Sunday, November 12, 2023

Another reason so much of science is so bad: bias in what gets researched.


Nina Strohminger and Olúfémi Táíwò write:

Most of us have been taught to think of scientific bias as a distortion of scientific results. As long as we avoid misinformation, fake news, and false conclusions, the thinking goes, the science is unbiased. But the deeper problem of bias involves the questions science pursues in the first place. Scientific questions are infinite, but the resources required to test them — time, effort, money, talent — are decidedly finite.

This is a good point. Selection bias is notoriously difficult for people to think about, as by its nature it depends on things that haven’t been seen.

I like Strohminger and Táíwò’s article and have only two things to add.

1. They write about the effects of corporations on what gets researched, using as examples the strategies of cigarette companies and oil companies to fund research to distract from their products’ hazards. I agree that this is an issue. We should also be concerned about influences from sources other than corporations, including the military, civilian governments, and advocacy organizations. There are plenty of bad ideas to go around, even without corporate influence. And, setting all this aside, there’s selection based on what gets publicity, along with what might be called scientific ideology. Think about all that ridiculous research on embodied cognition or on the factors that purportedly influence the sex ratio of babies. These ideas fit certain misguided models of science and have sucked up lots of attention and researcher effort without any clear motivation based on funding, corporate or otherwise. My point here is just that there are a lot of ways that the scientific enterprise is distorted by selection bias in what gets studied and what gets published.

2. They write: “The research on nudges could be completely unbiased in the sense that it provides true answers. But it is unquestionably biased in the sense that it causes scientists to effectively ignore the most powerful solutions to the problems they focus on. As with the biomedical researchers before them, today’s social scientists have become the unwitting victims of corporate capture.” Agreed. Beyond this, though, that research is not even close to being unbiased in the sense of providing accurate answers to well-posed questions. We discussed this last year in the context of a fatally failed nudge meta-analysis: it’s a literature of papers with biased conclusions (the statistical significance filter), with some out-and-out fraudulent studies mixed in).

My point here is that these two biases—selection bias in what is studied, and selection bias in the studies themselves—go together. Neither bias alone would be enough. If there were only selection bias is what was studied, the result would be lots of studies reporting high uncertainty and no firm conclusions, and not much to sustain the hype machine. Conversely, if there were only selection bias within each study, there wouldn’t be such a waste of scientific effort and attention. Strohminger and Táíwò’s article is valuable because they emphasize selection bias in what is studied, which is something we haven’t been talking so much about.



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