1,721,016 research outputs found
« Choix rationnels », conflit ethnique et culture
No full textVarshney Ashutosh, Bouyssou Rachel. « Choix rationnels », conflit ethnique et culture. In: Critique internationale, vol. 5. 1999. Mémoire, justice et réconciliation, sous la direction de Pierre Hassner. pp. 50-58
Ethnic Diversity and Ethnic Strife: An Interdisciplinary Perspective
Full text linkThe objective of this paper is to present an overview of ethnicity, ethnic strife and its consequences, as seen from the perspective of the disciplines of economics, political science, social anthropology and sociology. What exactly is ethnicity--how is it to be defined, characterized and measured? What exactly are the causal links from ethnicity so defined to its presumed consequences, including tension and violence? What are the feedback loops from the consequences of ethnic divisions back to these divisions themselves? How can policy, if at all, mitigate ethnic divisions and ethnic conflict? Finally, what role does interdisciplinarity have in helping to understand ethnicity and ethnic strife, and how can interdisciplinary collaboration be enhanced? These are the questions which this paper takes up and deals with in sequence.Ethnicity, Conflict, Interdisciplinary Approaches, International Development, International Relations/Trade,
Patterns of collective violence in Indonesia
No full textIndonesia has witnessed explosive group violence in recent years, but unlike its plentiful economic statistics, the data on conflict were remarkably sketchy. Because it wanted to give the appearance of order and stability, the New Order did not believe in publishing reports on group conflict, nor did it allow researchers and non-governmental organizations to probe the patterns and causes of conflict. This paper is based on the first database ever constructed on group violence in Indonesia. Following, and adapting for Indonesian conditions, methodologies developed and used elsewhere, we cover the years 1990-2003, split the data into various categories, and identify the national, regional and local patterns of collective violence. Much that we find is surprising, given the common perceptions about, and in, Indonesia. Of the several conclusions we draw, the most important one is that group violence in Indonesia is highly locally concentrated. Fifteen districts (kabupaten and kota), in which a mere 6.5 per cent of the country’s population lived in 2000, account for as much as 85.5 per cent of all deaths in group violence. Group violence is not as widespread as is normally believed. If we can figure out why so many districts remained reasonably quiet, even as the violent systemic shifts, such the decline of the New Order, deeply shook fifteen districts causing a large number of deaths, we may also understand how one should deal with the cataclysms of the endemically violent towns, as also how one might think about preventing, or minimizing, group violence in the coming years
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Variations on the Author
Full text link“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Appropriate Similarity Measures for Author Cocitation Analysis
Full text linkWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
A deep learning approach for COVID-19 detection from computed tomography scans
No full textThe classification of COVID-19 patients from chest computed tomography (CT) images is a very difficult task due to the similarities observed with other lung diseases. Based on various CT scans of COVID and non-COVID patients, the aim of this chapter is to propose a simple deep learning architecture and compare its diagnostic performance using transfer learning and several machine learning techniques that could extract COVID-19’s graphical features and classify them in order to provide a clinical diagnosis ahead of the pathogenic test, thus saving critical time for disease control. We also compare our approach and show that it outperforms various previous state-of-the-art techniques. We propose a deep learning architecture for transfer learning that is just a simple modification of eight new layers on the ImageNet pretrained convolutional neural networks (CNNs) which yielded us the best test accuracy of 98.30%, F1 score of 0.982, area under the receiver operating characteristic (ROC) curve of 0.982, and kappa value of 0.964 after training. Moreover, we use the proposed architecture for feature extraction and study the performance of various classifiers on them and were able to obtain the highest test accuracy of 91.75% with K-nearest neighbors.
Also, we compare multiple CNNs and machine learning models for their diagnostic potential in disease detection and suggest a much faster and automated disease detection methodology. We show that smaller and memory efficient architectures are equally good compared to deep and heavy architectures at classifying chest CTs. We also show that visual geometry group (VGG) architectures are overall the best for this task
Dispelling the Myths Behind First-author Citation Counts
Full text linkWe conducted a full-scale evaluative citation analysis study of scholars in the XML research field to explore just how different from each other author rankings resulting from different citation counting methods actually are, and to demonstrate the capability of emerging data and tools on the Web in supporting more realistic citation counting methods. Our results contest some common arguments for the continued
use of first-author citation counts in the evaluation of scholars, such as high correlations between author rankings by first-author citation counts and other citation
counting methods, and high costs of using more realistic citation counting methods that are not well-supported by the ISI databases. It is argued that increasingly available digital full text research papers make it possible for citation analysis studies to go beyond what the ISI databases have directly supported and to employ more
sophisticated methods
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