A Theory of Ambulance Chasing
Abstract
Ambulance chasing is a common socioscientific phenomenon in particle physics. I argue that despite the seeming complexity, it is possible to gain insight into both the qualitative and quantitative features of ambulance chasing dynamics. CompoundPoisson statistics suffices to accommodate the time evolution of the cumulative number of papers on a topic, where basic assumptions that the interest in the topic as well as the number of available ideas decrease with time appear to drive the time evolution. It follows that if the interest scales as an inverse power law in time, the cumulative number of papers on a topic is well described by a digamma function, with a distinct logarithmic behavior at large times. In cases where the interest decreases exponentially with time, the model predicts that the total number of papers on the topic will converge to a fixed value as time goes to infinity. I demonstrate that the two models are able to fit at least 9 specific instances of ambulance chasing in particle physics using only two free parameters. In case of the most recent ambulance chasing instance, the ATLAS {\gamma}{\gamma} excess, fits to the current data predict that the total number of papers on the topic will not exceed 310 papers by the June 1. 2016, and prior to the natural cutoff for the validity of the theory.
 Publication:

arXiv eprints
 Pub Date:
 March 2016
 arXiv:
 arXiv:1603.01204
 Bibcode:
 2016arXiv160301204B
 Keywords:

 Physics  Physics and Society;
 Computer Science  Digital Libraries;
 High Energy Physics  Phenomenology;
 Physics  Data Analysis;
 Statistics and Probability
 EPrint:
 9 pages, 4 figures