Bibliometric denialism or bibliometric Daniel-ism?

Less than a month ago, Daniel Torres-Salinas published a note on the ThinkEPI mailing list called “Negacionismo bibliométrico” (“Bibliometric denialism”). In it, he talked about the new atmosphere he is perceiving regarding bibliometrics. He called this new perception “bibliometric denialism”, a new trend that rejects scientific data and forms impossible expectations about what science can really provide, categorically denying the usefulness of bibliometric indicators and strongly discouraging their use in scientific evaluation processes.

Responses did not take long. Many people agreed with his view and expressed their wish to have a debate regarding this topic. Moreover, experts that participated in the conversation agreed that it is indeed a very hot topic, at least within the Spanish scientific landscape. Spanish evaluative institutions have signed declarations such as DORA, and then have applied them uncritically.

In the DORA’s case, the declaration focuses on a frontal and justified attack against the Impact Factor and the use of journal indicators applied to evaluate papers and scientists. Despite this, the Declaration does not unequivocally state that other indicators such as the H-index, social metrics or article-level metrics should not be used. It gives the impression that the criticism of the Impact Factor has been extended to the rest of the metrics, calling into question a large part of the bibliometric indicators and techniques. This represents a demanding and maximalist interpretation of the evaluative ideology of DORA. Moreover, uncritically criticising bibliometrics gives the impression that peer review is the only answer: there are no mentions to the problems of subjectivity, impartiality and bureaucratic cost of this alternative method.

Torres-Salinas finishes his reflection with the following paradox: it seems that, in the era of Big Data and data-informed decisions, we are promoting the opposite and denying the scientific corpus of Evaluative Bibliometrics. We will finish this note with the following statement of one of the email responses: “Data are not neutral, but less neutral is not having data or, even worse, not wanting to have data.”

What do you think? If you want to know more, you can read his note here.

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