An Archive of Taste

A groundbreaking synthesis of food studies, archival theory, and early American literature There is no eating in the archive. This is not only a practical admonition to any would-be researcher but also a methodological challenge, in that there is no eating—or, at least, no food—preserved among the printed records of the early United States. Synthesizing a range of textual artifacts with accounts (both real and imagined) of foods harvested, dishes prepared, and meals consumed, An Archive of Taste reveals how a focus on eating allows us to rethink the nature and significance of aesthetics in early America, as well as of its archive.Lauren F. Klein considers eating and early American aesthetics together, reframing the philosophical work of food and its meaning for the people who prepare, serve, and consume it. She tells the story of how eating emerged as an aesthetic activity over the course of the eighteenth century and how it subsequently transformed into a means of expressing both allegiance and resistance to the dominant Enlightenment worldview. Klein offers richly layered accounts of the enslaved men and women who cooked the meals of the nation’s founders and, in doing so, directly affected the development of our national culture—from Thomas Jefferson’s emancipation agreement with his enslaved chef to Malinda Russell’s Domestic Cookbook, the first African American–authored culinary text.The first book to examine the gustatory origins of aesthetic taste in early American literature, An Archive of Taste shows how thinking about eating can help to tell new stories about the range of people who worked to establish a cultural foundation for the United States

Data Feminism

A new way of thinking about data science and data ethics that is informed by the ideas of intersectional feminism. Today, data science is a form of power. It has been used to expose injustice, improve health outcomes, and topple governments. But it has also been used to discriminate, police, and surveil. This potential for good, on the one hand, and harm, on the other, makes it essential to ask: Data science by whom? Data science for whom? Data science with whose interests in mind? The narratives around big data and data science are overwhelmingly white, male, and techno-heroic. In Data Feminism, Catherine D'Ignazio and Lauren Klein present a new way of thinking about data science and data ethics—one that is informed by intersectional feminist thought. Illustrating data feminism in action, D'Ignazio and Klein show how challenges to the male/female binary can help challenge other hierarchical (and empirically wrong) classification systems. They explain how, for example, an understanding of emotion can expand our ideas about effective data visualization, and how the concept of invisible labor can expose the significant human efforts required by our automated systems. And they show why the data never, ever “speak for themselves.” Data Feminism offers strategies for data scientists seeking to learn how feminism can help them work toward justice, and for feminists who want to focus their efforts on the growing field of data science. But Data Feminism is about much more than gender. It is about power, about who has it and who doesn't, and about how those differentials of power can be challenged and changed

Introduction to Computational Media

Curatorial note from Digital Pedagogy in the Humanities: Yanni Loukissas’s syllabus documents the required introductory course in the Georgia Institute of Technology’s computational media major. The major is designed with a both/and pedagogy of code in mind; students take courses in both computer science and the humanities so as to develop a deep and nuanced understanding of the computer as a medium. The Introduction to Computational Media course represents the students’ first exposure to this synthesis and asks students to explore the history and theory of computation through a series of six focused projects. Each project employs a different programming language and has a different end product—including a data visualization, narrative bot, or procedural poem. Any one of these projects might be incorporated into another course as a capstone element, but the syllabus is most valuable as a whole, because it leads students toward a syncretic understanding of the computer as an expressive form

"Literary Data: Some Approaches"

Curatorial note from Digital Pedagogy in the Humanities: Andrew Goldstone’s syllabus for a graduate course on literary data is explicit about its dual aims: “to engage with the history and current practice of literary data analysis, and to introduce the foundational skills of literary data analysis in the R programming language.” Through readings on the history and theory of data, coupled with programming exercises designed to introduce students to basic computational operations and constructs, Goldstone provides a model for how students might apply computational methods to humanistic research questions with historical, theoretical, and technical considerations in mind. Its focus on literary data functions as a valuable illustration of how a disciplinary focus can lead to greater depth of understanding; and its hybrid class structure might present a model for how to teach programming in the context of a humanities seminar

