What contributes to gender parity in science? A Bayesian Network analysis González-Salmón, Elvira Chinchilla-Rodríguez, Zaida Nane, Gabriela F. Robinson García, Nicolás Scientometrics Gender This work is part of the COMPARE project (Ref: PID2020-117007RA-I00) and the RESPONSIBLE project (Ref: PID2021-128429NB-I00), both funded by the Spanish Ministry of Science (Ref: MCIN/AEI /10.13039/501100011033 FSE invierte en tu futuro). E.G-S. is currently supported by an FPU grant from the Spanish Ministry of Science (Ref: FPU2021/02320). N.R-G. is currently supported by a Ramón y Cajal grant from the Spanish Ministry of Science (Ref: RYC2019-027886-I). We retrieve data from Dimensions, the World Bank Open Data (WBOA) and the UNESCO Institute for Statistics (UIS) to construct a country level longitudinal dataset including the yearly number of researchers by gender. Our aim is to predict when each country will reach gender parity and which factors may influence the increase of the proportion of women in science. Here we present some preliminary findings using the ARIMA and Exponential Smoothing forecasting models, and a first attempt to look into influencing factors using Bayesian Networks. 2024-07-02T07:32:46Z 2024-07-02T07:32:46Z 2024-07-01 info:eu-repo/semantics/conferenceObject Published version: González-Salmón, E. et al. What contributes to gender parity in science? A Bayesian Network analysis. 2024 https://hdl.handle.net/10481/92908 10.5281/zenodo.12609269 eng http://creativecommons.org/licenses/by-nc-nd/4.0/ info:eu-repo/semantics/openAccess Attribution-NonCommercial-NoDerivatives 4.0 Internacional