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.