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- Convenors:
-
Victor Secco
(Ca' Foscari University of Venice)
Valentina Marcheselli (Cà Foscari - University of Venice)
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- Format:
- Traditional Open Panel
Short Abstract:
This panel focuses on sampling practices as a central but often overlooked stage of scientific research. We aim to explore the intersections between the generation of abstractable data, and the situated and embodied dimension of science in-the-making.
Long Abstract:
Sampling practices are central to data generation across various scientific disciplines. It is a pivotal step that underpins the possibility and production of data, influencing how data is generated, compared and extrapolated. While there has been an increased focus around the digitalised and refined aspects of data, the practices, logics, and technologies of sampling have received less attention. Can a focus on sampling bring into view the transformations of data and matter that are relevant to understand the contemporary making and doings of science?
This panel aims to address this gap by bringing together a diverse range of approaches to sampling practices within STS. We invite contributions that delve into both ethnographic and theoretical perspectives on sampling, offering the opportunity to explore themes such as:
- how sampling practices shape understandings of ecosystems and environments;
- local sampling and planetary thinking;
- sampling, extractivist economies and natural resources exploitation;
- the complexities of medical sample collection, from the intricacies of clinical trials to the ethical considerations surrounding human specimen collection;
- the porous boundaries of the lab;
- sampling as embodied practice;
- the mutual shaping of sensory experience, knowledge making practices and technology in use;
- interdisciplinary collaborations built around fieldwork and sample collection processes;
- sample collection and citizen science;
- the role of the STS researcher in sampling practices;
- metaphors, narratives and discourses of sampling practices;
- ethical questions raised by practices of sample collection and the future uses of data.
Accepted papers:
Session 1Alastair Mackie Anne Dippel (Friedrich-Schiller-Universität Jena)
Long abstract:
Whereas sampling usually refers to the extraction of data, in music, sampling may also include the transformation of this data into something new. This sample-based synthesis, also known as sample mangling, is then used to inspire or form part of new compositions, giving the original samples new meaning. Although recording audio has long been important in ethnographic fieldwork, it is usually anathema to change samples in any way. In this paper we will challenge this taboo and explore the potential of sample-mangling techniques in ethnographic data creation and analysis.
Merging creative ethnology (Kockel 2011) with ludic anthropology (Dippel 2022) and sonic ethnography (Gershon, 2018; Mackie 2024) our aim is to play with sound in a creative way in close co-laboration with audio synthesis techniques. Sample-based synthesis presents us with various tools to transform audio samples, such as modulation, subtraction and addition, and the infusion of probability and chaos. As these creative techniques already rely heavily on scientific approaches, can we also borrow from them and add them to our ethnographich toolbox? And by exploring samples from this creative perspective, can we uncover new sides to them which otherwise we may have missed?
By mangling samples gathered in the Large Hadron Collider and the Anti-Matter Lab at CERN, and in cross-border trains in Europe, we will ask what kind of new harmonies and rhythms we can detect in our data and whether these may lead us to unforeseen insights, thereby exploring the epistemic role creative sampling may play in our research.
Alicja Ostrowska (Chalmers University of Technology, Sweden)
Long abstract:
What is ”interesting” to search for in the context of life detection missions? In future NASA missions to search for signs of life and habitability, the plan is to let AI decide which data is considered as ”interesting” to send back. In other words, which samples are interpreted as potential signs of life and habitability. This is a fundamental shift in the role of AI in a mission’s infrastructure - from facilitating scientists’ decisions on Earth, to making decisions on site.
How is AI interpreting the samples? In this paper, I reflect upon how the selection of samples to train AI is affecting the understanding of the ”normal” and the ”anomalous” life. Based on ethnography of development of AI at NASA Goddard Space Flight Center, I analyze AI in terms of a new classification system to understand life.
At the basis of AI for life detection are three major cascades of transformation. First is the encapsulation of examples of life and habitability in samples. Second is the interpretation of these samples during laboratory experiments. Third is shaping the aforementioned into the format of data that can be processed by AI.
I suggest that the degree of value granted or refused to data, is strongly related to the insight of programmers about the efforts of scientists. These efforts start with scientists selecting particular samples over others, making it a pivotal part of space missions and not least, the understanding of life.
