Relevant bibliographies by topics / Mixed Authorship

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Academic literature on the topic 'Mixed Authorship'

Author: Grafiati
Published: 30 June 2021
Last updated: 15 February 2022

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Journal articles on the topic "Mixed Authorship"

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Hoover, David L. "The Tutor's Story: A Case Study of Mixed Authorship." English Studies 93, no. 3 (May 2012): 324–39. http://dx.doi.org/10.1080/0013838x.2012.668791.

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van Doren, Sophie, Margarita Brida, Michael A. Gatzoulis, Aleksander Kempny, Sonya V. Babu-Narayan, Ulrike M. M. Bauer, Helmut Baumgartner, and Gerhard Paul Diller. "Sex differences in publication volume and quality in congenital heart disease: are women disadvantaged?" Open Heart 6, no. 1 (April 2019): e000882. http://dx.doi.org/10.1136/openhrt-2018-000882.

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BackgroundWomen are underrepresented in leading medical positions and academia. The gender-gap in authorship of congenital heart disease (CHD) publications remains unknown. As determinants of gender equity in this field are poorly characterised, we aimed to quantify and characterise publications in CHD and to assess factors associated with female representation in research.Methods and resultsWe identified 35 118 CHD publications between 2006 and 2015 for which author gender could be ascertained. Overall, 25.0% of all authors were female. Women accounted for 30.2% and 20.8% of all first and senior authorship positions with great geographic heterogeneity. While globally female first and senior authorship increased by 0.8% and 0.6%/year, some geographic regions showed no improvement in gender representation. Significant predictors of female first authorship on logistic regression analysis were country gross domestic product, human development index, gender inequality index and a female senior author (p<0.0001 for all). Publications with a female lead author tended to be published in journals with a higher impact factor (IF) and to attract more citations compared with those with a male author. Mixed gender authorship was associated with higher IF and number of citations. Women were less disadvantaged when the analysis was confined to original research.ConclusionsWhile modest improvement in female authorship over time was noted, women remain underrepresented in contemporary academic CHD. Manuscripts with mixed gender authorship had higher IF and more citations. The main predictor of female first authorship was a female senior author. These data should inform policy recommendations regarding gender parity.
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Bourlon, Maria Teresa, Brenda Jimenez, Charbel Fadi Matar, Emilie M. Gunn, Ophira M. Ginsburg, Gilberto Lopes, and Eva Segelov. "Global oncology authorship and access patterns." Journal of Clinical Oncology 38, no. 15_suppl (May 20, 2020): 7061. http://dx.doi.org/10.1200/jco.2020.38.15_suppl.7061.

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7061 Background: Global Oncology is a movement to improve equitable access to cancer control and care, recognizing challenges due to economic and social factors between high, middle, and low-income countries (HIC, MIC, LIC). Access to local, regional, and global cancer data and analysis is a major driver for building a global oncology community. The JCO Global Oncology (JCO GO) online open access journal was established in 2015 with the mission to be the voice of research relevant to populations with limited resources. To assess its goals of encouraging global interaction and increasing MIC and LIC engagement, we analyzed authorship and accessing data. Methods: Logged views of articles published in 2018 were identified by DOI, using Google Analytics during the period 01/01/2018 to 06/30/2019. The country of origin of all authors and the location of downloads were classified according to the 218 economies listed in The World Bank Data (WBC) of 2019. Results: 132 articles were published in JCO GO in 2018 with 88152 views, from which the accessing nation was identified for 99%. Views originated from 180 countries: 35% HIC, 51% MIC, and 14% LIC. The most common accessing countries were: USA (37%), India (14%), United Kingdom (3%), Brazil (3%), and Ethiopia (3%). Corresponding authors came from 34 nations: 60% HIC, 32% MIC, and 8% LIC. The most common economies involved in any authorship were: USA (47%), India (10%), Brazil (5%), Mexico (4%), and Nigeria (3%). Reader origin did not differ according to corresponding author WBC. Article authorship was exclusively from one economic category in 49%: 23% HIC 16% MIC, 2% LIC. For 59% of articles, authorship came from mixed economies: 42% HIC + MIC, 11% HIC + LIC, 0% MIC + LIC, 6% HIC + MIC + LIC. Conclusions: JCO GO ’s reach extends to over 80% of the world´s economies. The majority of articles have authors from mixed WBC countries. Areas identified to address are: low level of LIC corresponding authorship; few papers from authors across all economies; no papers from only LMICs authors; low percentage of views by LIC. This information provides focus for global oncology authorities to target interventions to reduce the academic segregation of LICs, such as global oncology funding opportunities, mentorship and policies to encourage interactions and develop MIC and LIC leaders.
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Agun, Hayri Volkan, and Ozgur Yilmazel. "Bucketed common vector scaling for authorship attribution in heterogeneous web collections: A scaling approach for authorship attribution." Journal of Information Science 46, no. 5 (July 11, 2019): 683–95. http://dx.doi.org/10.1177/0165551519863350.

