Alexandre Hocquet

For the last ten years, within molecular life sciences, the reproducibility crisis discourse has been embodied as a crisis of trust in scientific images. Beyond the contentious perception of “questionable research practices” associated with a digital turn in the production of images, this paper highlights the transformations of gel electrophoresis as a family of experimental techniques. Our aim is to analyze the evolving epistemic status of generated images and its connection with a crisis of trust in images within that field.From the 1980s to the 2000s, we identify two key innovations (precast gels and gel docs) leading to a “two‐tiered” gel electrophoresis with different standardization procedures, different epistemic statuses of the produced images and different ways of generating (dis)trust in images. The first tier, exemplified by differential gel electrophoresis (DIGE), is characterized by specialized devices processing images as quantitative data. The second tier, exemplified by polyacrylamide gel electrophoresis (PAGE), is described as a routine technique making use of image as qualitative “virtual witnessing.” The difference between these two tiers is particularly apparent in the ways images are processed, even though both tiers involve image digitization. Our account thus highlights different views on reproducibility within the two tiers. Comparability of images is insisted upon in the first tier while traceability is expected in the second tier. It is striking that these differences occur not only within the same scientific field, but even within the same family of experimental techniques. In the second tier, digitization entails distrust, whereas it implies a collective sentiment of trust in the first tier.

. Computational chemistry grew in a new era of “desktop modeling,” which coincided with a growing demand for modeling software, especially from the pharmaceutical industry. Parameterization of models in computational chemistry is an arduous enterprise, and we argue that this activity leads, in this specific context, to tensions among scientists regarding the epistemic opacity transparency of parameterized methods and the software implementing them. We relate one flame war from the Computational Chemistry mailing List in order to assess in detail the relationships between modeling methods, parameterization, software and the various forms of their enclosure or disclosure. Our claim is that parameterization issues are an important and often neglected source of epistemic opacity and that this opacity is entangled in methods and software alike. Models and software must be addressed together to understand the epistemological tensions at stake.

Computational reproducibility possesses its own dynamics and narratives of crisis. Alongside the difficulties of computing as an ubiquitous yet complex scientific activity, computational reproducibility suffers from a naive expectancy of total reproducibility and a moral imperative to embrace the principles of free software as a non-negotiable epistemic virtue. We argue that the epistemic issues at stake in actual practices of computational reproducibility are best unveiled by focusing on software as a pivotal concept, one that is surprisingly often overlooked in accounts of reproducibility issues. Software is not only about designing and coding but also about maintaining, supporting, distributing, licensing, and governance; it is not only about developers but also about users. We focus on openness debates among computational chemists involved in molecular modeling software packages as empirical grounding for our argument. We then identify and analyse four epistemic characteristics as key to the role of software in computational reproducibility.