Chenyue Pan (Tsinghua University)
Long abstract:
Electron microscopes are widely used in materials science and their ultra-high resolution allows scientists to study the micro-structure and characterization of materials in detail, promoting the development of science.
This article adopts a qualitative research methodology in which the author conducted a four-month field work in a national large-scale instrumentation center in China. The laboratory's electron microscope equipment is among the top in the world, including several scanning electron microscopes and transmission electron microscopes.
This study adopts a symmetrical perspective, focusing on the use of electron microscopy in materials science for sample collection and observation. The work shows that the electron microscope, as a central actor in the laboratory, imposes strict discipline and various restrictions on researchers' body. The electron microscope can only function effectively providing researchers' eyes, arms and torso remain in a specific position, which is extremely crucial for the production of scientific results. Meanwhile, the scientists, who gradually acquire tacit knowledge of the electron microscope, utilize their empirical body as an important research tool. Well-performing scientists eventually become a symbiont with the instruments during the embodied practice. The body, which has rich connotations, interacts with micro-technology and is enabled by technological extensions.
It is a new dimension to understand the contemporary making and doings of materials science. Additionally, the study aims to enhance the current laboratory research by providing a story with Chinese characteristics and present the latest developments in the field.
Matthijs Mouthaan (Utrecht University, Copernicus Institute of Sustainable Development) Laura Piscicelli (Utrecht University) Taneli Vaskelainen (University of Helsinki)
Long abstract:
Deep sea mining has attracted political and commercial interest in recent years as demand for rare earth minerals has increased and geopolitical tensions have resurfaced. Governed by the United Nations’ International Seabed Authority, exploration and exploitation of deep sea resources beyond national jurisdiction require science-industry collaborations to sample ecological data and transform it into ecological baselines and anticipated impacts of mining activities for scientific research and regulatory risk assessments. While science-industry collaborations provide the necessary infrastructure to do science in the hostile landscape of the deep sea, we explore the collaborative complexities that influence the sampling practices of ecological deep sea data. We are particularly interested in how scientific professionals and industry practitioners bidirectionally negotiate and decide on what data is most (and least) suitable to illuminate deep sea biodiversity, where and how (not) to collect this data, and how (not) to transform and abstract it into science- and policy-relevant knowledge. The deep sea represents an extreme case to explore tensions in collaborative sampling practices and the consequential transformation of sampling data due to fundamental uncertainties of the deep sea’s ecosystem and its vast spatial scale that problematizes attempts at data abstraction. We draw on extensive interviews with actors involved in these science-industry collaborations to detangle how sampling practices are negotiated and are representative of competing sampling narratives, and how these practices ultimately steer our collective understanding of the deep sea and the governance of deep sea mining.
Baptiste Gonella (University of Pau and Pays de l'Adour (France)) Xavier Arnauld de Sartre (CNRS, France) Guy Sénéchal (University of Pau)
Long abstract:
The Lacq gas field in southwest France is crucial as the largest hydrocarbon deposit in the country since its eruptive discovery in 1951. While extensive commercial gas extraction was the priority until the field became depleted, wastewater injection into the gas reservoir later initiated the transformation of the Lacq basin into a chemical industrial hub. Today, amidst strong criticism, a proposal is being made to explore geological carbon capture and storage in the reservoir. However, fluid manipulations (extraction and injection) have induced hundreds of earthquakes as unintended side-effects, forcing the industry to implement costly seismic monitoring networks. Despite the tremendous amount of data collected through these networks, data quality has highly varied due to network overlaps and abrupt shutdowns. This article examines the history of different monitoring tools used (such as networks, sensors, and algorithms), looking at how they have contributed to a fragmented body of knowledge about Lacq seismicity. Based on semi-structured interviews and archival research, this paper challenges singular accounts of seismicity, revealing that stakeholders (such as industry, regulator, scientists, citizens) have distinct knowledge interests. If substantial efforts have undoubtedly allowed a better understanding of induced seismicity, the divergence of knowledge interests has also led to undone science, having different impact and profits on stakeholders. In conclusion, this paper suggests that studying the history of monitoring tools can be a promising way to highlight the gap between stakeholders’ discursive statements and their implemented measures in knowledge, unveiling a certain (dis)interest in critical issues such as human-induced seismicity.