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Domain, genre and topic influences on author style adversely affect the performance of authorship attribution (AA) in multi-genre and multi-domain data sets. Although recent approaches to AA tasks focus on suggesting new feature sets and sampling techniques to improve the robustness of a classification system, they do not incorporate domain-specific properties to reduce the negative impact of irrelevant features on AA. This study presents a novel scaling approach, namely, bucketed common vector scaling, to efficiently reduce negative domain influence without reducing the dimensionality of existing features; therefore, this approach is easily transferable and applicable in a classification system. Classification performances on English-language competition data sets consisting of emails and articles and Turkish-language web documents consisting of blogs, articles and tweets indicate that our approach is very competitive to top-performing approaches in English competition data sets and is significantly improving the top classification performance in mixed-domain experiments on blogs, articles and tweets.
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Trujeque Moreno, Eva Estefania, Fátima Encinas Prudencio, and Maria Thomas-Ruzic. "Exploring Authorship Development Among Mexican EFL Teacher-Researchers." PROFILE Issues in Teachers' Professional Development 17, no. 2 (July 1, 2015): 43–62. http://dx.doi.org/10.15446/profile.v17n2.44441.

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<p>This article presents a multi-theoretical model to address processes of <em>authorship development</em> in the English as a foreign language teaching profession. Working within a sociocultural perspective of second-language teacher education, the authors examined six experienced nonnative English-speaking teacher-researchers. Perceptions of their key moments in the profession were analyzed using a mixed-method approach that combined document analysis with personal narratives. The findings indicated that both <em>authoring</em> (products and activities in their profession) and <em>self-authorship</em> (transformational processes throughout their careers) contributed to constructing these English as a foreign language professionals as scholars.</p><p>En este artículo se presenta un modelo multiteórico y multinivel para identificar el proceso en el que los autores se desarrollan en el área de la enseñanza del inglés como lengua extranjera, proceso identificado como <em>desarrollo de la autoría</em>. Este modelo se desarrolló bajo una perspectiva sociocultural de la formación de profesores que presenta una muestra de las percepciones de seis profesores investigadores mexicanos en el área de inglés como lengua extranjera. Se utilizó un método mixto que combinó el análisis de documentos con narrativas personales. Los resultados de esta investigación indicaron la presencia de momentos significativos de su <em>autoría</em> (productos y actividades) y su <em>auto-autoría</em> (procesos de transformación), que contribuyeron a la construcción del desarrollo de la autoría de estos profesores-investigadores.</p>
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Haslam, Nick, and Simon Laham. "Early-career scientific achievement and patterns of authorship: the mixed blessings of publication leadership and collaboration." Research Evaluation 18, no. 5 (December 1, 2009): 405–10. http://dx.doi.org/10.3152/095820209x481075.

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Rebora, Simone, J. Berenike Herrmann, Gerhard Lauer, and Massimo Salgaro. "Robert Musil, a war journal, and stylometry: Tackling the issue of short texts in authorship attribution." Digital Scholarship in the Humanities 34, no. 3 (October 20, 2018): 582–605. http://dx.doi.org/10.1093/llc/fqy055.

