Computer scientists at Columbia University in New York have used a mathematical model to estimate the number of flawed scientific papers that go unretracted, and its relation to journal impact factors.In correspondence published in EMBO Reports (M. Cokol et al. EMBO Rep. 8, 5, 422–423; 2007), the researchers find that fewer papers are retracted by journals with low impact factors. But their model raises as many questions as it answers, say specialists in scientific publishing, some of whom argue that it greatly oversimplifies the issues.
From the Nature story: “scientists and editors familiar with retraction issues are sceptical of the quality of the model’s input data. Theoretical modelling exercises will generate bad results if the input data are flawed, says Drummond Rennie, deputy editor of the Journal of the American Medical Association, and a medical researcher at the Institute for Health Policy Studies, at the University of California, San Francisco.
Although the number of retracted articles is probably only the tip of the iceberg in terms of the number that should have been retracted, the model — based on journal impact factor and number of retractions — is too simplistic to capture the complex reality of the issues affecting the size and nature of the hidden part, Rennie says.”
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