We are living in an era of post-truth and alternative facts. Politicians and the public cherry-pick the data they trust, and choose to follow gut instincts and emotion over even ample but contradictory evidence. Our current president has been discrediting scientific results regarding many issues, such as climate change and vaccines. These trends are naturally deeply troubling to the scientific community.
But what happens when those trends also threaten the diversity and strength of the scientific community itself?
On our next #DiversityJC, we are going to discuss Maggie Koerth-Baker’s article: The Tangled Story Behind Trump’s False Claims Of Voter Fraud. It is a long piece with several links to relevant related articles, but very much worth the read. In short, it discusses how Trump and his team used the results from the peer-reviewed article Do non-citizens vote in U.S. elections? to backup his claims that “the election is rigged by millions of fraudulent voters — many of them illegal immigrants“.
This article brings up two themes for our next Diversity Journal Club:
First, what happens when science goes out in the wider world, especially newer findings on particularly polarized topics? The article is not open access, so in reading only to the highlights and abstract of the publication, it seems reasonable to infer that non-citizen immigrants might be voting at a higher rate than most experts thought. However, some additional reading identifies a potential pitfall with using very large databases in the study of low frequency categories, such as that in this paper: “in very large sample surveys, researchers may draw incorrect inferences concerning the behavior of relatively rare individuals in a population when there is even a very low level of misclassification.”
Scientists tend to think that larger samples sizes provide better results. But with some kinds of data, measurement errors come into play. And with large data, it is easy to find patterns that seem significant but are not – if you aren’t careful. For reasons like this, science can move slowly – it’s the process of many scholars reviewing and assessing the work to reduce uncertainty and make sure research is careful. This is clearly important for research using big data.
Yet while science can move slowly to address these issues – the rest of the world does not. Koerth–Baker’s story brings up how research that moves beyond the lab and into the wider culture can fall on deaf ears – or be twisted to fit an existing narrative or world view, especially on particularly topical topics (e.g. non-citizen voting is rampant and everywhere and must be stopped at all costs!).
Second, this article touches on immigration – and therefore some politicians have used it as an argument for restricting immigration. Yet science is a global human endeavor. The scientific method is the same everywhere on Earth, and scientists from everywhere contribute to science. Science works best without borders, engaging diverse collaborations and contributions, and the results enrich more of our lives the wider ideas and inventions can spread.
Collectively, then, the misinterpretation of a study like this, on a particularly critical but polarizing topic, can thrust results into the popular media in ways not supported by the facts and the data itself – to the detriment of science itself. To the detriment of scientists.
What are other dangers that misinterpretation of scientific results can bring – and when they speak to particularly pertinent topics, how do they then impact the scientific community? What other examples can you think of? What can be done to prevent this from happening?
Join our next #DiversityJC discussion this Friday, May 19th, 2pm EST.