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dc.contributor.authorSilan, Margherita
dc.contributor.authorBoccuzzo, Giovanna
dc.date.accessioned2023-08-03T15:07:07Z
dc.date.available2023-08-03T15:07:07Z
dc.date.issued2023
dc.identifierONIX_20230803_9791221501063_122
dc.identifier.issn2704-5846
dc.identifier.urihttps://library.oapen.org/handle/20.500.12657/74926
dc.description.abstractThe 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.
dc.languageEnglish
dc.relation.ispartofseriesProceedings e report
dc.subject.classificationthema EDItEUR::J Society and Social Sciencesen_US
dc.subject.otherGender equality
dc.subject.otherComposite indicator
dc.subject.otherSensitivity analysis
dc.titleChapter Gender INequality Indicator for Academia (GINIA)
dc.typechapter
oapen.identifier.doi10.36253/979-12-215-0106-3.54
oapen.relation.isPublishedBy9223d3ac-6fd2-44c9-bb99-5b98ca9d2fad
oapen.relation.isPartOfBook863aa499-dbee-4191-9a14-3b5d5ef9e635
oapen.relation.isbn9791221501063
oapen.series.number134
oapen.pages6
oapen.place.publicationFlorence


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