The intellectual migration of Italian graduates is a significant and enduring trend, marked by patterns shaping the national academic landscape. The migration primarily flows from southern to northern Italy and then extends to European countries or overseas, particularly prominent in STEM fields. Graduates seek enhanced professional opportunities and career prospects in more prosperous regions. Understanding these migration characteristics is crucial for addressing brain drain factors in Italy and beyond. This study focuses on Italian Master’s graduates in 2021-2022, analyzing a dataset of 2,137 CVs from Almalaurea. Various methods, including machine learning and text mining, were used to extract relevant information, including sociographic characteristics (such as gender, place of residence, degree grade, academic discipline, university attended, etc.) and the graduates' educational background. Significant differences were found when the geographical location of the graduates (the university from which they graduated) was taken into account. Therefore, the graduates were divided into three groups for the statistical analysis: Southern, Central and Northern Italy. This cluster approach allowed a comparative study of individual skills (e.g. language and computer skills, Erasmus experience) and future career prospects. These results are crucial for the development of targeted policies and initiatives that effectively counteract brain drain and create an environment that retains and attracts highly skilled workers.
Investigating the ICT skills of Italian graduates’ intellectual migration
Margaret Antonicelli;Angela Maria D’Uggento;Raffaella Girone;Claudia Marin
2023-01-01
Abstract
The intellectual migration of Italian graduates is a significant and enduring trend, marked by patterns shaping the national academic landscape. The migration primarily flows from southern to northern Italy and then extends to European countries or overseas, particularly prominent in STEM fields. Graduates seek enhanced professional opportunities and career prospects in more prosperous regions. Understanding these migration characteristics is crucial for addressing brain drain factors in Italy and beyond. This study focuses on Italian Master’s graduates in 2021-2022, analyzing a dataset of 2,137 CVs from Almalaurea. Various methods, including machine learning and text mining, were used to extract relevant information, including sociographic characteristics (such as gender, place of residence, degree grade, academic discipline, university attended, etc.) and the graduates' educational background. Significant differences were found when the geographical location of the graduates (the university from which they graduated) was taken into account. Therefore, the graduates were divided into three groups for the statistical analysis: Southern, Central and Northern Italy. This cluster approach allowed a comparative study of individual skills (e.g. language and computer skills, Erasmus experience) and future career prospects. These results are crucial for the development of targeted policies and initiatives that effectively counteract brain drain and create an environment that retains and attracts highly skilled workers.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.