Ranking de municípios para políticas públicas de educação: comparação entre avaliações multicritério a partir do IDH

Neste artigo se desenvolvem alternativas de abordagem multicritério visando à seleção de municípios para a implementação de políticas públicas de educação. Considerando que a situação da educação no Brasil apresenta grande variabilidade, o que impacta as demandas educacionais por políticas públicas de educação de forma diferente em diferentes regiões, verifica-se a necessidade de critérios objetivos para a seleção de pontos de aplicação de recursos para o combate a desigualdades nessa área. Em particular, se discute o emprego do Índice de Desenvolvimento Humano como fundamento para decisões na área educacional. Além disso, visa-se a estabelecer condições para a comparação dessas situações segundo diferentes critérios utilizados para fundamentar políticas públicas de educação.

Prioritization of Potential Mates' History of Sexual Fidelity During a Conjoint Ranking Task

This series of studies is the first to use conjoint analysis to examine how individuals make trade-offs during mate selection when provided information about a partner's history of sexual infidelity. Across three studies, participants ranked profiles of potential mates, with each profile varying across five attributes: financial stability, physical attractiveness, sexual fidelity, emotional investment, and similarity. They also rated each attribute separately for importance in an ideal mate. Overall, we found that for a long-term mate, participants prioritized a potential partner's history of sexual fidelity over other attributes when profiles were ranked conjointly. For a short-term mate, sexual fidelity, physical attractiveness, and financial stability were equally important, and each was more important than emotional investment and similarity. These patterns contrast with participants' self-reported importance ratings of each individual attribute. Our results are interpreted within the context of previous literature examining how making trade-offs affect mate selection.

Using incomplete citation data for MEDLINE results ranking.

Information overload is a significant problem for modern medicine. Searching MEDLINE for common topics often retrieves more relevant documents than users can review. Therefore, we must identify documents that are not only relevant, but also important. Our system ranks articles using citation counts and the PageRank algorithm, incorporating data from the Science Citation Index. However, citation data is usually incomplete. Therefore, we explore the relationship between the quantity of citation information available to the system and the quality of the result ranking. Specifically, we test the ability of citation count and PageRank to identify "important articles" as defined by experts from large result sets with decreasing citation information. We found that PageRank performs better than simple citation counts, but both algorithms are surprisingly robust to information loss. We conclude that even an incomplete citation database is likely to be effective for importance ranking.

Using incomplete citation data for MEDLINE results ranking.

Information overload is a significant problem for modern medicine. Searching MEDLINE for common topics often retrieves more relevant documents than users can review. Therefore, we must identify documents that are not only relevant, but also important. Our system ranks articles using citation counts and the PageRank algorithm, incorporating data from the Science Citation Index. However, citation data is usually incomplete. Therefore, we explore the relationship between the quantity of citation information available to the system and the quality of the result ranking. Specifically, we test the ability of citation count and PageRank to identify "important articles" as defined by experts from large result sets with decreasing citation information. We found that PageRank performs better than simple citation counts, but both algorithms are surprisingly robust to information loss. We conclude that even an incomplete citation database is likely to be effective for importance ranking.

Ranking factors affecting emissions of GHG from incubated agricultural soils

Agriculture significantly contributes to global greenhouse gas (GHG) missions and there is a need to develop effective mitigation strategies. The efficacy of methods to reduce GHG fluxes from agricultural soils can be affected by a range of interacting management and environmental factors. Uniquely, we used the Taguchi experimental design methodology to rank the relative importance of six factors known to affect the emission of GHG from soil: nitrate (NO3?) addition, carbon quality (labile and non-labile C), soil temperature, water-filled pore space (WFPS) and extent of soil compaction. Grassland soil was incubated in jars where selected factors, considered at two or three amounts within the experimental range, were combined in an orthogonal array to determine the importance and interactions between factors with a L16 design, comprising 16 experimental units. Within this L16 design, 216 combinations of the full factorial experimental design were represented. Headspace nitrous oxide (N2O), methane (CH4) and carbon dioxide (CO2) concentrations were measured and used to calculate fluxes. Results found for the relative influence of factors (WFPS and NO3? addition were the main factors affecting N2O fluxes, whilst glucose, NO3? and soil temperature were the main factors affecting CO2 and CH4 fluxes) were consistent with those already well documented. Interactions between factors were also studied and results showed that factors with Little individual influence became more influential in combination. The proposed methodology offers new possibilities for GHG researchers to study interactions between influential factors and address the optimized sets of conditions to reduce GHG emissions in agro-ecosystems, while reducing the number of experimental units required compared with conventional experimental procedures that adjust one variable at a time.

