The state of our current scientific climate, as evidenced by 2013 articles in the Economist and perhaps more tellingly, the heated reaction TO those articles, can leave a budding scientist feeling overwhelmed (Article 1, Article 2). We are already given a laundry list of scientific caveats: to hold in memory the foundational papers leading to our own scientific questions, to thoroughly analyze and critique these papers, and to plan out the statistical analyses of our experiments before even warming up the centrifuge. And to add to that growing list, we now have to contend with the fact that the vast majority of those foundational papers are likely to contain incorrect or unverifiable data!? Why can’t I just trust the scientists that came before me and get on with my own contributions? That fact itself may make any reasonable person decide to kick the scientific can and walk away to something seemingly more attainable, such as pursuing a career as an Olympic triathlete.
The articles in the Economist claim that a number of factors contribute to the apparent sloppiness and unreliability of modern science including, but not limited to: professional pressure to “publish or perish,” the drooling of top-tier journals over novel results (replications are not sexy), and plain ol’ not understanding the intricacies and rigors of statistics.
One of the fiercest criticisms of the Economist’s papers is a graduate student’s acerbic response in Scientific American. He claims that: “In actuality, unreliable research and irreproducible data have been the status quo since the inception of modern science. Far from being ruinous, this unique feature of research is integral to the evolution of science.”
Say WHAT? First of all, saying that unreliable research is a unique feature of research does not make sense. Second of all, how can unreliable research and irreproducible results be integral to the evolution of science? Let’s see what his evidence is to back up his claims.
The author continues on to discuss examples (dare I say anecdotes!) of famous scientists, wrong about one thing or another, as his reasoning for why it’s okay to have irreproducible results. But is Galileo famous because he rolled a brass ball down a hallway and declared his law of the motion of falling bodies to no one in particular? Further, any ol’ mad hatter off the street could say the same and no one would blink. Why do we trust Galileo? The author gives no reason for why the foundations of science rest on men like Galileo, Darwin, and Dalton. He may do better to think about why we trust Galileo in the first place rather than take away the misleading message that “if Galileo can intentionally create unreliable scientific data, then so should we!”
Thomas Kuhn discusses paradigm shifts in his classic book, “The Structure of Scientific Revolutions.” Kuhn argues that scientific revolutions occur when anomalies are discovered in well-accepted paradigms, thus casting a new light onto old data. In the case of Galileo, he observed an anomaly in a well-regarded paradigm. Further, instrumentation to measure physical properties was not available to Galileo at the time. Much of science was logic and deduction. It was what we might think of as crude experimentation, with no true controls nor advanced statistical analysis. Kuhn states, “…the analytical thought experimentation that bulks so large in the writings of Galileo, Einstein, Bohr, and others is perfectly calculated to expose the old paradigm to existing knowledge in ways that isolate the root of crisis with a clarity unattainable in the laboratory.” In other words, until the thought was created by Galileo, the means to test it did not exist. It was only after Galileo created this paradigm shift in thought were other scientists ripe to do the rigorous experimental analysis. Of course, it’s also important to note that his scientific career did not hinge on tenure or grant money.
The Scientific American essay misses the point of the Economists’ critique. The Economist is not suggesting that the starts and stutters of the scientific process are a hindrance to progress, nor are they saying that science should come only from 100% “truthful” scientific publications (whatever that means), they are merely saying that we ought to be careful in our reporting and analysis of data. This responsibility includes the task of verifying the work that came before us. If we avoid this, we are doing a disservice to the great fathers of our scientific disciplines. Galileo and Darwin could have only dreamt about the possibilities we have at our modern-day fingertips. We ought not to let them down.
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