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Re:50 Years Ago, Sugar Industry Quietly Paid Scientists to B... by 1vuio0pswjnm7 on Saturday February 13, 2021 @08:22PM (#26128792)
There is more than one way react to this paper. The top comment illustrates one way: "Everything is a lie. Distrust everything."

Obviously this approach could put the paper itself in question. How do we know it is not funded by "Big Fat". OK, that's silly but honestly where does the skepticism end and the truth begin.

Another way to look at this paper is that science is biased. It is biased in that people choose what to study. They decide what is "interesting". Given that resources to do research are limited, this has consequences. If they choose to focus on studying fat, then that may mean not studying something lese, like sugar.

Generally, scientists tend to be followers more than leaders. It makes sense to build on the work of others instead of striking out on a new path. New discoveries do not come easy. If the majority of labs are studying fat, then to a majority of people, including those funding research, studying sugar makes less sense.

This sort of herd mentality is certainly seen amongst programmers. I think it is even more extreme. As a programmer running with the herd, one lesson you could take from this is that whatever it is you are focused on right now might seem like the "right" choice of what to focus on that will lead you to the truth. If more or less everyone else is focused on it, too, how could the majority be wrong. The truth, however, which may not be recognised until some time in the distant future, is that you may be chasing the wrong thing.

I am very skeptical about the programming trends and areas of focus I read about every day on HN. I sense that is a minority viewpoint.

Re:50 Years Ago, Sugar Industry Quietly Paid Scientists to B... by kaba0 on Tuesday February 16, 2021 @07:57AM (#26153419)
People are biased but proper use of the scientific method and statistics is not. Of course there will always be a n=5 study on some stupid shit against the “mainstream” facts with bad methodology, but that doesn’t make the multiple independent n=insert big number proper studies’ findings bad. And thus, while there are definitely areas that are not yet well mapped, it doesn’t make the already well-known untrue.