“Trial and error” is one of the fundamental principles of science, yet the errors are seldom published. Failed experiments, including negative results, statistically insignificant data, and imperfect modelling, are all natural parts of the scientific journey. However, publication bias, the tendency to only publish positive outcomes, leaves out a significant part of the story.
In the Geosciences, as in other science fields, a study may have better chances to be accepted for publication in scientific literature if it confirms a theory or conceptual idea that is well accepted in the community or if it reaches a positive result. The cases that fail in their test of a new method or idea often end up in a drawer (which is why publication bias is also sometimes called the “file drawer effect”). Additionally, physically sound simulations may remain unpublished even when they could correspond to a concept that has not yet been considered because of, for example, scarce data. Conversely, negative results such as numerical methods that fail to converge or that turn out not to be worth pursuing also never get published. This is potentially a waste of time and resources within our community as other scientists may set about testing the same idea or model setup without being aware of previous failed attempts.
This session aims at discussing the issues surrounding publication bias and how to learn from failed models and negative results. We encourage constructive discussions of unexpected, controversial, failed and/or negative results from all disciplines of the Geosciences.