Editing Impact factor (section)

===Reproducibility===
While the underlying mathematical model is publicly known, the dataset which is used to calculate the JIF is not publicly available. This prompted criticism: "Just as scientists would not accept the findings in a scientific paper without seeing the primary data, so should they not rely on Thomson Scientific's impact factor, which is based on hidden data".<ref name="Rossner 2007"/> However, a 2019 article demonstrated that "with access to the data and careful cleaning, the JIF can be reproduced", although this required much labour to achieve.<ref name=":2">{{Citation |vauthors=Larivière V, Sugimoto CR |title=The Journal Impact Factor: A Brief History, Critique, and Discussion of Adverse Effects |date=2019 |work=Springer Handbook of Science and Technology Indicators |series=Springer Handbooks |pages=3–24 |veditors=Glänzel W, Moed HF, Schmoch U, Thelwall M |place=Cham |publisher=Springer International Publishing |doi=10.1007/978-3-030-02511-3_1 |arxiv=1801.08992 |isbn=978-3-030-02510-6 |s2cid=3677889}}</ref> A 2020 research paper went further. It indicated that by querying open access or partly open-access databases, like Google Scholar, ResearchGate, and Scopus, it is possible to calculate approximate impact factors without the need to purchase Web of Science / JCR.<ref>{{Cite journal |vauthors=Templ M |date=2020-06-19 |title=Modeling and Prediction of the Impact Factor of Journals Using Open-Access Databases: With an Application to the Austrian Journal of Statistics |url=https://www.ajs.or.at/index.php/ajs/article/view/1186 |journal=Austrian Journal of Statistics |volume=49 |issue=5 |pages=35–58 |doi=10.17713/ajs.v49i5.1186 |s2cid=225704065 |issn=1026-597X|doi-access=free }}</ref>