Domestic Initiatives: Home and Hearth
Back to the Future: Suburban Chicken-keeping as a Revived Environmental Practice
Paper Presentation in a Themed Session Ruth Barcan
The last ten years have witnessed the resurgence of small-scale domestic chicken-keeping in many cities around the world as part of a broader rise in urban agriculture. This paper draws on qualitative interviews with domestic chicken-keepers carried out in Sydney in 2014-17 to explore the possibility that this revival might signal something more than just “a pervasive nostalgia for earlier modes of living” (Hamilton 2014: 124). Springboarding off the concept of “practice memory” elaborated by Cecily Maller and Yolande Strengers (2015), it canvasses eight aspects of suburban chicken-keeping that arose from the interviews, using these themes as a means both of understanding chicken-keeping more richly and as the basis for gesturing towards a possible theoretical understanding of elements of social practice that might help make them revivable and durable.
Speculative Gastronomy: Artificial Intelligence in the Kitchen and the Flavor of Data
Paper Presentation in a Themed Session Jeannine Shinoda
My recent research into the confluence of food and technology via neural networks is inspired by these questions and the increasing intimate relationships we have with technology in our daily lives. As an artist, I am always interested in how we find inspiration and foster creativity. I wondered if the neural network would function like the "I Ching" did for John Cage? Or if perhaps like Marinetti’s "Futurist Cookbook", could using the absurd be seen as a proposition for social and political change? I welcomed the aleatory nature of this AI collaboration with the expectation that it would lead to new and unknown territory. What interests me most about this collaborative work with artificial intelligence, is the idea that this conceptual inquiry can become a sensorial experience. When selecting the recipe data to teach my neural network, I think about intention and expectation as flavors. Would more control over what I feed the neural network lead to more or less delicious results? What does bias taste like?
Thermodynamic Analysis of Skillet Materials to Maximize Sustainability and Home-cooking Habits
Paper Presentation in a Themed Session Carla Ramsdell, Jeff Ramsdell
Research indicates that home cooking habits have diminished in the United States. Any strategy charting a path to a sustainable food future requires that individuals are knowledgeable and confident with simple cooking techniques. This allows individuals to take control of food sourcing, maximizing biodiversity and minimizing transportation, storage, packaging and disposal. Additionally, families and communities are strengthened when these skills are developed and used regularly. One of the simplest and most energy efficient ways to cook is on a stove-top with a skillet, but the material choices of skillets available to consumers make this decision difficult. This research focuses on the thermodynamics and sustainability of skillet materials. From an expensive solid copper to an affordable traditional solid cast iron skillet, the material properties, including conductivity, specific heat and emissivity make a difference in the sustainability, success and enjoyment of these basic tools. Using infrared thermography and other diagnostic techniques, these thermal properties are compared. These results are combined with other non-thermal considerations such as cost, longevity and ease of use to develop guidelines for successful skillet selection. These results can be applied to commercial and residential kitchens to encourage the selection of skillets that will result in the optimal final results with minimal environmental impact. Using the results of this research, outreach efforts are under way to encourage resurgence in traditional home cooking. This is intended to revitalize the cultural importance of cooking and the family and community resiliency that evolves from the re-establishing these critical skills.