Analyzing the commercial activities of a street network by ranking their nodes: a case study in Murcia, Spain

Urban researchers and planners are often interested in understanding how economic activities are distributed in urban regions, what forces influence their special pattern and how urban structure and functions are mutually dependent. In this paper, we want to show how an algorithm for ranking the nodes in a network can be used to understand and visualize certain commercial activities of a city. The first part of the method consists of collecting real information about different types of commercial activities at each location in the urban network of the city of Murcia, Spain. Four clearly differentiated commercial activities are studied, such as restaurants and bars, shops, banks and supermarkets or department stores, but obviously we can study other. The information collected is then quantified by means of a data matrix, which is used as the basis for the implementation of a PageRank algorithm which produces a ranking of all the nodes in the network, according to their significance within it. Finally, we visualize the resulting classification using a colour scale that helps us to represent the business network.

Income Ranking and convergence with physical and human capital and income equality

This paper presents an overlapping generations model with physical and human capital and income inequality. It shows that inequality impedes output growth by directly harming capital accumulation and indirectly raising the ratio of physical to human capital. The convergence speed of output growth equals the lower of the convergence speeds of the relative capital ratio and inequality, and varies with initial states. Among economies with the same balanced growth rate but different initial income levels, the ranking of income can switch in favor of those starting from low inequality and a low ratio of physical to human capital, particularly if the growth rate converges slowly. (C) 2004 Elsevier B.V. All rights reserved.

Document re-ranking by generality in bio-medical information retrieval

Document ranking is an important process in information retrieval (IR). It presents retrieved documents in an order of their estimated degrees of relevance to query. Traditional document ranking methods are mostly based on the similarity computations between documents and query. In this paper we argue that the similarity-based document ranking is insufficient in some cases. There are two reasons. Firstly it is about the increased information variety. There are far too many different types documents available now for user to search. The second is about the users variety. In many cases user may want to retrieve documents that are not only similar but also general or broad regarding a certain topic. This is particularly the case in some domains such as bio-medical IR. In this paper we propose a novel approach to re-rank the retrieved documents by incorporating the similarity with their generality. By an ontology-based analysis on the semantic cohesion of text, document generality can be quantified. The retrieved documents are then re-ranked by their combined scores of similarity and the closeness of documents’ generality to the query’s. Our experiments have shown an encouraging performance on a large bio-medical document collection, OHSUMED, containing 348,566 medical journal references and 101 test queries.

Perceptions of journal quality and research paradigm:results of a web-based survey of British accounting academics

This paper reports the results of a web-based perception study of the ranking of peer reviewed accounting journals by UK academics. The design of the survey instrument allows an interactive selection of journals to be scored. The webbased format is unique in that it also includes a step in which respondents classify the journals according to methodological perspective (paradigm). This is depicted graphically in the paper in a bubble diagram that shows the "positioning" of journals according to perceptions of both paradigm and quality.

Constructing an 'efficient frontier' of accounting journal quality

This paper reports the construction of an 'efficient frontier' of the perceived quality attributes of academic accounting journals. The analysis is based on perception data from two web-based surveys of Australasian and British academics. The research reported here contributes to the existing literature by augmenting the commonly supported single dimension of quality with an additional measure indicating the variation of perceptions of journal quality. The result of combining these factors is depicted diagrammatically in a manner that reflects the risk and return trade-off as conceptualised in the capital market model of an efficient frontier of investment opportunities. This conceptualisation of a 'market' for accounting research provides a context in which to highlight the complex issues facing academics in their roles as editors, researchers and authors. The analysis indicates that the perceptions of the so-called 'elite' US accounting journals have become unsettled particularly in Australasia, showing high levels of variability in perceived quality, while other traditionally highly ranked journals (ABR, AOS, CAR) have a more 'efficient' combination of high-quality ranking and lower dispersion of perceptions. The implications of these results for accounting academics in the context of what is often seen as a market for accounting research are discussed. © 2006 Elsevier Ltd. All rights reserved.

University ranking as social exclusion

In this article we explore the dual role of global university rankings in the creation of a new, knowledge-identified, transnational capitalist class and in facilitating new forms of social exclusion.We examine how and why the practice of ranking universities has become widely defined by national and international organisations as an important instrument of political and economic policy. We consider how the development of university rankings into a global business combining social research, marketing and public relations, as a tangible policy tool that narrowly redefines the social purposes of higher education itself. Finally, it looks at how the influence of rankings on national funding for teaching and research constrains wider public debate about the meaning of ‘good’ and meaningful education in the UK and other national contexts, particularly by shifting the debate away from democratic publics upward into the elite networked institutions of global capital. We conclude by arguing that, rather than regarding world university rankings as a means to establish criteria of educational value, the practice may be understood as an exclusionary one that furthers the alignment of higher education with neoliberal rationalities at both national and global levels.