Riveter: Measuring Power and Social Dynamics Between Entities

Riveter provides a complete easy-to-use pipeline for analyzing verb connotations associated with entities in text corpora. We prepopulate the package with connotation frames of sentiment, power, and agency, which have demonstrated usefulness for capturing social phenomena, such as gender bias, in a broad range of corpora. For decades, lexical frameworks have been foundational tools in computational social science, digital humanities, and natural language processing, facilitating multifaceted analysis of text corpora. But working with verb-centric lexica specifically requires natural language processing skills, reducing their accessibility to other researchers. By organizing the language processing pipeline, providing complete lexicon scores and visualizations for all entities in a corpus, and providing functionality for users to target specific research questions, Riveter greatly improves the accessibility of verb lexica and can facilitate a broad range of future research

"Data-Based Project and Analysis"

Curatorial note from Digital Pedagogy in the Humanities: Like Melanie Feinberg’s course, this course usefully engages with information as authored by explicitly asking students to first understand and then to intervene in existing systems or processes in order to create an argument. However, while Feinberg’s course focuses on a specific aspect of information systems (metadata) and a specific theoretical concept (residuality), Klein’s course asks students to discover and articulate their own interests, which might range from forms of visualization to formats of data and from epistemological issues to the social or political. Whether producing a proof-of-concept or proposal, students must think about how their critical arguments intersect with real-world constraints. Projects such as Nicholas Felton’s personal annual reports are especially valuable objects to consider, as they represent uses of data that are personal and emerging, open to a variety of arguments and interventions, as well as concrete and specific, realized in specific technologies that are available to students. One of the interesting tensions running through the assignments collected here is between information as crafted by individuals and information as structured by distributed technical systems and tools, and one of the key pedagogical uses of Klein’s project is in having students experience and negotiate this tension

Sex differences in cancer mechanisms

We now know that cancer is many different diseases, with great variation even within a single histological subtype. With the current emphasis on developing personalized approaches to cancer treatment, it is astonishing that we have not yet systematically incorporated the biology of sex differences into our paradigms for laboratory and clinical cancer research. While some sex differences in cancer arise through the actions of circulating sex hormones, other sex differences are independent of estrogen, testosterone, or progesterone levels. Instead, these differences are the result of sexual differentiation, a process that involves genetic and epigenetic mechanisms, in addition to acute sex hormone actions. Sexual differentiation begins with fertilization and continues beyond menopause. It affects virtually every body system, resulting in marked sex differences in such areas as growth, lifespan, metabolism, and immunity, all of which can impact on cancer progression, treatment response, and survival. These organismal level differences have correlates at the cellular level, and thus, males and females can fundamentally differ in their protections and vulnerabilities to cancer, from cellular transformation through all stages of progression, spread, and response to treatment. Our goal in this review is to cover some of the robust sex differences that exist in core cancer pathways and to make the case for inclusion of sex as a biological variable in all laboratory and clinical cancer research. We finish with a discussion of lab- and clinic-based experimental design that should be used when testing whether sex matters and the appropriate statistical models to apply in data analysis for rigorous evaluations of potential sex effects. It is our goal to facilitate the evaluation of sex differences in cancer in order to improve outcomes for all patients

The Prognostic and Predictive Value of Melanoma-related MicroRNAs Using Tissue and Serum: A MicroRNA Expression Analysis

The overall 5-year survival for melanoma is 91%. However, if distant metastasis occurs (stage IV), cure rates are = 82%) when = 4 miRNAs were expressed. Moreover, the 'MELmiR-7' panel characterised overall survival of melanoma patients better than both serum LDH and S100B (delta log likelihood=11, p < 0.001). This panel was found to be superior to currently used serological markers for melanoma progression, recurrence, and survival; and would be ideally suited to monitor tumour progression in patients diagnosed with early metastatic disease (stages IIIa-c/IV M1a-b) to detect relapse following surgical or adjuvant treatment. (C) 2015 The Authors. Published by Elsevier B. V