‘Good’ & ‘bad’ science
I just step upon an excellent opinion article about good, bad, sound and junk science. Although is addressed to marine scientist, I think it has good lessons for every one who’s trying to make a living on the knowledge production business we call academia. If you’re interested on the full opinion paper, which I recommend, it’s entitled The good, the bad and the ugly science: examples from the marine science arena by E. Parsons and A. Wright from George Mason University. They define science as:
Science is a process. It’s the act of taking observations made in the natural world to test hypotheses, preferably in a rigorous, repeatable way. The tested hypotheses are then rejected if they fall short, rather than accepted if the data are compatible, and the results are ultimately critically reviewed by the scientific community. Concepts that work survive, whereas those that do not fit the observed data die off. Eventually, concepts that survive the frequent and repeated application of enormous amounts of observational data become scientific theory. Such theories become as close to scientific fact as is possible—nothing can be proved absolutely. This process holds for social science as much as for chemistry, physics or biology: it does not matter if the data come from surveys or observational data from humans. A study either follows this protocol or it does not. Put simply, it is science or it isn’t science.
The following passage reminded me of many conflicting opinions when faced to the regime shifts literature: what people argue what are or not regime shifts, and what constitutes a proof of their existence and / or occurrence. Not the both are different.
If a scientist were to follow the scientific method, a “good” scientist’s understanding of the environment changes as additional data are acquired, whereas a “bad” scientist sticks stubbornly to previously held beliefs despite being faced with data that suggest an alternative scenario. It is a basic tenant of scientific inquiry after all that hypotheses are rejected when not supported by data. Good scientists are willing to change their opinions quickly in the face of new evidence or in response to a good valid argument. However, opinions that are not based in data-tested hypotheses do not represent good or bad science; they are simply not scientific at all.
Sticking to an opinion or an idea despite evidence to the contrary is sadly quite common in the science community. One sees “scientists” who stubbornly resist new ideas and studies, especially those that contradict a paper that the “scientists” wrote or concepts that they have publicly supported, or even based their career on. But adapting to new evidence is a key criterion of the scientific method. When scientists stubbornly resist new evidence contrary to their opinion, it really is “bad science,” i.e., refusing to reject a hypothesis that has been shown to be false.
I hope the regime shifts database will help us to track the debate and distinguish what is ‘good’ from ‘bad’ as evidence accrue with time.