Hi David,
I agree that pitting the “top priority” group against the “no resources” group in a correlation is an odd way of approaching the data. I was trained not to create dichotomous variables unless advanced statistics tell us that the data is, indeed, dichotomous. Doing so gets rid of variance that may well be useful. The current analysis goes even further by excluding large numbers of people, as you noted.
I would be interested in seeing non-parametric correlations that can deal with ordinal data (e.g, Spearman’s) used on the full sample. I’m guessing the story may be different.
I would argue the article is extremely pessimistic.
Yes, funds sometimes get misallocated or are given to people who have committed fraud.
More often, they go to hard-working researchers who really don’t make that much at all...people who hate fake or misleading scientific claims more than the average taxpayer.
And yes, there’s a replication crisis...that people are aware of working to address.
In short, I think the author uses an extremely broad brush: “The widespread inability of publicly funded researchers to generate valid, reproducible findings is a testament to the failure of universities to properly train scientists and instill intellectual and methodologic rigor.”
And yet, scientific breakthroughs happen all the time and the world is better for it.
In short, maybe the author is burnt out or has only ever worked with poor colleagues? Or hasn’t been funded in a while?
Most of the researchers I’ve met are honest and hard-working and doing their best to get it right, even in the face of challenging questions and strained resources.