!is paper investigates the cumulative e"ects of social origin, school tracking, and academic performance on students’ educational and occupational expectations in Italy. Drawing on PISA 2022 data, the analysis focuses on low- performing students and explores how school pathways and socio-economic background shape both aspirations and future trajectories. Using a three-step quantitative approach - including OLS and logistic regressions - we assess the impact of academic track, family background, gender, geographical area, and migrant status on student performance, tertiary education expectations, and job aspirations. Findings show that early school tracking strongly predicts academic achievement and future plans, o#en amplifying pre-existing inequalities. Students from vocational tracks and disadvantaged regions are signicantly more likely to perform poorly and to expect lower-status occupations, while general track students express higher aspirations regardless of prior performance. !e results highlight a “chain e"ect” of disadvantage, in which school choices, performance, and expectations are shaped by intersecting structural factors. We also explore gender paradoxes, with girls outperforming boys yet facing labour market inequalities. !e study calls for targeted policies to support vulnerable groups - especially students in vocational tracks, migrants, and those in southern regions - and to foster inclusive school environments that expand the capacity to aspire.
Giancola et al. (Wed,) studied this question.