>Science can go through similar periods of stagnation, and currently, it seems like we might have hit upon one.
Most of the recent criticism of science is related to the biological and medical sciences. I would disagree that these fields have hit on a period of stagnation. On the contrary, I believe that the biomedical sciences are in a period where there is a massive amount of recently generated data and innumerable ways to find correlations among these data. The data themselves are also recorded in a wide number of different formats and data from one paper might be difficult to compare to that from another (giving possibly unwarranted suspicions of non-reproducibility).
In the midst of this maelstrom of data, individual scientists are trying their best to make sure they maintain their publication rate and grant funding. As a consequence, findings are sometimes published "too early". While one might criticize this trend to early publication, the reality is that it is sometimes impossible to know exactly in which direction the "final answer" (if there is one) lies. Retaining data until one had found the complete and final answer to something is also a disservice to other researchers.
I appreciate the public debate on this matter and hope it ends up working both ways, i.e. the public and science journalists get to understand better the constraints in basic research, and the scientists are given a little more support to undertake more thorough studies.
With regards to the latter point, I would refer you to a review on studies involving mouse models of Alzheimer's disease [0]. In that review, the argument is made that almost all studies on this topic are under-powered (in a statistical sense), and most labs should be using 5 to 10 times more mice per experimental condition. This would more than double the cost of each experiment. For constant funding, this would mean halving the number of labs studying Alzheimer's disease, which might not be such a bad idea if the data coming out was more reliable as a result.
Most of the recent criticism of science is related to the biological and medical sciences. I would disagree that these fields have hit on a period of stagnation. On the contrary, I believe that the biomedical sciences are in a period where there is a massive amount of recently generated data and innumerable ways to find correlations among these data. The data themselves are also recorded in a wide number of different formats and data from one paper might be difficult to compare to that from another (giving possibly unwarranted suspicions of non-reproducibility).
In the midst of this maelstrom of data, individual scientists are trying their best to make sure they maintain their publication rate and grant funding. As a consequence, findings are sometimes published "too early". While one might criticize this trend to early publication, the reality is that it is sometimes impossible to know exactly in which direction the "final answer" (if there is one) lies. Retaining data until one had found the complete and final answer to something is also a disservice to other researchers.
I appreciate the public debate on this matter and hope it ends up working both ways, i.e. the public and science journalists get to understand better the constraints in basic research, and the scientists are given a little more support to undertake more thorough studies.
With regards to the latter point, I would refer you to a review on studies involving mouse models of Alzheimer's disease [0]. In that review, the argument is made that almost all studies on this topic are under-powered (in a statistical sense), and most labs should be using 5 to 10 times more mice per experimental condition. This would more than double the cost of each experiment. For constant funding, this would mean halving the number of labs studying Alzheimer's disease, which might not be such a bad idea if the data coming out was more reliable as a result.
[0] ‘Too much good news’ – are Alzheimer mouse models trying to tell us how to prevent, not cure, Alzheimer's disease? http://www.sciencedirect.com/science/article/pii/S0166223610...