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Double-Blind Peer-Reviewing and Inclusiveness in Russian NLP Conferences

Part of the Lecture Notes in Computer Science book series (LNISA,volume 11832)


Double-blind peer reviewing has been proved to be pretty effective and fair way of academic work selection. However, to the best of our knowledge, nobody has yet analysed the effects caused by its introduction at the Russian NLP conferences. We investigate how the double-blind peer reviewing influences gender and location (according to authors’ affiliations) biases and whether it makes two of the conferences under analysis more inclusive. The results show that gender distribution has become more equal for the Dialogue conference, but did not change for the AIST conference. The authors’ location distribution (roughly divided into ‘central’ and ‘not central’) has become more equal for AIST, but, interestingly, less equal for Dialogue.

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The article was prepared within the framework of the HSE University Basic Research Program and funded by the Russian Academic Excellence Project ‘5-100’.

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Correspondence to Andrey Kutuzov .

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Kutuzov, A., Nikishina, I. (2019). Double-Blind Peer-Reviewing and Inclusiveness in Russian NLP Conferences. In: van der Aalst, W., et al. Analysis of Images, Social Networks and Texts. AIST 2019. Lecture Notes in Computer Science(), vol 11832. Springer, Cham.

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  • Print ISBN: 978-3-030-37333-7

  • Online ISBN: 978-3-030-37334-4

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