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Abstract During World War I (WWI), between 1916 and 1917, Robert Musil was the chief editor of the Tiroler Soldaten-Zeitung in Bozen. This activity probably also involved authorship of articles and has posed a philological problem to scholars, who have not been able to attribute with certainty a range of relatively short texts to Musil. With this article, we present a new approach that combines philological research with stylometric methods. Exploration of WWI archives and digitization of historical documents were paired with application of authorship attribution techniques, following extensive evaluation. To build the training set, we adapted the ‘impostors method’ by grouping three ‘distractor authors’ (similar to Musil in terms of style) and three actual candidates for authorship. In the test set, we developed two designs for tackling the issue of text length: a combinatory design, where longer chunks were composed by the juxtaposition of short texts; a simplified design, where the texts for attribution were merged with already attributed texts. Results of our experiment suggest that Musil attribution may be disproved with a high level of confidence for ten texts that were more probably written by a less well-known author, Albert Ritter. We carried out a keyness analysis on the specific words preferred or avoided by the two authors, which not only corroborated the results of the quantitative analysis but also findings from Musil philology. Our study showcases the potentialities of using mixed methods in stylometry.
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Abuhamad, Mohammed, Tamer Abuhmed, David Mohaisen, and Daehun Nyang. "Large-scale and Robust Code Authorship Identification with Deep Feature Learning." ACM Transactions on Privacy and Security 24, no. 4 (November 30, 2021): 1–35. http://dx.doi.org/10.1145/3461666.

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Successful software authorship de-anonymization has both software forensics applications and privacy implications. However, the process requires an efficient extraction of authorship attributes. The extraction of such attributes is very challenging, due to various software code formats from executable binaries with different toolchain provenance to source code with different programming languages. Moreover, the quality of attributes is bounded by the availability of software samples to a certain number of samples per author and a specific size for software samples. To this end, this work proposes a deep Learning-based approach for software authorship attribution, that facilitates large-scale, format-independent, language-oblivious, and obfuscation-resilient software authorship identification. This proposed approach incorporates the process of learning deep authorship attribution using a recurrent neural network, and ensemble random forest classifier for scalability to de-anonymize programmers. Comprehensive experiments are conducted to evaluate the proposed approach over the entire Google Code Jam (GCJ) dataset across all years (from 2008 to 2016) and over real-world code samples from 1,987 public repositories on GitHub. The results of our work show high accuracy despite requiring a smaller number of samples per author. Experimenting with source-code, our approach allows us to identify 8,903 GCJ authors, the largest-scale dataset used by far, with an accuracy of 92.3%. Using the real-world dataset, we achieved an identification accuracy of 94.38% for 745 C programmers on GitHub. Moreover, the proposed approach is resilient to language-specifics, and thus it can identify authors of four programming languages (e.g., C, C++, Java, and Python), and authors writing in mixed languages (e.g., Java/C++, Python/C++). Finally, our system is resistant to sophisticated obfuscation (e.g., using C Tigress) with an accuracy of 93.42% for a set of 120 authors. Experimenting with executable binaries, our approach achieves 95.74% for identifying 1,500 programmers of software binaries. Similar results were obtained when software binaries are generated with different compilation options, optimization levels, and removing of symbol information. Moreover, our approach achieves 93.86% for identifying 1,500 programmers of obfuscated binaries using all features adopted in Obfuscator-LLVM tool.
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Gorman, Robert. "Author identification of short texts using dependency treebanks without vocabulary." Digital Scholarship in the Humanities 35, no. 4 (October 24, 2019): 812–25. http://dx.doi.org/10.1093/llc/fqz070.

