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.
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