How might you measure a scientist’s ‘scientific worth’?
Today I will cover three indices developed to rank just how effective scientists are! In alphabetical and best to last order.
This index attempts to capture both the productivity and citation impact of a researcher by measuring the number of papers and number of citations these papers have. To calculate, ‘h’ is the number of papers h that have at least h citations (the other papers (total papers – h) have no more than h citations). See figure below.
This is an index created by Google Scholar for Google Scholar – only they use this measurement. It is simple: ‘i10’ equals the number of papers with at least 10 citations.
An example of these first two indices in use can be seen in a screen shot of the Google Scholar Alfred Wegener – who had a mighty nice theory about continental drift (which forms a substantial basis of today’s understanding of plate tectonics). Unfortunately Alfred never made it to see how he would rank on the last index.
Here ‘k’ stands for Kardashian.1 An index defined as “a measure of discrepancy between a scientist’s social media profile and publication record based on the direct comparison of numbers of citations and Twitter followers”. To find ‘k’, divide twitter followers by total citations. Kim Kardashian is the highest ranked in the system for being one of the most followed people on twitter (with very few scientific publications).
The inventor of the k-index (Neil Hall) declares “those people whose K-index is greater than 5 can be considered ‘Science Kardashians’”. These so called Kardashians are highlighted on the graph below. Hall advises that these Kardashians should get off twitter and get back to paper writing!!
So who are some of the greatest Science Kardashians?
This k-index portrays science communication as a negative. But some would think, is it not the ultimate goal of science to be able to communicate it with peers and the broader community? I mean how else will you get those citations up? Social media and science can (and should) overlap in a Venn diagram’s space. The exchange of ideas and communication of results should be the goal!
What’s your K-index?