Nine reasons why Impact Factors fail and using them may harm science | I&M / I&O 2.0

"Over the past few months I have come across many articles and posts highlighting the detrimental effect of the enormous importance scholars attach to Impact Factors. I feel many PhDs and other researchers want to break out of the IF rat race, but obviously without risking their careers. It is good to see that things are changing, slowly but surely. It seems a good moment to succinctly sum up what is actually wrong with Impact Factors. 1) Using Impact Factors to judge or show the quality of individual papers or the authors of those papers is a clear ecological fallacy. In bibliometrics normal distributions are very rare and consequently mean values as the IF are weak descriptors. This certainly holds for citation distributions of articles published in a journal. They are often very skewed with a small number of very highly cited articles. The citation distributions of high IF journals are probably even more skewed ... 2) The use of impact factors creates and sustains a double Matthew effect. The disproportial attention for high IF journals makes that the same paper accepted by such a journal will get far more eyeballs and will even receive more citations than it would have received in other journals. Related to this is the effect that authors and asessors deem a paper better just because it was published in a journal with high IF or rejection rates and may think that citing a paper from high IF journals is the safe way to go to avoid comments from referees. Thus, part of the citations these papers receive are a free ride based on the visibility and citability of the well known journal brands in which they are published ... 3) Impact Factors calculated by Thomson Reuters (formerly ISI) are only available for a minority of all journals. Only 10,853 of the approximately 30,000 scholarly journals are included in the journal citation reports. Arts and humanities are left out as are the majority of non-English journals. It is very difficult for a journal to join the club ... 4) Impact Factors are irreproducible and not transparent. It is not possible, using the Web of Science data, to reproduce impact factors. What often is also not realized is that there is a difference between Impact Factor levels and average citation levels ... 5) Related to the previous point, Impact Factors are affected by the mix of publication types in a journal. In particular, the share of review articles positively affects the IF as these articles have very high citation rates ... 6) (Coercive) journal self citations are one of the more perverse effects of overly relying on Impact Factors. Journals want to compete and attract attention and citations and these are at least partially based on their IFs. Some journal editors bluntly ask their authors to cite content from the journal they publish in ...  7) There is a correlation, but no clear cut relation between citation numbers and paper quality. All citation metrics are biased by other factors ... 8) Impact Factors do not facilitate cross-discipline comparison and indirectly may make interdisciplinary work less attractive [id. at ArXiv]. Publication and citation cultures are very diverse across disciplines. The average number of citations per paper and the distributions of citations over time make that average impact factors of fields vary enormously ... 9) Impact factors have a long delay. Impacts Factors reflect citation to papers published in print between 1.5 and 4.5 years ago (as the Journal Citation report are published in June and reflect citation made in the previous year to papers published in the two years preceding that year.. The papers themselves may even be much older, because of the time lag between online and print publication and the time that passes between finishing the manuscript and publication ..."