Beyond Vocation: Understanding Sociocultural and Opinion-Based Determinants of STEMM Career Choice in Peruvian Women

This study examines the underrepresentation of women in STEMM (Science, Technology, Engineering, Mathematics, and Medicine) within Peruvian public universities and identifies factors associated with women’s program choice. A cross-sectional survey was administered to first-term students across three public institutions spanning Peru’s Highlands, Coast, and Amazon regions. Data from 1142 students (145 women) were used for descriptive analysis of segregation, while an inferential sample (N = 152; 76 STEMM, 76 non-STEMM) was used for modeling. The instrument was an adapted “University Students’ Questionnaire on STEM Studies in Higher Education (QSTEMHE)” (Cronbach’s α = 0.89). Descriptive statistics and a penalized (Firth) binary logistic regression were used to evaluate sociodemographic, contextual/experiential, and motivational predictors of enrolling in a STEMM major. The cross-sectional design limits causal inference, and perception data are subject to self-report biases. Women accounted for 12.7% of STEMM enrolment overall, with pronounced horizontal segregation: engineering programs frequently recorded critically low female participation (≈3–5% in Civil, Mechanical, and Computer Engineering), whereas Medicine and Sanitary Engineering showed comparatively higher representation (27–38%). Perception data indicated that STEMM students more strongly rejected gender–ability stereotypes than non-STEMM peers, although a substantial proportion still reported constraining gender expectations and rigid household roles. In the penalized regression, Prior Interest in STEM (OR = 7.76; p = 0.018) and Motivation: Opportunities (OR = 2.24; p = 0.0001) significantly increased the probability of choosing STEMM. Crucially, Ethnicity emerged as a significant barrier: identifying as ‘Quechua’ (OR = 0.19; p = 0.0004) or ‘Other(s)’ (OR = 0.16; p = 0.011) significantly decreased this likelihood. Age, area of residence, and Motivation: Altruism was not significant. Findings support early, gender-responsive career guidance, mentoring, addressing intersectional ethnic barriers, and targeted financial aid to strengthen women’s participation and retention in STEMM.