WARNING OVER SCIENCE CITATIONS

WARNING OVER SCIENCE CITATIONS

世界數學界：不能過度依賴“引用統計”

英國《金融時報》艾倫•凱恩(Alan Cane)報導

2008年6月23日 星期一

Popular accounts of scientific discoveries depend on the quality of the scientific journals in which the original research appears. They, in turn, depend on the integrity of working scientists who review contributions and give them their seal of approval.科學研究的傳播流行程度，取決於刊登原始研究的科學雜誌的質量。而雜誌質量的好壞，又取決於審查、【放行出版】稿件的科學家的【正直】誠實。

In recent years, citation statistics have assumed increasing importance in assessing the quality of a piece of research. Essentially, the method measures the number of times a piece of research is cited by other scientists.近年來，在評估一篇研究的質量方面，引用統計變得越來越重要。該方法實際上就是計算一篇研究被其他科學家引用的次數。

It results in numbers called the “impact factor” and “h-index”, and these can have a significant influence on whether an academic achieves university tenure.這導致了“影響因數”(impact factor)和“h指數”(h-index)等數字的出現，並且這些數字對一位元學者能否獲得大學終身職位有著重大影響。

Now three heavyweights of the mathematical world, the International Council for Industrial and Applied Mathematics, the International Mathematical Union and the Institute of Mathematical Statistics, have issued a strongly worded warning against placing too much reliance on citation statistics.現在，數學界的三個重量級組織——國際工業與應用數學聯合會(International Council for Industrial and Applied Mathematics)、國際數學聯盟(International Mathematical Union)以及美國數理統計學會(Institute of Mathematical Statistics)已經對引用【統計】資料的過度依賴發出了措辭嚴厲的警告。

They argue that while they may seem accurate, objective and simple, they are not.他們認為，儘管它們可能看起來很準確、客觀、簡單，但並非如此。

“While having a single number to judge quality is indeed simple,” they write in a joint report, “it can lead to a shallow understanding of something as complicated as research. Numbers are not inherently superior to sound judgments.”他們在一份聯合報告中寫道：“儘管用一個單一的數字來判斷質量的好壞確實很簡便，但可能會導致人們對科學研究等複雜東西的狹隘理解。數字並非本來就好於合理的判斷力。”

Research is too important, they conclude, to measure its value with only a single coarse tool.他們總結道，研究太重要了，不能僅僅用一個粗糙的工具就來衡量它的價值。

譯者/董琴【內為hc 】