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    Chapter Gender INequality Indicator for Academia (GINIA)

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    Author(s)
    Silan, Margherita
    Boccuzzo, Giovanna
    Language
    English
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    Abstract
    The main aim of this work consists on a methodological proposal to represent and measure gender inequality in academia, focusing on the University of Padua. In order to reach our goal, we ended up with two different and complementary tools: a system of indicators and a composite indicator, that we called Gender INequality Indicator for Academia (GINIA). Data used to build and compute GINIA in the University of Padua come both from administrative datasets and from an ad-hoc survey, whose data were adjusted by post-stratification weights. Starting from existing indexes described in the literature, the GINIA is articulated into seven domains: work, money, knowledge, time, power, health, and space. These seven domains are better specified and declined through twelve subdomains that are measured by seventeen variables. The composite indicator is the result of the three-step aggregation and weighting procedure: 1) variables are aggregated into subdomains with an arithmetic mean and equal weights; 2) subdomains are aggregated into domains by arithmetic mean with equal weights; 3) domains are aggregated into GINIA indicator by a weighted geometric mean. Indeed, we think that variables related to the same domain can compensate each other, while this consideration is not plausible for domains. Additionally, the weights in the last step are calculated through a preference matrix based on the responses of the respondents about the importance they give to each domain. The indicator can change substantially if we change the methods of weighting or aggregation. Therefore, an uncertainty and sensitivity analysis was undertaken to assess the robustness of the composite indicator as the final step of the analysis with the computation of bootstrap confidence intervals.
    Book
    ASA 2022 Data-Driven Decision Making
    URI
    https://library.oapen.org/handle/20.500.12657/74926
    Keywords
    Gender equality; Composite indicator; Sensitivity analysis
    DOI
    10.36253/979-12-215-0106-3.54
    ISBN
    9791221501063, 9791221501063
    Publisher
    Firenze University Press, Genova University Press
    Publication date and place
    Florence, 2023
    Series
    Proceedings e report, 134
    Classification
    Society and Social Sciences
    Pages
    6
    Rights
    https://creativecommons.org/licenses/by/4.0/
    • Imported or submitted locally

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    License

    • If not noted otherwise all contents are available under Attribution 4.0 International (CC BY 4.0)

    Credits

    • logo EU
    • This project received funding from the European Union's Horizon 2020 research and innovation programme under grant agreement No 683680, 810640, 871069 and 964352.

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