I have written previously about Journal Impact Factors (here and here). The response to these articles has been great and earlier this year I was asked to write something about JIFs and citation distributions for one of my favourite journals. I agreed and set to work. Things started off so well. A title came straight to mind. In the […]
Tag: metrics
Throes of Rejection: No link between rejection rates and impact?
I was interested in the analysis by Frontiers on the lack of a correlation between the rejection rate of a journal and the “impact” (as measured by the JIF). There’s a nice follow here at Science Open. The Times Higher Education Supplement also reported on this with the line that “mass rejection of research papers by […]
The Great Curve II: Citation distributions and reverse engineering the JIF
There have been calls for journals to publish the distribution of citations to the papers they publish (1 2 3). The idea is to turn the focus away from just one number – the Journal Impact Factor (JIF) – and to look at all the data. Some journals have responded by publishing the data that underlie the JIF […]
What Difference Does It Make?
A few days ago, Retraction Watch published the top ten most-cited retracted papers. I saw this post with a bar chart to visualise these citations. It didn’t quite capture what the effect (if any) a retraction has on citations. I thought I’d quickly plot this out for the number one article on the list. The plot […]
White label: the growth of bioRxiv
bioRxiv, the preprint server for biology, recently turned 2 years old. This seems a good point to take a look at how bioRxiv has developed over this time and to discuss any concerns sceptical people may have about using the service. Firstly, thanks to Richard Sever (@cshperspectives) for posting the data below. The first plot shows the number of […]
Where You Come From: blog visitor stats
It’s been a while since I did some navel-gazing about who reads this blog and where they come from. This week, quantixed is close to 25K views and there was a burst of people viewing an old post, which made me look again at the visitor statistics. Where do the readers of quantixed come from? Well, geographically they […]
The Great Curve: Citation distributions
This post follows on from a previous post on citation distributions and the wrongness of Impact Factor. Stephen Curry had previously made the call that journals should “show us the data” that underlie the much-maligned Journal Impact Factor (JIF). However, this call made me wonder what “showing us the data” would look like and how journals might […]
Creep Diets: Fewer papers published at JCB
A couple of years ago, a colleague sent me this picture* to say “who put J Cell Biol on a diet?”. I joked that maybe they publish too many autophagy papers and didn’t think much more of it. Recently, Ron Vale put up this very interesting piece on bioRxiv discussing what it takes to publish […]
Wrong Number: A closer look at Impact Factors
This is a long post about Journal Impact Factors. Thanks to Stephen Curry for encouraging me to post this. tl;dr — I really liked this recent tweet from Stat Fact It’s a great illustration of why reporting means for skewed distributions is a bad idea. And this brings us quickly to Thomson-Reuters’ Journal Impact Factor […]
Waiting to Happen: Publication lag times in Cell Biology Journals
My interest in publication lag times continues. Previous posts have looked at how long it takes my lab to publish our work, how often trainees publish and I also looked at very long lag times at Oncogene. I recently read a blog post on automated calculation of publication lag times for Bioinformatics journals. I thought it would […]