deletions | additions       diff --git a/the fork factor.tex b/the fork factor.tex  index 03e058e..f91ff0c 100644  --- a/the fork factor.tex  +++ b/the fork factor.tex 
...
\textbf{More forking, more impact, less bad science.} Obviously, the more of your research data are published, the higher are you chances that they will be forked and used as a basis for groundbreaking work, and in turn, the higher the interest in your work and your academic impact. Whether your projects are data-driven peer reviewed articles on Authorea discussing a new finding, raw datasets detailing some novel findings on \href{http://zenodo.org}{Zenodo} or \href{http://figshare.com}{Figshare}, source code repositories hosted on Github presenting a new statistical package, every bit of your work that can be reused, will be forked and will give you credit. Do you want to do a favor to science? Publish also non-confirmatory results and help your scientific community to quickly spot \href{http://www.nature.com/news/papers-on-stress-induced-stem-cells-are-retracted-1.15501}{bad science} by publishing a dead end fork (Figure 1).  \textbf{And now onto the nerdy part: The Fork Factor}. So, we would like to imagine what academia would be like if forking actually mattered in determining a scholar's reputation. reputation and funding.  How would you calculate it? Here, we give it a shot. We define the \textbf{Fork Factor} (FF) as: \begin{equation}  FF = N*(L^{\frac{1}{\sqrt{N}}}-1)  \end{equation}