Recent quotes:

Study of reproducibility issues points finger at the mice | Ars Technica

The first thing that's obvious from the results is that there's no single reproducibility problem. Some of the experiments reproduced just fine, with limited variability. Others, as you might expect, saw differences between the strains. But for half of those cases, the magnitudes of the strain differences varied such that one lab might see a statistically different effect while another wouldn't. In one case, the strains showed opposite behaviors in the different labs. Beyond that, results were all over the map. In some cases, the mouse strain was the biggest source of variability. In others, it was the lab. The impact of the individual researcher, which was significant in other studies, turned out to be minor in all but one or two of the tests. But one of the strongest results was how much of the variability couldn't be accounted for by anything tracked by the study. In nine of the 10 tests, the unaccounted-for variation was above 25 percent of the total, and it was above half in six of the 10. "Things we didn't think to test" could be an extremely large category, but in this case, it's hard to think of ways to perform the experiments more consistently than they were done here. So while variations could be due to a large number of factors, that may make little practical difference since we can't control those factors anyway.

The chronic growing pains of communicating science online

The business-as-usual response to this challenge from many parts of the scientific community—especially in science, technology, engineering, and mathematics fields— has been frustrating to those who conduct research on science communication. Many scientists-turned-communicators continue to see online communication environments mostly as tools for resolving information asymmetries between experts and lay audiences (3). As a result, they blog, tweet, and post podcasts and videos to promote public understanding and excitement about science. To be fair, this has been driven most recently by a demand from policy-makers and from audiences interested in policy and decision-relevant science during the COVID-19 pandemic.

Agnotology and Epistemological Fragmentation – Data & Society: Points

Epistemology is the term that describes how we know what we know. Most people who think about knowledge think about the processes of obtaining it. Ignorance is often assumed to be not-yet-knowledgeable. But what if ignorance is strategically manufactured? What if the tools of knowledge production are perverted to enable ignorance? In 1995, Robert Proctor and Iain Boal coined the term “agnotology” to describe the strategic and purposeful production of ignorance. In an edited volume called Agnotology, Proctor and Londa Schiebinger collect essays detailing how agnotology is achieved. Whether we’re talking about the erasure of history or the undoing of scientific knowledge, agnotology is a tool of oppression by the powerful.