Paper short abstract:

Working through relationships of asymmetry informing interactions within and between STEM and social scientists involved in early cancer detection projects, I reconstruct the place and value of the ethnographic method within molecular research infrastructures.

Paper long abstract:

Situated within novel translational and transatlantic research infrastructures for the early detection of cancer, major science funders bring together many STEM professionals, economists and social scientists. The aim is to accelerate the discovery and validation of molecular biomarkers to uncover and intervene in the natural history of early-stage or premalignant lesions. Whilst researchers and various publics need to first get on board and be persuaded by the narrative of early detection to realise its vision, the process of integrating multidisciplinary approaches has been mired by as many opportunities as tensions. In this presentation, I unpack some of the concerns scientists articulated when invited to participate in an ethnographic study about cancer early detection within a British academic research centre. I underline the imagined boundaries around ‘ownership’, ‘competence’ and ‘confidentiality’ that scientists erected to protect what they saw as a sensitive intellectual project. I then outline the mutual implications of carrying out ethnographic work in STEM scientists’ professional lives and spaces. Finally, I explore the imagined divides that separated my work from the scientists’ projects, teasing apart the practices through which those divides were sometimes negotiated: from the idea of participating in a social science study as a token of public engagement to investing in an ongoing process of what I call ‘disciplinary catching up’. Working through relationships of asymmetry informing interactions within and between STEM and social scientists, I reconstruct the place and value of the ethnographic method within molecular research infrastructures.

Paper short abstract:

Experts involved in classifying disease make important moral decisions about inclusion and progress. Drawing on ethnographic work among classifiers, I reflect on the opportunities for social scientists to cultivate potent epistemic spaces and meaningfully contribute to classification projects.

Paper long abstract:

Experts involved in classifying disease make important decisions about the necessary use of technology, the addition of novel disease entities, and the affective registers of disease nomenclature. In doing so, they make moral arguments about access, inclusion, communication, and progress, often drawing on examples to bolster their cases. And yet, the empirical detail of these examples is often slim and what might be called the evidence of their claims is far less scrutinised than what is expected for more “scientific” claims. Many experts are aware of this and lament having to rely on personal and anecdotal evidence. Foregrounding these dimensions of classification work creates a mandate for the social sciences to fill in the detail and raise the bar of evidence. The question, then, is how to assume this mandate in ways that can meaningfully impact disease classification and its integration. Drawing on ethnographic work with experts classifying cancer at an increasingly molecular level, I reflect on the opportunities for the social sciences to cultivate potent epistemic spaces and repackage experts’ concerns in ways that are relevant and meaningful for them. In particular, I will discuss the importance of emphasising shared histories, delineating expertise, finding entry-points, reframing concerns, and imagining collaboration.

Paper short abstract:

For ethnographic research to capture translations of data, the disruptions and practices that surround data infrastructuring in biomedical research, this work argues that—just as data oscillates between states—ethnographers must oscillate between different perspectives and methods.

Paper long abstract:

In today’s biomedical laboratory, data infrastructures support the researchers’ work from data collection to data analysis thereby transforming data from brain tissue to cleaned and processed analyzable images and finally into research insights. For these transformations to work, such infrastructures need to be constantly maintained, updated, and improved. When not well integrated, the introduction of new steps and technological tools can disturb established practices in the laboratory. It can also shift attention away from generating new scientific results to working on infrastructures. In this process, what has been a means to do research becomes the end in itself.

This presentation is based on ethnographic fieldwork in a biomedical laboratory that invites the “crowd” to contribute to the analysis of research data by way of “virtual microscope” in an online citizen science project. Focusing on “infrastructuring as material-semiotic practice” (Niewöhner 2015), not only allows ethnographers to grasp biomedical research data in its various states, but also to attend particularly to the introduction of new data pipeline steps which compel scientists to temporarily move their research goals out of sight in order to build new infrastructures, investing in its potential future benefits when those infrastructures will have vanished into the background again. Here, infrastructuring goes hand in hand with practices of building trust and persuasion of scientists. For ethnographic research to capture these practices, the disruptions and oscillations in data states, this work argues that ethnographers must also oscillate between different perspectives and methods to follow the data and its surrounding practices.

Paper short abstract:

Based on ethnographic research in a medical science laboratory, this presentation examines the sites of material and data translation as “border zones” where coded ideals, for good scientific practice and disease treatment discovery, inform the daily activities of scientists in this process.

Paper long abstract:

Bioscientific experiments have always necessitated a transfer of substances from one form to another. Historically, “wet” data like cellular assays became autoradiographs in the laboratory, just as the scientific discoveries they represented were transformed first into talk among researchers, and then into text for publication (Cetina Knorr, 1990). The logics of translation which guide these activities have frequently been a focus of laboratory ethnographies, but with the advent of “drier” forms of data production these practices are growing increasingly complex. Substances like human cells take on multiple, even simultaneous, iterations as they move from the hospital to the petri dish and into the binary language of computers. At each moment of transformation, bioscientists must work to preserve the essences they aim to investigate, while they sort and remove what’s been classified as noise in their materials. As research on the translation of literature has already shown, texts undergo transformation with logics that are diverse and constantly shifting, and that are equally dependent on the deft decision-making of translators themselves; for example, whether to create translations that maintain the flavor of the original language at the cost of loss in accuracy of meaning (Gambier, 1995). What logics then inform this bioscientific practice today? Based on ethnographic research conducted in a medical research laboratory in Japan, this presentation examines the sites of material and data translation as “border zones” (Steiner, 1996) where coded ideals, for good scientific practice and disease treatment discovery, inform the daily activities of scientists in this process.