The underrepresentation of females in STEM fields hinders productivity and perpetuates labor market inequalities. In countries where children are tracked into educational trajectories from high school (as in Italy, 8th grade), it is crucial to understand what drives gendered pathways before educational segregation starts. Collecting experimental and survey data from Italian 8th graders, we find that perceived advantageous comparisons with peers in math ability and counter-stereotypical beliefs increase the likelihood that girls enroll in a math-intensive track during high school. Policy initiatives improving girls’ expectations about their relative math performance may thus encourage female students to pursue STEM tracks.

Decoding girls’ STEM high school choices: Ability, confidence, stereotypes / Cappelletti, Dominique; Vittoria Levati, M.; Ploner, Matteo. - In: JOURNAL OF POLICY MODELING. - ISSN 0161-8938. - 2026:(2026). [10.1016/j.jpolmod.2026.107046]

Decoding girls’ STEM high school choices: Ability, confidence, stereotypes

Cappelletti, Dominique
Primo
;
Ploner, Matteo
Ultimo
2026-01-01

Abstract

The underrepresentation of females in STEM fields hinders productivity and perpetuates labor market inequalities. In countries where children are tracked into educational trajectories from high school (as in Italy, 8th grade), it is crucial to understand what drives gendered pathways before educational segregation starts. Collecting experimental and survey data from Italian 8th graders, we find that perceived advantageous comparisons with peers in math ability and counter-stereotypical beliefs increase the likelihood that girls enroll in a math-intensive track during high school. Policy initiatives improving girls’ expectations about their relative math performance may thus encourage female students to pursue STEM tracks.
2026
Cappelletti, Dominique; Vittoria Levati, M.; Ploner, Matteo
Decoding girls’ STEM high school choices: Ability, confidence, stereotypes / Cappelletti, Dominique; Vittoria Levati, M.; Ploner, Matteo. - In: JOURNAL OF POLICY MODELING. - ISSN 0161-8938. - 2026:(2026). [10.1016/j.jpolmod.2026.107046]
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