The Circulation of Socioeconomic Measurements in Chilean Education: Producing and Reinforcing Vulnerable Bodies in School Spaces

In the context of global inequality and neoliberal educational governance, this research examines how specific socioeconomic measurements in Chilean education, such as the School Vulnerability Index (SVI), the SIMCE socioeconomic groups (GSE), and PISA's EESC, contribute to the reproduction of social hierarchies. This ethnographic study from a new materialism approach traces the development and circulation of these measurements, focusing on their inclusion or exclusion of specific variables, such as biological and cultural factors, and their impact on how vulnerability is constructed and recognized in school environments.

Through 23 interviews with national professionals involved in creating and implementing these indices, along with ethnographic work in both an elite private school and a public school, the research highlights how these tools produce stable and "acceptable" socioeconomic differences that influence school practices and student outcomes. The analysis reveals that these measurements often reinforce the same inequalities they aim to address, framing them as natural responses to poor performance.

This presentation contributes to the discussion on how educational policies, despite their intention to promote equity and inclusion, can perpetuate internal segregation and social stratification. It questions how algorithms and measurement techniques, deeply embedded in cultural and biological discourses, create new scales of vulnerability and privilege that circulate nationally and globally. Our findings reveal that the process of 'whitening' vulnerability is used as a strategy to reinforce privileged positions, while the knowledge of authorities further entrenches the subordinate status of vulnerable groups. This research calls for reevaluating the role of socioeconomic measurements in educational policy, advocating for a shift towards approaches that genuinely promote equity and inclusion while questioning the over-reliance on data-driven algorithms in shaping educational outcomes.