datos para la participaci??n en los rankings de 2013 de 19 universidades. A continuaci??n, se describen los datos solicitados a las universidades por los tres rankings, que est??n referidos a profesorado, estudiantes, t??tulos y datos econ??micos. Por ??ltimo, se detallan los datos que cada universidad participante en el estudio aporta a los rankings y con los que ??stos obtienen sus indicadores, mostr??ndose los perfiles de cada una de ellas. Tambi??n se muestra el nivel de concordancia entre los datos solicitados y los aportados.