A quantitative analysis of measures of quality in science
arXiv:physics/0701311 · doi:10.1007/s11192-007-1868-8
Abstract
Condensing the work of any academic scientist into a one-dimensional measure of scientific quality is a difficult problem. Here, we employ Bayesian statistics to analyze several different measures of quality. Specifically, we determine each measure's ability to discriminate between scientific authors. Using scaling arguments, we demonstrate that the best of these measures require approximately 50 papers to draw conclusions regarding long term scientific performance with usefully small statistical uncertainties. Further, the approach described here permits the value-free (i.e., statistical) comparison of scientists working in distinct areas of science.
11 pages, 8 figures, 4 tables
References in corpus (2)
Cited by in corpus (19)
- The w-index: A significant improvement of the h-index
- Taking census of physics
- How relevant is the predictive power of the h-index? A case study of the time-dependent Hirsch index
- Science and Facebook: the same popularity law!
- Bibliometric Indicators of Young Authors in Astrophysics: Can Later Stars be Predicted?
- Completing
- A Case Study of the Arbitrariness of the h-Index and the Highly-Cited-Publications Indicator
- Using altmetrics for detecting impactful research in quasi-zero-day time-windows: the case of COVID-19
- Event shape sorting
- How to derive an advantage from the arbitrariness of the g-index
- How to evaluate individual researchers working in the natural and life sciences meaningfully? A proposal of methods based on percentiles of citations
- The inconsistency of the h-index
- Observables of non-equilibrium phase transition
- Comment: Citation Statistics
- New approaches for increasing the reliability of the h index research performance measurement
- Prospects of Event Shape Sorting
- Fluctuating shapes of the fireballs in heavy-ion collisions
- Event Shape Sorting: selecting events with similar evolution
- Examples for counterintuitive behavior of the new citation-rank indicator P100 for bibliometric evaluations