Analysis of Archetypes to Determine Time Use and Workload Profiles of Spanish University Professors
comunitat-uji-handle:10234/9
comunitat-uji-handle2:10234/174799
comunitat-uji-handle3:10234/174800
comunitat-uji-handle4:
INVESTIGACIONMetadatos
Título
Analysis of Archetypes to Determine Time Use and Workload Profiles of Spanish University ProfessorsFecha de publicación
2023Editor
MDPICita bibliográfica
Cabero, I.; Epifanio, I.; Gual-Arnau, X. Analysis of Archetypes to Determine Time Use and Workload Profiles of Spanish University Professors. Educ. Sci. 2023, 13, 295. https://doi.org/10.3390/ educsci13030295Tipo de documento
info:eu-repo/semantics/articleVersión de la editorial
https://www.mdpi.com/2227-7102/13/3/295Versión
info:eu-repo/semantics/publishedVersionPalabras clave / Materias
Resumen
Allocation of time use is important to develop appropriate policies, especially in terms
of gender equality. Individual well-being depends on many factors, including how time is spent.
Therefore, knowing and analysing ... [+]
Allocation of time use is important to develop appropriate policies, especially in terms
of gender equality. Individual well-being depends on many factors, including how time is spent.
Therefore, knowing and analysing the time use and workload of academic staff is relevant for
academic policy making. We analyse the responses of 703 Spanish academic staff regarding different
activities of paid work and household work (unpaid). We use an innovative machine learning
technique in this field, archetype analysis, which we introduce step by step while exploring our data.
We identify five profiles, and we examine gender inequalities. The findings indicate that there is
a higher prevalence of women in the profiles with a greater workload in household activities and
teaching-related activities, but the prevalence is the same in the profile with a greater workload in
research activities. [-]
Publicado en
Education Sciences, 2023, 13.Entidad financiadora
Ministerio de Ciencia e Innovación | Generaliat Valenciana | Universitat Jaume I
Código del proyecto o subvención
PID2020-118763GA-I00 | PID2020-115930GA-I00 | CIGE/2021/019 | UJI-B2020-22 | UJI-A2022-11
Derechos de acceso
info:eu-repo/semantics/openAccess
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