The two articles that I focused on were The Economist article, “Trouble at the lab” and the Scientific America article “The Replication Myth: Shedding light on One of Science’s Dirty Little Secrets”. Both articles comment on prevalence of research bias in current scientific discoveries, though the articles reach drastically different conclusions on the impact that these biases will have on public perception and future scientific endeavors. While both The Economist and Scientific America articles argue that the error is inherent in the peer-review construct, my belief coincides with that of the Scientific America article in that irreproducibility in research is not inherently bad, but it is the nature in which this irreproducibility occurred that dictates its benefit to the scientific community.
The Economist article raises some troubling trends in peer-reviewed science. The article cites that “Fiveyears ago about 60% of researchers said they would share their raw data ifasked; now just 45% do.” My idealized view of science relies on two basic premises: one that the scientific method is sound and rigorous and second, that the science is conducted in a collaborative atmosphere. Limited funding creates an atmosphere that is in direct conflict with both of these premises. It fosters an environment that favors speed and novelty. It favors those who publish first and favors those that publish results not yet seen in its respective field, regardless of the fact that it could contradict a number of more rigorously researched findings. The peer review process can do little to correct it because it too is subject to these two shortcomings. Without the adequate time needed, they cannot offer a thorough assessment of the data presented to them. I am not inherently against irreproducible data. Like the ideas presented in the Scientific America article, I believe that this data can “allow science to evolve”. It can foster debate, conversations, and fruitful discussions, and through these interaction, we can further our understanding of science. However, when data is irreproducible because of negligent, haphazard, and irresponsible conduct, it does nothing to further the conversation, but destroys public perception of science. In doing so, further limits scientific funding and in turn, limits the soundness of the science.