Learning from failed models and negative results (Posters only) (co-organized)
|Convener: Laetitia Le Pourhiet | Co-Conveners: Susanne Buiter , Cedric THIEULOT|
/ Attendance Thu, 12 Apr, 17:30–19:00
Publication bias in academic research can occur when the outcome of an experiment or study influences the decision whether to publish it. The Geosciences are of course not immune to publication bias. This session aims at discussing the issues surrounding publication bias and how to learn from failed models and negative results.
In the Geosciences, as in other science fields, a study may have best chances for acceptance 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 deep down 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 Additionally, physically sound simulations may remain unpublished even when they could correspond to a concept that has not yet been considered because of, for example, scarce data.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.
In this session, we encourage constructive discussions of unexpected, controversial, failed and/or negative results on any aspect of tectonics, structural geology, geodynamics, geomorphology and related fields.