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Seeing Like a Model Fish

How Digital Extractions Mediate Metabolic Relations

Bibliographic Data

ID5338044
AuthorsBauer (0000-0001-5760-5965, University of Oslo, corresponding author)
Year2024
Volume49
Issue3
Pages524-554
Publication date2024-05-01
Peer ReviewedYes
Open AccessYes
TypeARTICLE
VenueScience Technology & Human Values (JOURNAL)
Journal identifiersISSN: 0162-2439 • E-ISSN: 1552-8251
PublisherSAGE Publications Inc (PUBLISHER)
DOI10.1177/01622439241236520
OpenAlexW4393277806
LanguageEN
References cited64

Digital models have become key sites of biological practice and science policy. This paper examines efforts to craft a digital salmon model for metabolic research. It traces the data configurations of feed, food, and health in Norway's bioeconomy aspirations-from cell culture studies in the lab to an integrated digital repository and public health nutrition trials in schools. A response to policy calls for more sustainable aquaculture, digital models become lynchpins for intensified data sourcing. I describe how datafication and digital model integration enact a particular mode of management, focused on profitability and human preferences, when optimizing fish feed to sustainability goals. Integrating molecular biology and mathematical functions, digital modeling promotes the idea of a prediction machine for preemptive optimization of feed and food across settings. Yet, unforeseen disruptions to aquaculture, for instance, by algae and lice, expose the complexity of marine food webs and the limitations of digital models. Even while in the making, the digital fish model becomes performative and shapes knowledge practices much beyond the lab. As knowledge infrastructures, models participate in the remaking of metabolic relations, recalibrating decision-making, while feeding back into and co-shaping the very entities and environments they were crafted to investigate

Biology · Computational biology · Fish · Fishery · Bioinformatics and Genomic Networks · Computer Science · Nutrition, Genetics, and Disease · Single-cell and spatial transcriptomics

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