Phil Davis, Author at The Scholarly Kitchen

Phil Davis is a publishing consultant specializing in the statistical analysis of citation, readership, publication and survey data. He has a Ph.D. in science communication from Cornell University (2010), extensive experience as a science librarian (1995-2006) and was trained as a life scientist. https://phil-davis.com/

Articles by Phil Davis

Did ChatGPT Just Lie To Me?

After making up a false claim about a nonexistent study done by the AAAS, the AI software admitted that it made a mistake and then apologized.

Editors can’t spot talent. I’ve heard this joke before. It isn’t funny

Editors at The BMJ are lousy at predicting the citation performance of research papers. Or are they?

Desperately Seeking (Statistical) Significance

Twitter does not increase citations, a reanalysis of author data shows. Did the authors p-hack their data?

Fill in the Blank Leads to More Citations

When a reputable journal refuses to get involved with a questionable paper, science looks less like a self-correcting enterprise and more like a way to amass media attention.

Unpacking The Altmetric Black Box

Article Attention Scores for papers don’t seem to add up, leading one to question whether Altmetric data are valid, reliable, and reproducible.

Journal Citation Indicator. Just Another Tool in Clarivate’s Metrics Toolbox?

Can Clarivate deliver on a single, normalized measurement of citation impact or did its marketing department promise too much?

Sci-Hub Citation Study Confuses Causes With Effects

Do Sci-Hub downloads cause more citations, or are high impact papers simply downloaded more often?

Changing Journal Impact Factor Rules Creates Unfair Playing Field For Some

Some journals are expected to benefit immensely under Clarivate’s new counting model.

Changes to Journal Impact Factor Announced for 2021

Starting 2021, Journal Impact Factors will be calcuated using online publication dates, not print ones. But phased roll-out may lead to bias for some journals.

Tweeting-Citations Authors Speak, Finally

We stand by our data. We just won’t share it or believe that you replicated our study.

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