Scientist or Data Collector

There has been speculation, in fact, as to why it is observed that older scientists sometimes jump off the deep end.

Maybe I felt a bit offended by this sentence in Steven Novella’s blog, so please excuse my perhaps barbed remarks.

First of all I’d like to mention there are diseases, Alzheimer’s for instance, that turn older people more forgetful and subsequently shut down there intellectual capabilities. I wont dwell on these disorders as they are difficult to diagnose in early stages and over a distance in time and space it’s impossible at all. I’ll focus on problems that lay in science itself and how it is organized.

Over the last century science developed from something that was eligible for enthusiasts only to a well funded respected profession. Along with increased funding, however, science changed its character. It became a mere data collecting business with many thousands or even millions of data collectors—I would not call them scientists in the original sense any more. Don’t get me wrong at this point. Of course, we need money to advance science. We need even more, if you ask me. And of course, we desperately need this newly recruited army of data collectors without which so grand tasks as the Human Genome Project could have never been fulfilled. (You feel the rascal in this sentence. Honestly I didn’t intend this in the first place.) But nowadays reading data from a sequencer for instance, requires less ingenuity than say navigating a ship. Scientists are professionals as everybody else. You cannot pick a genius in this ocean of mediocre data collectors. All odds are against it. It starts with the application for a grant. Some years ago, I attended a seminar of the organization women in science where the lecturer explained how to compose a successful application. Not only that the procedure of writing an application clearly favors those who are good at language, which is not an essential element of an ingenious scientist, she explained how to embellish and exaggerate the proposal. This has nothing to do any more with Marie Curie exhausting herself and spoiling her health only to advance science.

Also, because of this trend in science, it became increasingly difficult to pick a Nobel Laureate from the ocean of data collectors. Steven vividly illustrated how much luck is involved in becoming selected. I outlined how subconsciously such a decision is made sometimes.

The same holds true when a paper is submitted to a journal. The editorial staff consists exclusively of successful data collectors and proposal writers, so the system is designed to accept almost exclusively data collection papers and to bar the publication of what appears too outlandish, with one remarkable exception that is if the paper is submitted by an authority, a Nobel Laureate for instance. And here exactly is the reason why there appears so much stupid stuff from older scientists. The peer reviewers are hypercritical towards young and unknown scientists and uncritical towards old authorities. They do so because they are incapable of better judgment. Some years ago editors tried to explain the reason for rejection and a discussion might have ensued, nowadays they don’t even bother to sent an email. It can be understood as an adaptation process as it happens in biology, during domestication for instance. The public money favored the adaptation of the scientific community to as easy as possible get most of the money for less effort. For the records, it’s a fauceir process in fact.

By the way there is always a grain of truth in every so outlandish an idea or at least it can be an inspiration for an other more sophisticated concept, and this holds true for the Luc Montagnier paper too, but this is an other story not to be related here.


One thought on “Scientist or Data Collector

  1. Pingback: Grant application cheating « Fauceir Blog

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