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Measuring Gender Equality in Universities

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Advances in Soft and Hard Computing (ACS 2018)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 889))

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Abstract

The paper proposes a fuzzy expert system for gender equality evaluation in tertiary education that has been experimented in 6 European universities in Italy, Lithuania, Finland, Germany, Portugal, Ukraine within the EQUAL-IST Horizon 2020 project with the goal to design and implement Gender Equality Plans (GEPs) for IST Research Institutions. We propose a Fuzzy Expert System (FES), a cognitive model that, by replicating the expert way of learning and thinking, allows to formalize qualitative concepts and to reach a synthetic measure of the institution’s gender equality (ranging from 0 to 1 increasing with gender equality achievements), that can be then disentangled in different dimensions. The dimensions included in the model relate to gender equality in the structure of employment (academic and non academic) and in the governance of the universities, to the equal opportunity machinery and to the work-life balance policies promoted by the institutions. The rules and weights in the system are the results of a mixed strategy composed by gender equality experts and by a participatory approach that has been promoted within the EQUAL-IST project. The results show heterogeneity in the final index of gender equality and allow to detect the more critical areas where new policies should be implemented to achieve an improvement in gender equality. The value of the final gender equality index resulting from the application of the FES is then compared to the gender equality perceived by each institution involved in the project and will be used to improve also the awareness in gender gap in important dimensions in tertiary education setting.

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Acknowledgments

This paper has benefited from funding from the EQUAL-IST Horizon 2020 project: Gender Equality Plans for Information Sciences and Technology Research Institutions - Grant Agreement N. 710549.

We thank Dr Alessandro Grandi for having provided the data used to implement the system.

Author information

Authors and Affiliations

  1. Department of Economics Marco Biagi, University of Modena and Reggio Emilia, Modena, Italy

    Tindara Addabbo

  2. Department of Engineering Enzo Ferrari, University of Modena and Reggio Emilia, Modena, Italy

    Claudia Canali

  3. Economics Department, University of Salento, Lecce, Italy

    Gisella Facchinetti & Tommaso Pirotti

Authors
  1. Tindara Addabbo
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  2. Claudia Canali
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  3. Gisella Facchinetti
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  4. Tommaso Pirotti
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Corresponding author

Correspondence to Tommaso Pirotti .

Editor information

Editors and Affiliations

  1. West Pomeranian University of Technology in Szczecin, Szczecin, Poland

    Jerzy Pejaś

  2. West Pomeranian University of Technology in Szczecin , Szczecin, Poland

    Imed El Fray

  3. West Pomeranian University of Technology in Szczecin, Szczecin, Poland

    Tomasz Hyla

  4. Polish Academy of Sciences, Systems Research Institute, Warsaw, Poland

    Janusz Kacprzyk

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Addabbo, T., Canali, C., Facchinetti, G., Pirotti, T. (2019). Measuring Gender Equality in Universities. In: Pejaś, J., El Fray, I., Hyla, T., Kacprzyk, J. (eds) Advances in Soft and Hard Computing. ACS 2018. Advances in Intelligent Systems and Computing, vol 889. Springer, Cham. https://doi.org/10.1007/978-3-030-03314-9_10

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