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Abstract How to classify short texts effectively remains an important question in computational stylometry. This study presents the results of an experiment involving authorship attribution of ancient Greek texts. These texts were chosen to explore the effectiveness of digital methods as a supplement to the author’s work on text classification based on traditional stylometry. Here it is crucial to avoid confounding effects of shared topic, etc. Therefore, this study attempts to identify authorship using only morpho-syntactic data without regard to specific vocabulary items. The data are taken from the dependency annotations published in the Ancient Greek and Latin Dependency Treebank. The independent variables for classification are combinations generated from the dependency label and the morphology of each word in the corpus and its dependency parent. To avoid the effects of the combinatorial explosion, only the most frequent combinations are retained as input features. The authorship classification (with thirteen classes) is done with standard algorithms—logistic regression and support vector classification. During classification, the corpus is partitioned into increasingly smaller ‘texts’. To explore and control for the possible confounding effects of, e.g. different genre and annotator, three corpora were tested: a mixed corpus of several genres of both prose and verse, a corpus of prose including oratory, history, and essay, and a corpus restricted to narrative history. Results are surprisingly good as compared to those previously published. Accuracy for fifty-word inputs is 84.2–89.6%. Thus, this approach may prove an important addition to the prevailing methods for small text classification.
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Wheland, Ethel R., Kevin A. Butler, Helen Qammar, Karyn Bobkoff Katz, and Rose Harris. "What Are They Thinking? Students' Affective Reasoning and Attitudes about Course Withdrawal." NACADA Journal 32, no. 2 (September 1, 2012): 17–25. http://dx.doi.org/10.12930/0271-9517-32.2.17.

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In this mixed-methods study we identify situations that impact students' decisions to withdraw from a course and examine their affective reasoning and attitudes toward course withdrawal. Exploring students' decision-making processes through the lens of self-authorship, we show that students frequently seek information from people with whom they have a personal rather than academic relationship, make decisions with little awareness of academic consequences, and often experience a feeling of dissonance when withdrawing from courses, even describing themselves as “quitters.” Our results lead to recommendations that can assist academic advisors in developing meaningful interventions that advance students' decision-making abilities and intellectual development.
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Dissertations / Theses on the topic "Mixed Authorship"

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Rörlien, Viktor, and Nils Brundin. "Mixed-initiative Puzzle Design Tool for Everyone Must Die." Thesis, Malmö universitet, Institutionen för datavetenskap och medieteknik (DVMT), 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:mau:diva-43258.

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The application of PCG to generate puzzles offers great value since their replayability is severely limited, requiring any game that employs them to produce many different puzzles. In this paper we propose a modified version of the progressive content generation approach to function as a mixed-initiative system, to create puzzles for the novel partially physics-based game \textit{Everyone Must Die}. Thus exploring the adaptability and usefulness of the progressive content generation approach for a unique type of puzzle game. Further the mixed-initiative system is explored in relation to how effectively it can generate puzzles with a specified difficulty, an issue many papers exploring puzzle generation neglect. This is explored by implementing and incorporating a PCG system by extending an existing puzzle editor featured in the game. The analysis is conducted with the help of a user study on the developers of the game by testing qualitative experiences with the system. The promising results are then discussed and concluded with suggestions for future work and improvements to the described system and its used approach.
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Books on the topic "Mixed Authorship"

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Amos, Diane. Mixed blessings. Waterville, Me: Five Star, 2004.

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Wakley, Dina. Art journal courage: Fearless mixed media techniques for journaling bravely. Cincinnati OH: North Light, 2014.

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Adventures in mixed media: Collage, stitch, fuse, and journal your way to a more creative life. New York: Potter Craft, 2011.

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McDonald, Quinn. Raw art journaling. Cincinnati, Ohio: North Light Books, 2011.

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Palazzari, Ronda. Art of layers: Simple techniques, inventive scrapbook pages, imaginative papercrafts. Cincinnati, Ohio: North Light Books, 2012.

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Erdrich, Louise. Conversations with Louise Erdrich and Michael Dorris. Jackson: University Press of Mississippi, 1994.

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McDonald, Quinn. Inner Hero Creative Art Journal: Mixed Media Messages to Silence Your Inner Critic. F&W Media, Incorporated, 2014.

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Taylor, Terry. The Artful Storybook: Mixed-Media Artists Create Handmade Tales. Lark Books, 2008.

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Rutell, Megan. Beyond Bullets: Creative Journaling Ideas to Customize Your Personal Productivity System. Ulysses Press, 2017.

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Javier-Cerulli, Gabrielle. Art Journal Your Archetypes: Mixed-Media Techniques for Finding Yourself. F&W Media, Incorporated, 2016.

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