1,720,954 research outputs found
Going Beyond Counting First Authors in Author Co-citation Analysis
Get PDFThe 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
Get PDF“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
Get PDFWe 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
Dispelling the Myths Behind First-author Citation Counts
Get PDFWe 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
koamabayili/VECTRON-author-checklist: VECTRON author checklist
No full textWe have done our best to complete the author checklist relating to the use of animals in the hut study. Note that the objective for the hut study was to evaluate the IRS treatment applications for residual efficacy against Anopheles mosquitoes, including the local An. coluzzii mosquito population. Cows were only used to attract mosquitoes into the huts and no tests were carried out directly on the cows. The author checklist is intended for use with studies where experiments are carried out on animals, which is why we have had such difficulty in completing this for the hut study, as many of the questions do not relate to how the cows were used
Author-wise bibliometric analysis based on entropy.
No full textAuthor-wise bibliometric analysis based on entropy.</p
Estimation and Classification Problems under Equality Restrictions on Parameters
No full textThis thesis deals with the problem of estimation and classification for the parametric stochastic model under the equality restriction on the model parameters. A parametric classification problem is a supervised learning problem in machine learning. The key characteristic of parametric classification problems is that they assume that the input data comes from a specific distribution and that the relationship between the input features and the output classes can be captured using a fixed set of parameters. In this thesis, our primary focus is to estimate the unknown model parameters and study the corresponding classification procedures for the different parametric models. In Chapter 1, we briefly introduce the general problem of classification and estimation of unknown parameters. We provide a comprehensive literature review on classification and estimating the unknown model parameters under equality restriction. In Chapter 2, we discuss some fundamental notations, terminology, and results for the estimation and classification problem that helps to frame the rest of the chapters. In Chapter 3, we revisit the problems of estimation and classification for k(_ 2) normal populations with common mean and ordered variances. In the literature, authors have proposed classification rules based on the Graybill-Deal estimator or its improved version of a common mean under ordered variances. Still, the maximum likelihood estimator (MLE), whose closed-form expression does not exist, is not used for classification purposes. We have proposed the plug-in type restricted version of MLEs of model parameters and utilize these estimators to construct plug-in type classification rules. More importantly, a simulation study has been carried out to numerically compare the performances for all the classification rules, including the existing ones. It has been observed that the classification rules, which are based on the MLE and its restricted version, perform quite satisfactorily (if not the best) compared to other rules. This study is extended to several normal populations with a common mean and ordered variances. To show the practical implication of the proposed methodology, we have considered real-life datasets and obtained the rules’ accuracy. Chapter 4 studies the estimation and classification problem for two inverse Gaussian populations under the equality restriction on model parameters. We have considered the two different situations when the mean parameter is common and the other when the scale like (dispersion ) parameter is common. Under the common mean setup, we proposed restricted-type MLEs and some plug-in type estimators for a common mean parameter. We proposed several plug-in type classification rules using these estimators under order-restricted scale-like parameters. In the sequel, we numerically compared the risk values of all the estimators, which shows that one of the proposed plug-in types restricted MLE outperforms others, including the Graybil-Deal type estimator of the common mean. Our computational results reveal that the proposed classification rules outperform existing rules regarding the probability of correct classification. A similar study has been done for the case when the dispersion parameter is common and mean parameters are different. We proposed the Bayes estimator for the model parameters using the Markov chain Monte Carlo (MCMC) method, which is missing in the literature. The classification rule based on Bayes estimators outperforms the existing rules in terms of the expected probability of correct classification. Chapter 5 considers the estimation and classification problem for two logistic populations under equality restriction on the location or scale parameters. The existence and uniqueness of MLEs of the common location and scale parameters are proved. Further, We constructed several plug-in type classification rules based on the MLEs and the Bayes estimators of model parameters. Moreover, the oracle property for the rules based on the MLEs is established. More importantly, an in-depth simulation study is carried out to compare the performance of proposed model estimators and the corresponding classification rules. Similarly, we considered the estimation and classification problems for two logistic populations with common scales and different mean parameters. In Chapter 6, we studied the classification procedure when the training samples are type-II censored from two exponential populations with a common location and different scale parameters. We have also considered the case when prior information about ordering scale parameters exists. We have developed the classification procedure to classify a censored observation into one of the two exponential populations. Using the original and improved estimators of the common location parameters, we have proposed several classification rules and compared their performances numerically. In Chapter 7, we have generalised these results for the case when the training samples are progressive type-II censored. In this regard, we obtain several estimators of the common location and derive a sufficient condition for improving these estimators, considering with and without order restriction on scale parameters. Further, we have constructed several classification rules to classify a group of progressive type-II censored samples into one of the exponential populations. In both cases, real-life datasets are used to demonstrate the estimation and classification methodologies. Chapter 8 concludes our findings and discusses some of our future research problems
Author Under Sail The Imagination of Jack London, 1893-1902
No full textIn Author Under Sail, Jay Williams offers the first complete literary biography of Jack London as a professional writer engaged in the labor of writing. It examines the authorial imagination in London's work, the use of imagination in both his fiction and nonfiction, and the ways he defined imagination in the creative process in his business dealings with his publishers, editors, and agents. In this first volume of a two-volume biography, Williams traverses the years 1893 to 1902, from London's "Story of a Typhoon" to The People of the Abyss. The Jack London who emerges in the pages of Author Under Sail is a writer whose partnership with publishers, most notably his productive alliance with George Brett of Macmillan, was one of the most formative in American literary history. London pioneered many author models during the heyday of realism and naturalism, blurring the boundaries of these popular genres by focusing on absorption and theatricality and the representation of the seen and unseen. London created an impassioned, sincere, and extremely personal realism unlike that of other American writers of the time. Author Under Sail is a literary tour de force that reveals the full range of London as writer, creative citizen, and entrepreneur at the same time it sheds light on the maverick side of machine-age literature.Intro -- Title Page -- Copyright Page -- Dedication -- Contents -- Acknowledgments -- Introduction -- 1. Spirit Truth -- 2. From Absorption to Theatricality and Back Again -- 3. "I Will Build a New Present" -- 4. Sons as Authors -- 5. Fathers as Publishers -- 6. The Daughter as Author -- 7. Lovers as Authors -- 8. At Sea with the Family -- 9. Yellow News, Yellow Stories -- 10. The Return Home -- Notes -- Bibliography -- Index -- About Jay WilliamsIn Author Under Sail, Jay Williams offers the first complete literary biography of Jack London as a professional writer engaged in the labor of writing. It examines the authorial imagination in London's work, the use of imagination in both his fiction and nonfiction, and the ways he defined imagination in the creative process in his business dealings with his publishers, editors, and agents. In this first volume of a two-volume biography, Williams traverses the years 1893 to 1902, from London's "Story of a Typhoon" to The People of the Abyss. The Jack London who emerges in the pages of Author Under Sail is a writer whose partnership with publishers, most notably his productive alliance with George Brett of Macmillan, was one of the most formative in American literary history. London pioneered many author models during the heyday of realism and naturalism, blurring the boundaries of these popular genres by focusing on absorption and theatricality and the representation of the seen and unseen. London created an impassioned, sincere, and extremely personal realism unlike that of other American writers of the time. Author Under Sail is a literary tour de force that reveals the full range of London as writer, creative citizen, and entrepreneur at the same time it sheds light on the maverick side of machine-age literature.Description based on publisher supplied metadata and other sources.Electronic reproduction. Ann Arbor, Michigan : ProQuest Ebook Central, YYYY. Available via World Wide Web. Access may be limited to ProQuest Ebook Central affiliated libraries
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