1,721,000 research outputs found
Keynote: Lauren Klein “Data Feminism and Digital Scholarship“
No full textAn opening Keynote presentation by Lauren Klein introduced by Evan Peck. Lauren Klein is Winship Distinguished Research Professor and Associate Professor in the departments of English and Quantitative Theory & Methods at Emory University, where she also directs the Digital Humanities Lab. Before moving to Emory, she taught in the School of Literature, Media, and Communication at Georgia Tech. Klein works at the intersection of digital humanities, data science, and early American literature, with a focus on issues of gender and race. She is the author of An Archive of Taste: Race and Eating in the Early United States (University of Minnesota Press, 2020) and, with Catherine D’Ignazio, Data Feminism (MIT Press, 2020). With Matthew K. Gold, she edits Debates in the Digital Humanities, a hybrid print-digital publication stream that explores debates in the field as they emerge. Her work has appeared in leading humanities journals including PMLA, American Literature, and American Quarterly; and at technical conferences including NACCL, EMNLP, and IEEE VIS. Her research has been supported by grants from the NEH and the Mellon Foundation
Feminist Data Practices: Conversations with Catherine D’Ignazio, Lauren Klein, and Maya Livio
Full text linkMany of the papers and more-than-textual proposals submitted for this special issue included machine vision technologies and other data- and AI- mediated practices. To provide a critical perspective on data-driven (design) research, we decided to explore the emerging field of data feminism through online interviews with three scholars and practitioners who apply intersectional feminist theory and practice to the realm of data-driven work: Catherine D’Ignazio, Lauren Klein, and Maya Livio.
With Catherine D’Ignazio and Lauren Klein, authors of the book Data Feminism (2020), we touch upon the idea of data feminism as a way of thinking about (and acting upon) data and data science, informed by intersectional feminist thinking. From examining and challenging power structures in the data collection process to embracing pluralism beyond binaries and hierarchies, they outline a research program that clarifies why and how data science needs intersectional feminism. With them, we discuss how art and (speculative) design practices can make power imbalances visible. We also discuss the limitations and advantages of participatory data practices and the responsibility that lies upon data collectors when making visible an issue through data can cause more harm than good to those affected by it. We discuss how sometimes one needs to reject ground rules of data visualization to pursue higher political goals beyond simple analytical needs. We conclude this conversation with an invitation to embrace complexity when applying feminist principles to data work, while being aware of our personal standpoints and limitations.
With Maya Livio, researcher and curator at the University of Colorado Boulder, we discuss how an intersectional feminist approach to data science can also consider more-than-human beings. We talk about her work on animal interfaces, in which she explores how the contact points between the human and more-than-human worlds are permeated with technology. Maya Livio then takes us through her experiences in feminist labs, explaining how the first step of incorporating a feminist practice is to take stock of and codify the work being done, cultivating attention towards (often unspoken or unwritten) methods and practices. We also discuss how she and her colleagues developed a framework for operationalizing the art of noticing as a methodological contribution. Finally, we touch upon her personal research approach, characterized by a mix of experimental multidisciplinary practices, moving from writing to curating to design and art-making.Muchos de los artículos y las propuestas más-que-textuales que se presentaron para este número especial incluían tecnologías de visión artificial y otras prácticas mediadas por datos e inteligencia artificial (IA). Con el propósito de ofrecer una perspectiva crítica sobre la investigación (de diseño) basada en datos, decidimos explorar el campo emergente del feminismo de datos a través de entrevistas en línea con tres académicas y profesionales que aplican la teoría y la práctica feminista interseccional al trabajo basado en datos: Catherine DʼIgnazio, Lauren Klein y Maya Livio.
Con Catherine DʼIgnazio y Lauren Klein, autoras del libro Data Feminism (2020), abordamos la idea del feminismo de datos como una manera de pensar (y actuar) sobre los datos y la ciencia de datos, la que se caracteriza por estar informada por el pensamiento feminista interseccional. Desde la necesidad de examinar y desafiar las estructuras de poder en el proceso de recopilación de datos hasta la necesidad de abrazar el pluralismo más allá del pensamiento binario y las jerarquías, DʼIgnazio y Klein esbozan un programa de investigación que aclara por qué y cómo la ciencia de datos necesita el feminismo interseccional. Con ellas discutimos cómo el arte y las prácticas de diseño (especulativo) pueden hacer visibles los desequilibrios de poder. También discutimos las limitaciones y ventajas de las prácticas participativas de datos y la responsabilidad que recae sobre quienes recolectan datos cuando usar datos para hacer visible un tema puede causar más daño que beneficios a los afectados. Discutimos cómo, a veces, es necesario rechazar las reglas básicas de la visualización de datos para alcanzar objetivos políticos más elevados que las simples necesidades analíticas. Concluimos esta conversación con una invitación a abrazar la complejidad al momento de aplicar los principios feministas al trabajo con datos, siendo conscientes de nuestros puntos de vista y limitaciones personales.
Con Maya Livio, investigadora y curadora de la Universidad de Colorado Boulder, hablamos de la manera en que un enfoque feminista interseccional de la ciencia de datos puede tener en cuenta también a los seres más-que-humanos. Conversamos sobre su trabajo con interfaces animales, en el que explora cómo los puntos de contacto entre los mundos humano y más-que-humano están impregnados de tecnología. A continuación, Maya Livio nos lleva a sus experiencias en los laboratorios feministas, para explicarnos que el primer paso para incorporar una práctica feminista es hacer un balance o inventario y codificar el trabajo que se está realizando, cultivando asimismo la atención hacia los métodos y las prácticas (a menudo tácitos o no escritos). También discutimos cómo ella y sus colegas desarrollaron un marco para operacionalizar el “arte de notar” como una contribución metodológica. Por último, nos referimos a su enfoque personal de investigación, caracterizado por una mezcla de prácticas multidisciplinares experimentales, que van desde la escritura hasta la curatoría, pasando por el diseño y la creación artística
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
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
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
- …
