Whether this piece was actually published in New Scientist or elsewhere, I cannot remember; but by the note at the end about my job, this must have been written between late 1988 to autumn of 1989.
'Loadsamoney' was a catchphrase of a Harry Enfield character who performed on an improvised comedy show, late night on Fridays - he was an unskilled slapdash plasterer on building sites, who boasted of making 'loadsamoney' while doing a shoddy job...
Things have, of course, gotten much, much worse in science than I envisaged at this time.
LOADSAMONEY IN THE LAB
It’s hard to keep up with the changing criteria for scientific excellence these days. It seems no time since ‘Loadsapapers’ was the hero of the hour, and he was bad enough, but now that ‘Loadsamoney’ is top dog I am beginning to mourn our old hero’s passing.
To recapitulate: the problem we all face is to decide (for the purposes of implementing The Cuts) who is a good scientist and who is not; in order to be able to make up tables of research ability using some kind of numerical measure. The answer is that the best measure of scientist excellence in a given field is based on deep knowledge of the subject and of the individuals involved. There is no better measure than this. It is the bottom line. Unfortunately, we don’t have that information and if we did then people would still disagree on it. That is life, and it is how things are; but it isn’t what is required.
So the first compromise was made. Even if we are not competent to judge the scientists' quality we can look at the publications. Even if we can't judge the quality of the publications, we can count them. Good scientists will publish lots of papers because they are clever and work hard and bad scientists will not because they are lazy and/or thick! Notice the accumulation of approximations in the reasoning. Still, this managed to convince some of the people for some of the time and led to the birth of 'loadsapapers' as the paradigmatic successful scientist. He ruled the roost throughout most of the sixties and seventies.
The next hero did not last so long, probably only for the first half of the eighties. He was called 'Loadsacitations’. The logic ran that there was no point in writing ‘loadsa’ papers if nobody was reading them, or if having read them, they ignored them. It was important that a person's research made a big "impact" on their field. How could you find out about this.
Well, once again, if you were an expert in the area and knew the principal workers then you would know as well as anybody could. But this runs into the same problems as before, it subjective, it is not quantitative and it is too slow and expensive to gather the data. So we got citation counting whose logic is that if you receive lots of mentions in the references to others people's papers them you are a good scientist. If they don't mention you for whatever reason then that is bad. The even lazier version of this method is to find out the journals whose papers usually get frequently cited and call them ‘high impact’. If you publish in these journals then your work will probably be cited a Iot, which means that it is probably having a lot of influence in some way, which means that you will probably be a better scientist. Again the chain of approximations building up as we go.
People fairly soon got fed up with a system which defined the greatest biologist of the century as the man who devised a neat, accurate and quick method of measuring protein. And scientist were under a tight squeeze for cash. All this in a society where the entrepreneur was the model: the person who made money full stop. It didn't matter how, it didn't matter what was done with it - the point was to make the money.
And so ‘"loadsamoney’, the Harry Enfield character who flaunts his wealth, gave up plastering and moved into science. Instead of being judged by papers or by citations, scientists are now judged by income. Research funding is the thing: how much external funding you are 'drawing in'. The stars are the ones who get the Megabucks from the big funding agencies. If you get lots of money, the logic runs, then you must be good.
Money is, of course, quantifiable; but more important it is something which we would all like. It is, so far as doing scientific research goes, a definitely Good Thing. Well, like all of these measures, there is some truth in it. Some truth. But not enough, because of the circularity which is set up. Money = good scientist = more money = even better scientist. It is hardly exaggerating to say that, at present anyway, people are not looking further than the money! When the time comes to judge by results we will probably have a different measure of excellence anyway.
It's time to caIm down a bit and remember what this whole quality measurement exercise is actually for. It is to select the best. We simply have to accept that no formula can do this for us: neither a simple formula nor any complex, weighted and balanced formula either. Nothing is better than the judgement of a single well informed person, and nothing can be. It is as blankly simple, and as infinitely complex as that.
The latest news is that ‘Loadsamoney’ has left science. In fact he left after his first pay cheque. He couldn't believe that he was expected to administer multi-million dollar research grants without any allocation of time, in addition to an increasing teaching load, on less than l5K a year and, to cap it all, without tenure!
* Dr Bruce Charlton MD MA is senior demonstrator in the department of physiological sciences in the medical school at the University of Newcastle upon Tyne.
In engineering disciplines, there is a variant of Loadsamoney who is a successful and respected entrepreneur and treats the university as a convenient place to launch new business ventures while staying close to a source of young, inexpensive and energetic students who can be recruited to do the work for them. A lot of bureaucratic activity seems to revolve around supporting / feeding off of this character. Of course, business success and scientific advancement are two entirely separate things.
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