Abstract I discuss Van Drimmelen’s (2023) Metascience2023 presentation on researchers’ decision making during the research process.

Tom Hostler has just published an article titled “The invisible workload of open research” in the Journal of Trial and Error’s special issue on the “Consequences of the scientific reform movement: Is the scientific reform movement headed in the right direction?” It’s an insightful and thought-provoking piece that uncovers the potential workload costs of open research, considers why these costs may be ignored by university management,

The December 2022 issue of the journal Industrial and Organizational Psychology includes a very interesting discussion of the pros and cons of open science. There’s a target article titled “Open science, closed doors: The perils and potential of open science for research in practice” (Guzzo et al., 2022) and nine commentaries on this article. You can find all 10 papers here.

In this new article, I consider questionable research practices in the field of metascience. A questionable metascience practice (QMP) is a research practice, assumption, or perspective that’s been questioned by several commentators as being potentially problematic for metascience and/or the science reform movement. I discuss 10 QMPs that relate to criticism, replication, bias, generalization, and the characterization of science.

Sabina Leonelli’s new book – “Philosophy of Open Science” – will be published later this year. However, there is an open access preprint available on the PhilSci Archive here. In the book, Leonelli provides “a constructively critical reading” of the standard approach to open science which, she argues, is focused on sharing “objects” such as data and materials.

I really enjoyed Mel Andrews’ recent essay: "Philosophy in the Trenches and Laboratory Benches of Science" and its main point that “every laboratory needs a philosopher.” This point is made in the context of a concern about “the industrialisation of science”: This concern about the industrialisation of science reminded me of something that statistician Ronald Fisher wrote many years ago when he argued that the Neyman-Pearson approach to