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

  • Conference paper
  • First Online:
Analysis of Images, Social Networks and Texts (AIST 2019)

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

Abstract

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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Notes

  1. 1.

    https://aistconf.org/.

  2. 2.

    http://www.dialog-21.ru/en/.

  3. 3.

    https://nlp.rusvectores.org.

  4. 4.

    https://ainlconf.ru/.

References

  1. Budden, A.E., Tregenza, T., Aarssen, L.W., Koricheva, J., Leimu, R., Lortie, C.J.: Double-blind review favours increased representation of female authors. Trends Ecol. Evol. 23(1), 4–6 (2008)

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Acknowledgements

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

Author information

Authors and Affiliations

  1. University of Oslo, Oslo, Norway

    Andrey Kutuzov

  2. Skolkovo Institute of Science and Technology (Skoltech), Moscow, Russia

    Irina Nikishina

  3. National Research University Higher School of Economics, Moscow, Russia

    Irina Nikishina

Authors
  1. Andrey Kutuzov
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  2. Irina Nikishina
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Corresponding author

Correspondence to Andrey Kutuzov .

Editor information

Editors and Affiliations

  1. RWTH Aachen University, Aachen, Germany

    Wil M. P. van der Aalst

  2. University of Ljubljana, Ljubljana, Slovenia

    Vladimir Batagelj

  3. National Research University Higher School of Economics, Moscow, Russia

    Dmitry I. Ignatov

  4. Krasovskii Institute of Mathematics and Mechanics, Yekaterinburg, Russia

    Michael Khachay

  5. National Research University Higher School of Economics, Moscow, Russia

    Valentina Kuskova

  6. University of Oslo, Oslo, Norway

    Andrey Kutuzov

  7. National Research University Higher School of Economics, Moscow, Russia

    Sergei O. Kuznetsov

  8. National Research University Higher School of Economics, Moscow, Russia

    Irina A. Lomazova

  9. Lomonosov Moscow State University, Moscow, Russia

    Natalia Loukachevitch

  10. LORIA, Vandœuvre-lès-Nancy, France

    Amedeo Napoli

  11. University of Florida, Gainesville, FL, USA

    Panos M. Pardalos

  12. Ca Foscari University of Venice, Venice, Italy

    Marcello Pelillo

  13. National Research University Higher School of Economics, Nizhny Novgorod, Russia

    Andrey V. Savchenko

  14. Kazan Federal University, Kazan, Russia

    Elena Tutubalina

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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. https://doi.org/10.1007/978-3-030-37334-4_1

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  • DOI: https://doi.org/10.1007/978-3-030-37334-4_1

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-37333-7

  • Online ISBN: 978-3-030-37334-4

  • eBook Packages: Computer ScienceComputer Science (R0)

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