Rota’s third advice is a bit problematic: 3 Publish the same result several times
As I looked through his Collected Papers however, another picture emerged. The editors had gone out of their way to publish every little scrap Riesz had ever published. It was clear that Riesz’ publications were few. What is more surprising is that the papers had been published several times. Riesz would publish the first rough version of an idea in some obscure Hungarian journal. A few years later, he would send a series of notes to the French Academy’s Comptes Rendus in which the same material was further elaborated. A few more years would pass, and he would publish the definitive paper, either in French or in English.
He justifies this on the basis that different versions will speak to different sub-disiplines who might appreciate what you are doing. This is similar to the difference between r- and K- selection.Are you a bug or a fish that produces 1000’s of offspring at a time, hoping some survive to reproduce the next generation? Or are you an elephant with a 2 year gestational period, and having at most a calf every 5-7 years?
When Rota was thinking, the world was different (although can be truthfully said for any point in time). The pressure to publish was not as great as it is now, which in turn leads to the temptation to publish the same stuff over and over. This is inherently bad, as you will become known as a douchbag of a scientist.
Yet, there is a value to this advice, at least if you cross field boundaries (possibly mid-career). With the caveats of at least some new data and more new interpretation and certainly a new and interesting context and implications, republishing can be valuable. I publish both in clinical journals (which tend to be lower IF) because that’s where people who review my grants read, publish and edit. Yet my heart and mind belongs to basic science journals. The implications of my work speak to both.
AND! Remember Drug Monkey’s advice about preliminary data (not the same as publishing):
Stop whining about preliminary data. Base it on feasibility and work from there. Most figures support at least a half dozen distinct grant applications. Maybe more.
(NB: this is an all around great post about funding.. go read it again)