Garcia Montalvo, JoséAlimonti, DanieleReiland, SonjaVernos, IsabelleUniversitat Pompeu Fabra. Departament d'Economia i Empresa2024-11-142024-11-142020-10-01http://hdl.handle.net/10230/68671Women are underrepresented in the top ranks of the scientific career, including the biomedical disciplines. This is not generally the result of explicit and easily recognizable gender biases but the outcome of decisions with many components of unconscious nature that are difficult to assess. Evidence suggests that implicit gender stereotypes influence perceptions as well as decisions. To explore these potential reasons of women's underrepresentation in life sciences we analyzed the outcome of gender-science and gender-career Implicit Association Tests (IAT) taken by 2,589 scientists working in high profile biomedical research centers. We found that male-science association is less pronounced among researchers than in the general population (34% below the level of the general population). However, this difference is mostly explained by the low level of the IAT score among female researchers. Despite the highly meritocratic view of the academic career, male scientists have a high level of male-science association (261% the level among women scientists), similar to the general population.application/pdfengL'accés als continguts d'aquest document queda condicionat a l'acceptació de les condicions d'ús establertes per la següent llicència Creative CommonsGender stereotype and the scientific career of women: Evidence from biomedical research genters<resourceType xmlns="http://datacite.org/schema/kernel-3" resourceTypeGeneral="Other">info:eu-repo/semantics/workingPaper</resourceType><subject xmlns="http://datacite.org/schema/kernel-3" subjectScheme="keyword">gender bias</subject><subject xmlns="http://datacite.org/schema/kernel-3" subjectScheme="keyword">implicit association test</subject><subject xmlns="http://datacite.org/schema/kernel-3" subjectScheme="keyword">research centers</subject><subject xmlns="http://datacite.org/schema/kernel-3" subjectScheme="keyword">scientific career</subject><subject xmlns="http://datacite.org/schema/kernel-3" subjectScheme="keyword">Statistics, Econometrics and Quantitative Methods</subject><rights xmlns="http://datacite.org/schema/kernel-3">info:eu-repo/semantics/openAccess</rights>