Performing 'meat': Meat replacement as drag

I propose that meat replacement is to meat, as drag is to gender. Meat replacement has the potential to shake concepts of meat, like drag does for gender. Meat replacements not only mimic meat but disclose how meat itself is performed in carnivorous culture -and show that it may be performed otherwise. My approach is inspired by the show RuPaul’s Drag Race. The argument builds on an imitation of Judith Butler’s work on gender performativity, performed by replacing ‘drag/ gender/ sex/ heterosexism’ terms and relations in Butler’s text with ‘meat replacement/ meat/ species/ carnism’ ones

Meat we don't greet: How sausages can save pigs or how effacing livestock makes room for emancipation

I propose that the intensification of meat production ironically makes meat concepts available to be populated by plants. I argue that what I call “technologies of effacement” facilitate the intensification of animal farming and slaughter by blocking face-to-face encounters between animals and people (Levinas 1969; Efstathiou 2018, 2019). My previous ethnographic work on animal research identifies technologies of effacement as including (a) architectures and the built environment, (b) entry and exit rules, (c) special garments, (d) naming and labeling procedures, and (e) protocols for handling animals (Efstathiou 2018, 2019). Building on ethnographic research by Dawn Coppin (2003) and Nöellie Vialles (1994), in the United States and France respectively, I propose that (a) Concentrated Animal Feeding Operation (CAFO) buildings, gestation, and farrowing crates; (b) rules for entering and exiting the slaughterhouse; (c) white slaughterhouse garments; (d) unique identification systems; and (e) “trapping” animals before stunning can all operate as technologies of effacement. Though developed to serve other manifest aims, like hygiene, expediency, or safety, these technologies operate to sustain routine, inviting one to look at animals as tokens of a known type while blocking encounters between humans and animals (and also among animals) as radically different, morally significant Others (Efstathiou 2018, 2019)

Getting our hands dirty with technology: The role of the performing arts in technological development

This paper argues for the involvement of the performing and applied arts in technological development in the field of Responsible Research and Innovation (RRI). It discusses the challenges and the benefits for the arts, and presents existing methods in the field of RRI. It then describes two practical case studies called gameformances carried out by the authors

Scientific knowledge in the age of computation: explicated, computable and manageable?

With increasing publication and data production, scientific knowledge presents not simply an achievement but also a challenge. Scientific publications and data are increasingly treated as resources that need to be digitally ‘managed.’ This gives rise to scientific Knowledge Management (KM):second-order scientific work aiming to systematically collect, take care of and mobilise first-hand disciplinary knowledge and data in order to provide new first-order scientific knowledge. We follow the work of Leonelli (2014, 2016), Efstathiou (2012, 2016) and Hislop (2013) in our analysis of the use of KM in semantic systems biology. Through an empirical philosophical account of KM-enabled biological research, we argue that KM helps produce new first-order biological knowledge that did not exist before, and which could not have been produced by traditional means. KM work is enabled by conceiving of ‘knowledge’ as an object for computational science: as explicated in the text of biological articles and computable via appropriate data and metadata. However, these founded knowledge concepts enabling computational KM risk focusing on only computationally tractable data as knowledge, underestimating practice-based knowing and its significance in ensuring the validity of ‘manageable’ knowledge as knowledge.; Con el aumento de la publicación y la producción de datos, el conocimiento científico no solo es reconocido como un logro, sino también como un desafío. Las publicaciones y los datos científicos se tratan cada vez más como recursos que deben ser ‘gestionados’ digitalmente. Esto da lugar a la Gestión del Conocimiento científico (Knowledge Management (KM)): labor científica de segundo orden destinada a recopilar, cuidar y movilizar de forma directa el conocimiento disciplinario de primera mano y los datos para proporcionar nuevos conocimientos científicos de primer orden. Seguimos el trabajo de Leonelli (2014, 2016), Efstathiou (2012, 2016) y Hislop (2013) en nuestro análisis del uso de la KM en la biología de sistemas semánticos. A través de una descripción filosófica empírica de la investigación biológica habilitada para KM, argumentamos que KM ayuda a producir un nuevo conocimiento biológico de primer orden que no existía antes y que no podría haber sido producido por medios tradicionales. El trabajo de KM está facultado para concebir el “conocimiento” como un objeto para la ciencia computacional: como algo explicitado en el texto de artículos biológicos y como computable a través de datos y metadatos apropiados. Sin embargo, los conceptos fundados permiten el riesgo computacional de KM de centrarse solo en los datos que se pueden tratar de manera computacional como conocimiento, subestimando el conocimiento basado en la práctica y su importancia para garantizar la validez del conocimiento “manejable” como conocimiento

Scientific knowledge in the age of computation

With increasing publication and data production, scientific knowledge presents not simply an achievement but also a challenge. Scientific publications and data are increasingly treated as resources that need to be digitally ‘managed.’ This gives rise to scientific Knowledge Management : second-order scientific work aiming to systematically collect, take care of and mobilise first-hand disciplinary knowledge and data in order to provide new first-order scientific knowledge. We follow the work of Leonelli, Efstathiou and Hislop in our analysis of the use of KM in semantic systems biology. Through an empirical philosophical account of KM-enabled biological research, we argue that KM helps produce new first-order biological knowledge that did not exist before, and which could not have been produced by traditional means. KM work is enabled by conceiving of ‘knowledge’ as an object for computational science: as explicated in the text of biological articles and computable via appropriate data and metadata. However, these founded knowledge concepts enabling computational KM risk focusing on only computationally tractable data as knowledge, underestimating practice-based knowing and its significance in ensuring the validity of ‘manageable’ knowledge as knowledge

Scientific knowledge in the age of computation: Explicated, computable and manageable?

We have two theses about scientific knowledge in the age of computation. Our general claim is that scientific Knowledge Management practices emerge as second-order practices whose aim is to systematically collect, take care of and mobilise first-hand disciplinary knowledge and data. Our specific thesis is that knowledge management practices are transforming biological research in at least three ways. We argue that scientific Knowledge Management a. operates with founded concepts of biological knowledge as explicated and computable, b. enables new outputs and ways of knowing within biology, and c. risks enforcing objectivist epistemologies of knowledge as some one objective thing