Skinner used the term “schedules of reinforcement” to describe broad categories of reward patterns which come to reliably control the behavior of his experimental animals. For instance, when he rewarded rats for pressing a lever at a given interval after the last reinforcement (i.e., fixed interval; FI), the animals would pause pressing the lever until just before the interval was over and then start pressing the lever like mad. When the number of presses are plotted cumulatively over time, this leads to a scalloped plot (black trace in Fig. 1). A similar, but clearly distinct curve can be observed when the reward comes only after a given number of lever presses (i.e., fixed ratio; FR): there, the animals stop pressing while they consume the reward and then resume repeatedly pressing the lever until the next reward is consumed (blue trace in Fig. 1). If the ratio or interval is varied, however, the animals more or less consistently press the lever at a rate given by the reward frequency (red and green traces, Fig. 1).

Fig. 1.: Different categories of response patterns to different schedules of reinforcement. VR – variable ratio; FR – fixed ratio; VI – variable interval; FI – fixed interval

In an analogous way, if you tell scientists that they need a certain number of publications to get/keep their jobs, they will double the number of articles they publish. Likewise, if you tell scientists that they need to “acquire external funding” in order to get/keep their jobs, they will increase the number of grants they write, until it’s almost all they do. This latter response class is particularly absurd and counterproductive: the number of scientists keeps increasing, at least for now. In most countries, the increase is larger than the increase in public funds, or the public funds are even decreasing. This means that the success rate of getting research funding must drop, even if every researcher would not increase the number of grants they write. However, as each scientist needs grants to keep working, the dropping success rates have the same consequence as a VR schedule with a low probability of reward (red line, Fig. 1): scientists maintain a very high level of grant writing which matches the decreasing success rate: if it’s 10%, you have to – on average – write 10 grant proposals to get one of them funded. If the success rate is down to 5%, you have to write 20 and so on. As scientists multiply and keep increasing the number of grants they write, the success rates keep dropping accordingly, making the scientists write yet more proposals. A vicious cycle if ever there was one. Skinner couldn’t have devised a more pernicious schedule himself.

That may seem absurd enough, but it is only half of the story. As research “income is crucial to the development of world-class research“, not only universities are ranked according to the volume of government funds they attract, but also (and likely consequently) the scientists within each institution are ranked according to the funds they attract. In Germany, for example, how much funds a scientist can attract, can have direct effects on their salary. Thus, if there is a cheaper and a more expensive way to do the same experiment, it is in the scientist’s own best interest to chose the more expensive experiment. As it stands today, scientists should write as many grant proposals as possible and make them as expensive as possible. In other words: the successful scientist of today wastes not only time, but also tax funds. If you factor in that in order to get your grants funded, you also must publish in the so-called ‘top-journals’ where the key factor is getting past the professional editor, the most successful scientists of this day must be great salespersons: they need to sell grant agencies their wasteful research proposals and editors their unreliable papers. If we are lucky, some of them might also be great scientists, as well.


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Posted on  at 12:14