deletions | additions       diff --git a/the fork factor.tex b/the fork factor.tex  index dca8c9b..e404a15 100644  --- a/the fork factor.tex  +++ b/the fork factor.tex 
...
\textbf{Research impact in the era of forking.} A number of \href{http://altmetrics.org/manifesto/}{alternative metrics for evaluating academic impact} are emerging. These include metrics to give scholars credit for sharing of raw science (like datasets and code), semantic publishing, and social media contribution, based not solely on citation but also on usage, social bookmarking, conversations. We, at Authorea, strongly believe that these alternative metrics should and will be a fundamental ingredient of how scholars are evaluated for funding in the future. In fact, \href{https://www.authorea.com}{Authorea} already welcomes data, code, and raw science materials alongside its articles, and is built on an infrastructure (Git) that naturally poses as a framework for distributing, versioning, and tracking those materials. \href{http://en.wikipedia.org/wiki/Git_(software)}{Git} is a versioning control platform currently employed by developers for collaborating on source code, and its features perfectly fit the needs of most scientists as well. A versioning system, such as \href{https://www.authorea.com}{Authorea} and \href{http://www.github.com}{GitHub}, empowers \textbf{forking} of peer-reviewed research data, allowing a colleague of yours to further develop it in a new direction. Forking inherits the history of the work and preserves the value chain of science (i.e., who did what). In other words, forking in science means \textit{standing on the shoulder of giants} (or soon to be giants) and is equivalent to citing someone else's work but in a functional manner. Whether it is a "negative" result (we like to call it non-confirmatory result) or not, publishing your peer reviewed research in Authorea will promote forking of your data. (To learn how we plan to implement peer review in the system, please stay tuned for future posts on this blog.)  \textbf{More forking, more impact, higher quality science.} Obviously, the more of your research data are published, the higher are you your  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).