A professional athlete’s success is
measured by the number of championships they win during their career. Similarly an actor’s success may be measured
by the number of nominations and awards received during their career. Almost every profession has some way to
measure a person’s success, and science is no different. Julia Belluz says in her 2015 article Why you can’t always believe what you read in scientific journals that
publications are often used metric of scientific success.
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Not only is
there pressure for scientists to publish, but there is pressure for scientist
to publish positive results, or results that conclusively support or refute the
hypothesis tested in an experiment. Christopher
Pannuci says that “positive results are more likely to be submitted for publication than negative results.” This leads to a lack of negative results
being published in the literature and in some cases researchers will even “throw
out” negative results. While negative
results don’t confirm or refute a particular hypothesis, they can still tell us
something.
In recent years journals have been
started that publish only negative results, such as the Journal of Negative Results in BioMedicine or New Negatives in Plant Science.
I think this is an important step forward in science because it gives scientists
an avenue to share data with others that might not otherwise get published. Collaboration is a critical piece to the
advancement of science, and I believe the progression of science as a whole is
deterred by publishing primarily positive results.
The same emphasis should be placed on negative results that is currently
placed on positive results. In fact, it
almost seems unethical, in a way, to not publish negative results. In a sense,
you are discarding data because it does not fit your hypothesis, but it could
have the potential to lead to a breakthrough in a different experiment or field
of study. To me it seems akin to when
scientists “p-hack” their data until they get results that are publishable in
scientific journals. Modifying and
censoring published data to what scientists want to see (aka – significant and
positive results) seems like no way to advance the sciences in the coming
years.
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