This paper aims to assess gender bias in Italian university student mobility controlling for the field of study. It uses data from the Italian National Student Archive (Anagrafe Nazionale degli Studenti – ANS) for the cohort of freshmen enrolled in the 2017 academic year. The analysis is firstly carried out at the national level, and secondly, it focuses on macro-geographical areas. University mobility choices are thus investigated from a gender perspective, conditioning upon other theoretically relevant characteristics collected for the prospective first-year university student population enrolled in 2017. The macro-regional comparison unfolds across the following areas: North and Centre, Southern Italy, main Islands (Sicily and Sardinia). We analyze data in a regression setting (logit models) within the multilevel framework, which considers students at level 1, and the field of study at level 2. Gender differences in the propensity to be a mover – conditional upon the choice of the field of study – were captured by introducing random intercepts to account for the clustering of students in fields of study and random slopes to allow the gender effect to differ among them. As a result, we consider how the propensity of being a mover is affected by gender and field of study and depict peculiarities of students belonging to different macro geographical areas and concerning the main evidence at a national level.

Gender bias in university student mobility: a cohort analysis in Italy

Isabella Sulis;Barbara Barbieri;Luisa Salaris
;
Mariano Porcu
2023-01-01

Abstract

This paper aims to assess gender bias in Italian university student mobility controlling for the field of study. It uses data from the Italian National Student Archive (Anagrafe Nazionale degli Studenti – ANS) for the cohort of freshmen enrolled in the 2017 academic year. The analysis is firstly carried out at the national level, and secondly, it focuses on macro-geographical areas. University mobility choices are thus investigated from a gender perspective, conditioning upon other theoretically relevant characteristics collected for the prospective first-year university student population enrolled in 2017. The macro-regional comparison unfolds across the following areas: North and Centre, Southern Italy, main Islands (Sicily and Sardinia). We analyze data in a regression setting (logit models) within the multilevel framework, which considers students at level 1, and the field of study at level 2. Gender differences in the propensity to be a mover – conditional upon the choice of the field of study – were captured by introducing random intercepts to account for the clustering of students in fields of study and random slopes to allow the gender effect to differ among them. As a result, we consider how the propensity of being a mover is affected by gender and field of study and depict peculiarities of students belonging to different macro geographical areas and concerning the main evidence at a national level.
2023
gender bias, university choices, mobility, multilevel analysis, mixed effect models
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11584/386786
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